diff --git a/.gitignore b/.gitignore index e56a54c..e4e4eff 100644 --- a/.gitignore +++ b/.gitignore @@ -15,6 +15,12 @@ fig* *.tar *.whl +# Allow these CSVs needed for the floris interface +!MITRotor/FlorisInterface/IEA_15mw_rotor.csv +!examples/examples_in/* + +Validation/ + ### Python ### # Byte-compiled / optimized / DLL files __pycache__/ @@ -188,4 +194,10 @@ poetry.toml # LSP config files pyrightconfig.json -# End of https://www.toptal.com/developers/gitignore/api/python \ No newline at end of file +# End of https://www.toptal.com/developers/gitignore/api/python + +.DS_Store +examples/Tune_Cases/ +*dbg* +DISCON.IN +*txt \ No newline at end of file diff --git a/MITRotor/Aerodynamics.py b/MITRotor/Aerodynamics.py index 265872c..bd761a0 100644 --- a/MITRotor/Aerodynamics.py +++ b/MITRotor/Aerodynamics.py @@ -7,7 +7,7 @@ from numpy.typing import ArrayLike from .RotorDefinition import RotorDefinition -from .Geometry import BEMGeometry +from .Geometry import BEMGeometry, expand_to_Nr_Ntheta from UnifiedMomentumModel.Utilities.Geometry import calc_eff_yaw __all__ = [ @@ -269,13 +269,16 @@ def __call__( AerodynamicProperties: Calculated aerodynamic properties stored in AerodynamicProperties object. """ + tsr = expand_to_Nr_Ntheta(tsr) + pitch = expand_to_Nr_Ntheta(pitch) # calculate values in "yaw-only" frame local_yaw = -self.eff_yaw Vax = U * ((1 - an) * np.cos(local_yaw)) + theta_eff = geom.theta_mesh + self.delta_theta Vtan = ( (1 + aprime) * tsr * geom.mu_mesh - U * (1 - an) - * np.cos(self.eff_theta_mesh) + * np.cos(theta_eff) * np.sin(local_yaw) ) @@ -291,8 +294,8 @@ def __call__( an = an, aprime = aprime, solidity = solidity, - U = U * np.ones(geom.shape), - wdir = wdir * np.ones(geom.shape), + U = U * np.ones_like(geom.mu_mesh), + wdir = wdir * np.ones_like(geom.mu_mesh), Vax = Vax, Vtan = Vtan, aoa = aoa, diff --git a/MITRotor/BEMSolver.py b/MITRotor/BEMSolver.py index daea9bc..fcd7ac1 100644 --- a/MITRotor/BEMSolver.py +++ b/MITRotor/BEMSolver.py @@ -7,12 +7,13 @@ from . import Momentum, TipLoss from .Aerodynamics import AerodynamicModel, AerodynamicProperties, DefaultAerodynamics -from .Geometry import BEMGeometry +from .Geometry import BEMGeometry, expand_to_Np, expand_to_Nr_Ntheta from .RotorDefinition import RotorDefinition from .TangentialInduction import DefaultTangentialInduction, TangentialInductionModel from UnifiedMomentumModel.Utilities.Geometry import calc_eff_yaw + def average(geometry: BEMGeometry, value: ArrayLike, grid: Literal["sector", "annulus", "rotor"] = "rotor"): # Assuming the function returns a 2D grid of values @@ -58,13 +59,13 @@ def solidity(self, grid: Literal["sector ", "annulus", "rotor"] = "rotor"): def U(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): return average(self.geom, self.aero_props.U, grid) - def wdir(self, grid: Literal["sector ", "annulus", "rotor"] = "rotor"): + def wdir(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): return average(self.geom, self.aero_props.wdir, grid) def Vax(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): return average(self.geom, self.aero_props.Vax, grid) - def Vtan(self, grid: Literal["sector ", "annulus", "rotor"] = "rotor"): + def Vtan(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): return average(self.geom, self.aero_props.Vtan, grid) def W(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): @@ -91,29 +92,27 @@ def Ctan(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): def Cx(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): return average(self.geom, self.aero_props.C_x_corr, grid) - def Ctau(self, grid: Literal["sector ", "annulus", "rotor"] = "rotor"): + def Ctau(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): return average(self.geom, self.aero_props.C_tau_corr, grid) - def Ctau_uncorr(self, grid: Literal["sector ", "annulus", "rotor"] = "rotor"): + def Ctau_uncorr(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): return average(self.geom, self.aero_props.C_tau, grid) def F(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): return average(self.geom, self.aero_props.F, grid) def Cp(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): - dCp = ( - self.tsr - * self.geom.mu_mesh - * self.Ctau_uncorr(grid="sector") - ) + tsr = np.asarray(self.tsr) + if tsr.ndim == 1: + tsr = expand_to_Nr_Ntheta(tsr) + dCp = (tsr * self.geom.mu_mesh * self.Ctau_uncorr(grid="sector")) return average(self.geom, dCp, grid=grid) def Cp_corr(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): - dCp = ( - self.tsr - * self.geom.mu_mesh - * self.Ctau(grid="sector") - ) + tsr = np.asarray(self.tsr) + if tsr.ndim == 1: + tsr = expand_to_Nr_Ntheta(tsr) + dCp = (tsr * self.geom.mu_mesh * self.Ctau(grid="sector")) return average(self.geom, dCp, grid=grid) def Ct(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): @@ -128,6 +127,13 @@ def Ctprime(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): eff_yaw = calc_eff_yaw(self.yaw, self.tilt) Ctprime = self.Ct(grid="sector") / ((1 - self.a(grid="sector")) ** 2 * np.cos(eff_yaw) ** 2) return average(self.geom, Ctprime, grid=grid) + + # TODO: make sure that this is correct!! Check with np.isclose(Cp, tsr * Cq) + def Cq(self, grid: Literal["sector", "annulus", "rotor"] = "rotor"): + mu = np.asarray(self.geom.mu_mesh) + Ctau = self.Ctau_uncorr(grid="sector") + dCq = mu * Ctau + return average(self.geom, dCq, grid=grid) @adaptivefixedpointiteration(max_iter=500, relaxations=[0.25, 0.5, 0.96]) @@ -169,21 +175,37 @@ def sample_points(self, yaw: float = 0.0, tilt: float = 0.0) -> tuple[ArrayLike, return X, Y, Z def pre_process(self, pitch, tsr, yaw = 0, tilt = 0, **kwargs): + pitch, tsr = np.asarray(pitch), np.asarray(tsr) + yaw, tilt = np.asarray(yaw), np.asarray(tilt) + self.scalar_inputs = (pitch.ndim == 0) & (tsr.ndim == 0) & (yaw.ndim == 0) & (tilt.ndim == 0) + if not self.scalar_inputs: + assert len(pitch) == len(tsr) == len(yaw) == len(tilt), "Setpoint arrays should be the same lenght" # switch reference frame to a "yaw-only" frame where y' is aligned with the lateral wake - self.aerodynamic_model.eff_yaw = calc_eff_yaw(yaw, tilt) - if tilt == 0: - dtheta = 0 - elif yaw == 0: - dtheta = np.pi / 2 - else: # non-zero yaw and tilt - sin_eff = np.sin(self.aerodynamic_model.eff_yaw) - dtheta = np.arccos(np.sin(yaw) / sin_eff) - self.aerodynamic_model.eff_theta_mesh = self.geometry.theta_mesh + dtheta + yaw, tilt = np.broadcast_arrays(yaw, tilt) + eff_yaw = calc_eff_yaw(yaw, tilt) + # initialize dtheta + dtheta = np.zeros_like(eff_yaw, dtype=float) + # masks + yaw_zero = (yaw == 0) + not_tilt_zero = np.logical_not(tilt == 0) + # case1: yaw == 0 and tilt != 0 + case1 = yaw_zero & not_tilt_zero + dtheta[case1] = np.pi / 2 + # case2: yaw != 0 and tilt != 0 + case2 = np.logical_not(yaw_zero) & not_tilt_zero + dtheta[case2] = np.arccos( + np.sin(yaw[case2]) / np.sin(eff_yaw[case2]) + ) + # expand everything to the correct dimensions to ensure broadcasting + self.aerodynamic_model.eff_yaw = expand_to_Nr_Ntheta(eff_yaw) + self.aerodynamic_model.delta_theta = expand_to_Nr_Ntheta(dtheta) + self.geometry.mu_mesh = expand_to_Np(self.geometry.mu_mesh) + self.geometry.theta_mesh = expand_to_Np(self.geometry.theta_mesh) return def initial_guess(self, *args, **kwargs) -> Tuple[ArrayLike, ...]: - a = (1 / 3) * np.ones(self.geometry.shape) - aprime = np.zeros(self.geometry.shape) + a = (1 / 3) * np.ones_like(self.geometry.mu_mesh) + aprime = np.zeros_like(self.geometry.mu_mesh) return a, aprime @@ -198,8 +220,8 @@ def residual( tilt: ArrayLike = 0.0, ) -> Tuple[ArrayLike, ...]: an, aprime = x - U = np.ones(self.geometry.shape) if U is None else U - wdir = np.zeros(self.geometry.shape) if wdir is None else wdir + U = np.ones_like(self.geometry.mu_mesh) if U is None else U + wdir = np.zeros_like(self.geometry.mu_mesh) if wdir is None else wdir aero_props = self.aerodynamic_model( an = an, @@ -221,12 +243,25 @@ def residual( return e_an, e_aprime def post_process(self, result: FixedPointIterationResult, pitch, tsr, yaw = 0, U=None, wdir=None, tilt = 0.0) -> BEMSolution: - U = np.ones(self.geometry.shape) if U is None else U - wdir = np.zeros(self.geometry.shape) if wdir is None else wdir + U = np.ones_like(self.geometry.mu_mesh) if U is None else U + wdir = np.zeros_like(self.geometry.mu_mesh) if wdir is None else wdir an, aprime = result.x aero_props = self.aerodynamic_model(an, aprime, pitch, tsr, yaw, self.rotor, self.geometry, U, wdir, tilt = tilt) aero_props.F = self.tiploss_model(aero_props, pitch, tsr, yaw, self.rotor, self.geometry, tilt = tilt) avg_Ct = average(self.geometry, aero_props.C_x) u4,v4,w4 = self.momentum_model.compute_initial_wake_velocities(avg_Ct, yaw, tilt = tilt) + if self.scalar_inputs: # if all setpoints were scalars + # return single values as scalars + pitch, tsr, yaw, tilt = [np.asarray(x).item() for x in (pitch, tsr, yaw, tilt)] + u4, v4, w4 = [np.asarray(x).item() for x in (u4, v4, w4)] + # remove unneeded extra axis from Ntheta x Nr arrays + an = np.squeeze(an) + aprime = np.squeeze(aprime) + self.geometry.theta_mesh = np.squeeze(self.geometry.theta_mesh) + self.geometry.mu_mesh = np.squeeze(self.geometry.mu_mesh) + for key, value in vars(aero_props).items(): + if isinstance(value, np.ndarray): + setattr(aero_props, key, np.squeeze(value)) + return BEMSolution(pitch, tsr, yaw, aero_props, self.geometry, result.converged, result.niter, u4, v4, tilt = tilt, w4 = w4) diff --git a/MITRotor/FlorisInterface/FlorisInterface.py b/MITRotor/FlorisInterface/FlorisInterface.py new file mode 100644 index 0000000..102575f --- /dev/null +++ b/MITRotor/FlorisInterface/FlorisInterface.py @@ -0,0 +1,172 @@ +import os +import numpy as np +import polars as pl +from attrs import define, field +from typing import Optional +from scipy.interpolate import interp1d, RegularGridInterpolator +# FLORIS Imports +from floris.type_dec import floris_float_type, NDArrayFloat +from floris.core.turbine.operation_models import BaseOperationModel +from floris.core.rotor_velocity import average_velocity +from floris.utilities import cosd +# MITRotor / UMM Imports +from MITRotor.ReferenceTurbines import IEA15MW +from MITRotor.Momentum import UnifiedMomentum +from MITRotor.Geometry import BEMGeometry +from MITRotor.TipLoss import NoTipLoss +from MITRotor.BEMSolver import BEM +from MITRotor.FlorisInterface.ROSCOInterface import query_controls +from UnifiedMomentumModel.Utilities.Geometry import calc_eff_yaw + +# default rotor if none provided by user (IEA 15MW) +def default_bem_factory(): + return BEM( + rotor=IEA15MW(), + momentum_model=UnifiedMomentum(averaging="rotor"), + geometry=BEMGeometry(Nr=10, Ntheta=20), + tiploss_model=NoTipLoss() + ) +# pitch vs windspeed interpolater if none provided by user +# for IEA 15MW from figure 2 (https://docs.nrel.gov/docs/fy22osti/82134.pdf) +def default_pitch_interp(): + module_dir = os.path.dirname(__file__) + pitch_file = os.path.join(module_dir, "IEA_15mw_rotor.csv") + df = pl.read_csv(pitch_file) + wind_table = df["Wind [m/s]"].to_numpy() + pitch_table = np.deg2rad(df["Pitch [deg]"]) + # TODO: should fill_value be extrapolate? + return interp1d(wind_table, pitch_table, kind="linear", fill_value="extrapolate", bounds_error=False) + +# tsr vs windspeed interpolater if none provided by user +# for IEA 15MW from figure 2 (https://docs.nrel.gov/docs/fy22osti/82134.pdf) +def default_tsr_interp(): + module_dir = os.path.dirname(__file__) + tsr_file = os.path.join(module_dir, "IEA_15mw_rotor.csv") + df = pl.read_csv(tsr_file) + wind_table = df["Wind [m/s]"].to_numpy() + tip_speed_table = df["Tip Speed [m/s]"].to_numpy() + tsr_table = tip_speed_table / wind_table + # TODO: should fill_value be extrapolate? + return interp1d(wind_table, tsr_table, kind="linear", fill_value="extrapolate", bounds_error=False) + +@define +class MITRotorTurbine(BaseOperationModel): + """ + Turbine operation model as described by Liew et al. (2024). + + Args: + bem_model (BEM): optional BEM model as defined in MITRotor, defaults to IEA15MW with UMM momentum model + pitch_interp (interp1d): optional 1D interpolator for pitch trajectory based on wind speed, + defaults to IEA15MW Figure 2 (https://docs.nrel.gov/docs/fy22osti/82134.pdf) + tsr_interp (interp1d): optional 1D interpolator for tsr trajectory based on wind speed, + defaults to IEA15MW Figure 2 (https://docs.nrel.gov/docs/fy22osti/82134.pdf) + + Methods: + power + thrust_coefficient + axial_induction + """ + # user can define a BEM model if they want a different rotor, momentum model, or geometry + bem_model = field(init = True, factory = default_bem_factory, type = BEM) + gen_eff = field(init = True, default = 95.756, type=Optional[float]) # [%] + eff_ratio = field(init=True, default=None, type=Optional[float]) # allow override + + # TODO: figure out the default factory for the tsr and pitch!! Use saved file... + # create interp objects based on pitch and tsr csvs + # pitch_interp = field(init = True, factory = default_pitch_interp, type = interp1d, repr = False) + pitch_interp = field(init = True, default = None, type = RegularGridInterpolator, repr = False) + pitch_rad = field(init = True, default = True, type = bool) + # tsr_interp = field(init = True, factory = default_tsr_interp, type = interp1d, repr = False) + tsr_interp = field(init = True, default = False, type = RegularGridInterpolator, repr = False) + rated_rotor_speed = field(init=True, default=None, type=Optional[float]) # [rad/s] + + # save most recent solution by unique floris arguments + _last_key = field(init=False, default=None, type = bytes) + _a = field(init=False, default=None, type = NDArrayFloat) + _Ct = field(init=False, default=None, type = NDArrayFloat) + _power = field(init=False, default=None, type = NDArrayFloat) + + def __attrs_post_init__(self): + if self.eff_ratio is None: + gearbox_eff = self.bem_model.rotor.rosco_values[1] + self.eff_ratio = (self.gen_eff / 100.0) * (gearbox_eff / 100.0) + + def _get_state_key(self, velocities: np.ndarray, yaw_angles: np.ndarray, tilt_angles: np.ndarray) -> tuple: + # saves key to uniquely identify farm state -> avoids re-solving for calls to power, thrust, and induction for same state + return velocities.tobytes(), yaw_angles.tobytes(), tilt_angles.tobytes() + + def _update_solution(self, + velocities: NDArrayFloat, + air_density: float, + yaw_angles: NDArrayFloat, + tilt_angles: NDArrayFloat, + average_method: str = "cubic-mean", + cubature_weights: Optional[NDArrayFloat] = None, + power_thrust_table: Optional[dict] = None, + **_, + ): + # create cache key for current inputs + key = self._get_state_key(velocities, yaw_angles, tilt_angles) + # update solution if conditions are different + if key != self._last_key: + n_findex, n_turbines = yaw_angles.shape + + # save new key and clear fields + self._last_key = key + self._a = np.empty((n_findex, n_turbines), dtype=floris_float_type) + self._Ct = np.empty((n_findex, n_turbines), dtype=floris_float_type) + self._power = np.empty((n_findex, n_turbines), dtype=floris_float_type) + + # compute the power-effective wind speed across the rotor + rotor_average_velocities = average_velocity( # NOT adjusted for yaw + velocities=velocities, + method=average_method, + cubature_weights=cubature_weights, + ) + # calculate rotor area + rotor_area = np.pi * self.bem_model.rotor.R**2 + + # get setpoints + yaw, tilt = np.deg2rad(yaw_angles), np.deg2rad(tilt_angles) + eff_yaw = calc_eff_yaw(yaw, tilt) + pitch = query_controls(self.pitch_interp, rotor_average_velocities, eff_yaw) + tsr = query_controls(self.tsr_interp, rotor_average_velocities, eff_yaw) + # pitch = self.pitch_interp(rotor_normal_average_velocities) + if not self.pitch_rad: + pitch = np.deg2rad(pitch) + + # if self.rated_rotor_speed is None: + # tsr = self.tsr_interp(rotor_normal_average_velocities) + # else: + # R = self.bem_model.rotor.R + # tsr_lookup = self.tsr_interp(rotor_normal_average_velocities) + # omega_lookup = tsr_lookup * rotor_normal_average_velocities / R # rad/s implied by lookup + # tsr_from_rated_speed = self.rated_rotor_speed * R / rotor_average_velocities # above-rated branch + # tsr = np.where(omega_lookup <= self.rated_rotor_speed, tsr_lookup, tsr_from_rated_speed) + # tsr = np.maximum(tsr, 0.0) + + for tindex in range(n_turbines): + # solve BEM + bem_sol = self.bem_model(pitch[:, tindex], tsr[:, tindex], yaw = yaw[:, tindex], tilt = tilt[:, tindex]) + # get induction and thrust coeff + self._a[:, tindex] = bem_sol.a() + self._Ct[:, tindex] = bem_sol.Ct() + # compute power -> need generator efficiency + self._power[:, tindex] = ( + 0.5 * bem_sol.Cp() * air_density * rotor_area + * (rotor_average_velocities[:, tindex])**3 + * self.eff_ratio + ) + return + + def power(self, **kwargs) -> NDArrayFloat: + self._update_solution(**kwargs) + return self._power + + def thrust_coefficient(self, **kwargs) -> NDArrayFloat: + self._update_solution(**kwargs) + return self._Ct + + def axial_induction(self, **kwargs) -> NDArrayFloat: + self._update_solution(**kwargs) + return self._a \ No newline at end of file diff --git a/MITRotor/FlorisInterface/IEA_15mw_rotor.csv b/MITRotor/FlorisInterface/IEA_15mw_rotor.csv new file mode 100644 index 0000000..c5ce68c --- /dev/null +++ b/MITRotor/FlorisInterface/IEA_15mw_rotor.csv @@ -0,0 +1,51 @@ +Wind [m/s],Pitch [deg],Power [MW],Power Coefficient [-],Aero Power Coefficient [-],Rotor Speed [rpm],Tip Speed [m/s],Thrust [MN],Thrust Coefficient [-],Torque [MNm],Torque Coefficient [-],Blade Moment [MNm],Blade Moment Coefficient [-] +3,3.920293066,0.042500121,0.056434434,0.05897929,5,63.33974388,0.202909425,0.808309128,0.0848295,0.002806784,5.980185544,0.197868559 +3.54953237,3.913016973,0.292273273,0.234311418,0.244877465,5,63.33974388,0.275784048,0.784774049,0.583372359,0.01378822,7.854972515,0.185655162 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new file mode 100644 index 0000000..5ed046e --- /dev/null +++ b/MITRotor/FlorisInterface/ROSCOInterface.py @@ -0,0 +1,770 @@ +# Python modules +import os +from collections import deque +from ctypes import cdll, POINTER, c_float, c_int32, c_char_p, create_string_buffer +from dataclasses import dataclass +import numpy as np +from pathlib import Path +from scipy.interpolate import interp1d, RegularGridInterpolator +import warnings +# ROSCO toolbox modules +from rosco import discon_lib_path as lib_name +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox import control_interface as ROSCO_ci +from rosco.toolbox import sim as ROSCO_sim +from rosco.toolbox.utilities import write_rotor_performance, write_DISCON +from rosco.toolbox.inputs.validation import load_rosco_yaml + +# ----------------------------- +# Create Ct/Cp surfaces +# ----------------------------- +def load_from_mitrotor( + turbine, bem, refine_cp_surface=False, + TurbineName = "IEA15MW", rotor_performance_filename = 'Cp_Ct_Cq.txt', + GenEff = 95.756, generator_inertia = 1836784, + yaw = 0.0 +): + ''' + Loads rotor performance information by running MITRotor aerodynamic analysis. + + Based on ROSCO function load_from_ccblade: + https://github.com/NatLabRockies/ROSCO/blob/main/rosco/toolbox/turbine.py#L272 + + Args: + turbine (rosco.toolbox.turbine.Turbine): ROSCO turbine object + bem (MITRotor.BEM): MITRotor BEM object + refine_cp_surface (boolean): if true then smooth cp surface, else false + TurbineName (string): string turbine name; default to "IEA15MW" + GenEff (float): generator efficiency (0-100); defaults to IEA15MW value 95.756 + generator_inertia (float): generator_inertia; defaults to IEA15MW value 1836784 [kg m^2] + + Returns: turbine with new fields needed for ROSCO controller, including Ct, Cp, and Cq surfaces + ''' + # Set turbine parameters + turbine.TurbineName = TurbineName + turbine.rotor_performance_filename = rotor_performance_filename + + (tower_height, gearbox_efficiency, gearbox_ratio, air_density) = bem.rotor.rosco_values + turbine.TowerHt = tower_height + turbine.GBoxEff = gearbox_efficiency + turbine.Ng = gearbox_ratio + turbine.rho = air_density + + turbine.GenEff = GenEff + turbine.generator_inertia = generator_inertia + + turbine.yaw = yaw + turbine.rotor_radius = bem.rotor.R + turbine.J = turbine.rotor_inertia + turbine.generator_inertia * turbine.Ng**2 + turbine.rated_torque = turbine.rated_power/(turbine.GenEff/100*turbine.rated_rotor_speed*turbine.Ng) + + # Generate the look-up tables, mesh the grid and flatten the arrays for aerodynamic analysis + TSR_initial = np.arange(0.5, 25., 0.5) + pitch_initial = np.arange(0.0, 31., 1.0) + pitch_initial_rad = np.deg2rad(pitch_initial) + + tsr_mesh, pitch_rad_mesh = np.meshgrid(TSR_initial, pitch_initial_rad) + + tsr_flat = tsr_mesh.ravel() + pitch_rad_flat = pitch_rad_mesh.ravel() + + # Get values from MITRotor + print('Running MITRotor aerodynamic analysis, this may take a minute...') + + mit_sols = bem( + pitch_rad_flat, + tsr_flat, + yaw=np.ones_like(tsr_flat) * turbine.yaw, + tilt=np.ones_like(tsr_flat) * np.deg2rad(5.0), + ) + + print('MITRotor aerodynamic analysis run successfully.') + + # Reshape directly into lookup tables + n_pitch = len(pitch_initial_rad) + n_tsr = len(TSR_initial) + + Cp_table = mit_sols.Cp().reshape(n_pitch, n_tsr).T + Ct_table = mit_sols.Ct().reshape(n_pitch, n_tsr).T + Cq_table = mit_sols.Cq().reshape(n_pitch, n_tsr).T + + # Store necessary metrics for analysis + turbine.pitch_initial_rad = pitch_initial_rad + turbine.TSR_initial = TSR_initial + + turbine.Cp_table = Cp_table + turbine.Ct_table = Ct_table + turbine.Cq_table = Cq_table + + turbine.Cp = ROSCO_turbine.RotorPerformance(turbine.Cp_table,turbine.pitch_initial_rad,turbine.TSR_initial, refine=refine_cp_surface) + turbine.Ct = ROSCO_turbine.RotorPerformance(turbine.Ct_table,turbine.pitch_initial_rad,turbine.TSR_initial, refine=refine_cp_surface) + turbine.Cq = ROSCO_turbine.RotorPerformance(turbine.Cq_table,turbine.pitch_initial_rad,turbine.TSR_initial, refine=refine_cp_surface) + return turbine + +# ----------------------------- +# Generate control scheme +# ----------------------------- +def get_rosco_control_interps( + rosco_yaml, bem, + TurbineName = "IEA15MW", rotor_performance_filename = 'Cp_Ct_Cq.txt', SimName = "Sim1", + GenEff = 95.756, generator_inertia = 1836784, + regenerate = False, + save_control_file = None, + save_dir = ".", + dt = 0.05, + yaw_grid_deg = np.arange(0.0, 25.0, 1.0), # in degrees +): + """ + Creates pitch and tsr 2D interpolators using ROSCO controller tuning. + + Creates turbine and controller. Controller is tuned on yaw = 0 Cp/Ct surfaces from MITRotor. + ROSCO simulation with controller and turbrine is then run for each (wind_speed, yaw) combination + till steady state. Steady-state set points are made into a 2D interpolator and optionally saved to + a CSV. + + Args: + rosco_yaml (string): yaml file (+path) that defineds turbine and control parameters; + [see MITRotor/ReferenceTurbines/ROSCO_IEA15MW.yaml for example] + bem (MITRotor.BEM): MITRotor BEM object + TurbineName (string): string turbine name; default to "IEA15MW" + GenEff (float): generator efficiency (0-100); defaults to IEA15MW value 95.756 + generator_inertia (float): generator_inertia; defaults to IEA15MW value 1836784 [kg m^2] + save_control_file (string): file name (+path) of saved look-up table value; if None (default) then not saved + regenerate (bool): if True, then regenerate control path, else use saved in save_control_file; if save_control_file is None, set to True + save_dir (string): path to save all files output when creating the interpolaters + dt (float): timestep for ROSCO simulation; default = 0.05 seconds + + Returns: + pitch_interp (string): 1D pitch interpolator from wind speed tuned with ROSCO control paramters + tsr_interp (string): 1D tsr interpolator from wind speed tuned with ROSCO control paramters + rated_rotor_speed (float): rated rotor speed value + """ + + # load ROSCO inputs and make basic turbine + inps = load_rosco_yaml(rosco_yaml) + turbine_params = inps['turbine_params'] + turbine = ROSCO_turbine.Turbine(turbine_params) + + # if control csv exists and do not want to regenerate, load old csv + if not regenerate and save_control_file is not None: + pitch_interp, tsr_interp = load_control_interps_from_csv(save_control_file) + return pitch_interp, tsr_interp, turbine.rated_rotor_speed + + # load and check control parameters + controller_params = inps['controller_params'] + if controller_params["WE_Mode"] != 0: + warnings.warn( + "Using wind speed estimators in this simple simulation is known to cause problems. We suggest using WE_Mode = 0.", + UserWarning, + ) + + # generate turbine Cp/Ct surfaces + turbine = load_from_mitrotor( + turbine, bem, + TurbineName = TurbineName, rotor_performance_filename = rotor_performance_filename, + generator_inertia = generator_inertia, GenEff = GenEff, + yaw = 0.0, + ) + # save turbine Cp/Ct surface + cp_filename = turbine.rotor_performance_filename + write_rotor_performance(turbine, txt_filename=cp_filename) + + # make and tune controller + controller = ROSCO_controller.Controller(controller_params) + controller.tune_controller(turbine) + + # Write parameter input file + param_filename = os.path.join(save_dir,'DISCON.IN') + write_DISCON( + turbine,controller, + param_file=param_filename, + txt_filename=cp_filename + ) + + # load initial setpoints from tuned controller + init_pitch_list = np.rad2deg(np.maximum(controller.pitch_op, controller.ps_min_bld_pitch)) + init_tsr_list = controller.TSR_op + + # load/set values for interpolator axes + v_grid = controller.v.copy() + yaw_grid_deg = np.asarray(yaw_grid_deg, dtype=float) + yaw_grid_rad = np.deg2rad(yaw_grid_deg) + + pitch_tbl = np.zeros((len(v_grid), len(yaw_grid_rad))) + tsr_tbl = np.zeros_like(pitch_tbl) + power_tbl = np.zeros_like(pitch_tbl) + + # needed constants + R = turbine.rotor_radius + GBRatio = turbine.Ng + + # loop through interpolator axes and find setpoints using ROSCO simulation + for (i, v) in enumerate(v_grid): + # initial guess setpoints based on tuned controller + init_pitch = init_pitch_list[i] + init_tsr = init_tsr_list[i] + init_omega = init_tsr * v / R + init_gen = init_omega * GBRatio + # loop through yaw + for (j, yaw_rad) in enumerate(yaw_grid_rad): + # create controller interface + controller_int = WarmStartControllerInterface( + lib_name, + param_filename=param_filename, + sim_name=f"{SimName}_{i}_{j}", + DT=dt, + init_ws=v, + init_rot_speed=init_omega, + init_gen_speed=init_gen, + init_pitch_deg=init_pitch, # init_pitch is in deg + init_torque=0.0, + init_nac_imu=yaw_rad, # init_nac_imu is rad + ) + + # create the ROSCO simulation + sim = ROSCO_sim.Sim(turbine, controller_int) + # run the simulation to steady state + sim_ws_mitrotor( + sim=sim, bem=bem, ws=v, dt=dt, + init_tsr=init_tsr, + init_pitch=init_pitch, # deg + yaw_init=yaw_rad, # rad + wd=0.0, + ) + # save setpoints in 2D tables + pitch_tbl[i, j] = sim.bld_pitch + tsr_tbl[i, j] = sim.tsr + power_tbl[i, j] = sim.gen_power + + # save CSV of (optional) + if save_control_file is not None: + save_control_file = Path(save_control_file) + save_control_file.parent.mkdir(parents=True, exist_ok=True) + + vv, yy = np.meshgrid(v_grid, yaw_grid_rad, indexing="ij") + data = np.column_stack([ + vv.ravel(), # wind_speed_mps + yy.ravel(), # yaw_rad + pitch_tbl.ravel(), # pitch_rad + tsr_tbl.ravel(), # tsr + power_tbl.ravel(), # generated power + ]) + + header = "wind_speed_mps,yaw_rad,pitch_rad,tsr,gen_power" + np.savetxt(save_control_file, data, delimiter=",", header=header, comments="") + + # Direct 2D interpolators, no custom wrapper + pitch_interp = RegularGridInterpolator( + (v_grid, yaw_grid_rad), pitch_tbl, + method="linear", bounds_error=False, fill_value=None + ) + tsr_interp = RegularGridInterpolator( + (v_grid, yaw_grid_rad), tsr_tbl, + method="linear", bounds_error=False, fill_value=None + ) + + return pitch_interp, tsr_interp, turbine.rated_rotor_speed + + +def load_control_interps_from_csv(csv_path): + """ + Load wind/yaw control LUT CSV and return 2D interpolators. + + Expected CSV columns: + wind_speed_mps, yaw_rad, pitch_rad, tsr, gen_power + """ + data = np.genfromtxt(csv_path, delimiter=",", names=True) + + ws = np.asarray(data["wind_speed_mps"], dtype=float) + yaw = np.asarray(data["yaw_rad"], dtype=float) + pitch = np.asarray(data["pitch_rad"], dtype=float) + tsr = np.asarray(data["tsr"], dtype=float) + + v_grid = np.unique(ws) + yaw_grid = np.unique(yaw) + + # sort rows by (ws, yaw), then reshape into [n_ws, n_yaw] + order = np.lexsort((yaw, ws)) + n_ws, n_yaw = len(v_grid), len(yaw_grid) + + pitch_tbl = pitch[order].reshape(n_ws, n_yaw) + tsr_tbl = tsr[order].reshape(n_ws, n_yaw) + + pitch_interp = RegularGridInterpolator( + (v_grid, yaw_grid), pitch_tbl, + method="linear", bounds_error=False, fill_value=None + ) + tsr_interp = RegularGridInterpolator( + (v_grid, yaw_grid), tsr_tbl, + method="linear", bounds_error=False, fill_value=None + ) + + return pitch_interp, tsr_interp + +# def query_control(pitch_interp, tsr_interp, ws, yaw_rad): +# pitch = query_pitch(pitch_interp, ws, yaw_rad) +# tsr = query_tsr(tsr_interp, ws, yaw_rad) +# return pitch, tsr + +def query_controls(interp, ws, yaw_rad): + """ + Vectorized query for 2D interpolator interp(ws, yaw). + + Supports: + - scalar ws, scalar yaw -> float + - array ws, scalar yaw -> array + - scalar ws, array yaw -> array + - array ws, array yaw (broadcastable shapes, including same-length 1D pairwise) -> array + """ + ws_arr = np.asarray(ws, dtype=float) + yaw_arr = np.asarray(yaw_rad, dtype=float) + + # Broadcast to common shape (or raise if incompatible) + ws_b, yaw_b = np.broadcast_arrays(ws_arr, yaw_arr) + + # Build points for RegularGridInterpolator: shape (N, 2) + pts = np.column_stack((ws_b.ravel(), yaw_b.ravel())) + + # Vectorized interpolation + vals = np.asarray(interp(pts)).reshape(ws_b.shape) + + # Return float for scalar input, ndarray otherwise + return float(vals) if vals.shape == () else vals + + +# ----------------------------- +# Steady-state simulation +# ----------------------------- +def sim_ws_mitrotor( + sim, bem, ws, dt, init_tsr, init_pitch, + wd=0.0, yaw_init=0.0, + max_iter=20000, + conv_settings=None, + verbose=True, +): + """ + Steady-state single-wind-speed simulation (no time history storage), + with rolling-window convergence checks. + """ + if conv_settings is None: + conv_settings = ConvergenceSettings() + + # Turbine constants + R = sim.turbine.rotor_radius + rho = sim.turbine.rho + Ng = sim.turbine.Ng + J = sim.turbine.J + gbox_eff = sim.turbine.GBoxEff / 100.0 + gen_eff = sim.turbine.GenEff / 100.0 + + # States + bld_pitch = np.deg2rad(init_pitch) # rad (init_pitch is deg) + rot_speed = (init_tsr * ws / R) # rad/s + gen_speed = rot_speed * Ng # rad/s + gen_torque = 0.0 # Nm + gen_power = 0.0 # W + nac_yaw = yaw_init # rad + nac_yawrate = 0.0 # rad/s + + # Convergence tracker + tracker = init_convergence_tracker(dt, conv_settings) + + n_iter = 0 + t = 0.0 + converged = False + last_metrics = None + # begin iteration + while n_iter < max_iter: + t += dt + + # aero side + tsr = rot_speed * R / max(ws, 1e-6) + + # yaw misalignment for aero + yaw_err = wd - nac_yaw + + # BEM call + sol = bem( + bld_pitch, tsr, + yaw = yaw_err, + tilt = 0.0 + ) + cp = float(np.ravel(sol.Cp())[0]) + + # 1DOF rotor dynamics (same structure as ROSCO Sim) + aero_torque = 0.5 * rho * (np.pi * R**3) * (cp / max(tsr, 1e-6)) * ws**2 + rot_speed = rot_speed + (dt / J) * (aero_torque - Ng * gen_torque / gbox_eff) + gen_speed = rot_speed * Ng + + # Controller input state + turbine_state = { + "iStatus": 1, + "t": t, + "dt": dt, + "ws": ws, + "bld_pitch": bld_pitch, + "gen_torque": gen_torque, + "gen_speed": gen_speed, + "gen_eff": gen_eff, + "rot_speed": rot_speed, + "Yaw_fromNorth": nac_yaw, + "Y_MeasErr": yaw_err, + } + + # Controller outputs + gen_torque, bld_pitch, nac_yawrate = sim.controller_int.call_controller(turbine_state) + + # Power + gen_power = gen_speed * gen_torque * gen_eff # W + + # Yaw dynamics + nac_yaw += nac_yawrate * dt + + # Convergence tracking + update_convergence_tracker(tracker, gen_power, rot_speed, bld_pitch) + converged, metrics = check_convergence(n_iter, dt, tracker, conv_settings) + if metrics is not None: + last_metrics = metrics + + # Check if converged + if converged: + if verbose and last_metrics is not None: + print( + f"Converged after {n_iter} steps " + f"(t={n_iter*dt:.1f}s): " + f"P={last_metrics['p_mean']/1000:.1f} kW, " + f"std(P)/mean(P)={last_metrics['rel_p_std']:.2e}, " + f"max|dω/dt|={last_metrics['max_domega_dt']:.2e} rad/s², " + f"max|dθ/dt|={np.rad2deg(last_metrics['max_dpitch_dt']):.2e} deg/s" + ) + break + + n_iter += 1 + + if not converged and verbose: + print(f"WARNING: hit max_iter={max_iter} without convergence") + # Kill controller + sim.controller_int.kill_discon() + + # Save outputs + sim.bld_pitch = bld_pitch # rad + sim.tsr = rot_speed * R / max(ws, 1e-6) + sim.rot_speed = rot_speed # rad/s + sim.gen_speed = gen_speed # rad/s + sim.gen_torque = gen_torque # Nm + sim.gen_power = gen_power # W + sim.nac_yaw = nac_yaw # rad + sim.n_iter = n_iter + sim.converged = converged + + return converged + + +class WarmStartControllerInterface(ROSCO_ci.ControllerInterface): + """ + ROSCO controller interface with configurable warm-start initial conditions. + + This subclass overrides the default `ControllerInterface` initialization so + the first DISCON call (`iStatus=0`) is seeded with user-provided initial + wind speed, rotor/generator speeds, pitch, torque, and nacelle IMU angle, + instead of hard-coded defaults. + + Notes + ----- + - This is useful for steady-state sweeps, where reducing startup transients + improves convergence speed and robustness. + - Units are expected to match ROSCO avrSWAP channel conventions. + """ + + def __init__( + self, + lib_name, + param_filename="DISCON.IN", + init_ws=10.0, # m/s + init_rot_speed=1.0, # rad/s + init_gen_speed=1.0, # rad/s + init_pitch_deg=0.0, # deg + init_torque=0.0, # Nm + init_nac_imu=0.0, # rad + **kwargs + ): + """ + Initialize warm-start settings and construct the ROSCO controller interface. + + Parameters + ---------- + lib_name : str + Path to the ROSCO dynamic library (.dll/.so/.dylib). + param_filename : str, optional + Path to DISCON input file, by default "DISCON.IN". + init_ws : float, optional + Initial wind speed used during DISCON init, in m/s. + init_rot_speed : float, optional + Initial low-speed shaft rotor speed, in rad/s. + init_gen_speed : float, optional + Initial generator speed (high-speed shaft), in rad/s. + init_pitch_deg : float, optional + Initial collective blade pitch, in degrees. + init_torque : float, optional + Initial generator torque, in Nm. + init_nac_imu : float, optional + Initial nacelle IMU angle/state, in radians. + **kwargs + Additional keyword arguments forwarded to + `ROSCO_ci.ControllerInterface` (e.g., `DT`, `sim_name`, etc.). + """ + self.init_ws = float(init_ws) + self.init_rot_speed = float(init_rot_speed) + self.init_gen_speed = float(init_gen_speed) + self.init_torque = float(init_torque) + self.init_nac_imu = float(init_nac_imu) + + # parent uses self.pitch for initial blade pitch + super().__init__( + lib_name, + param_filename=param_filename, + pitch=init_pitch_deg, + **kwargs + ) + + def init_discon(self): + """ + Initialize DISCON with warm-start avrSWAP values. + + This method allocates and populates the avrSWAP array, sets the first-call + status (`iStatus=0`), invokes DISCON once to initialize internal ROSCO states, + then switches to normal run mode (`iStatus=1`) for subsequent calls. + + Raises + ------ + ValueError + If ROSCO returns a negative `aviFAIL` error code during initialization. + """ + self.torque = self.init_torque + + # Load library + allocate swap + self.discon = cdll.LoadLibrary(self.lib_name) + self.avrSWAP = np.zeros(self.avr_size) + + # Required channels + self.avrSWAP[2] = self.DT + self.avrSWAP[60] = self.num_blade + + # --- warm-start initial states (replaces hard-coded values) --- + self.avrSWAP[19] = self.init_gen_speed # gen speed [rad/s] + self.avrSWAP[20] = self.init_rot_speed # rot speed [rad/s] + self.avrSWAP[82] = self.init_nac_imu # nac IMU + self.avrSWAP[26] = self.init_ws # wind speed [m/s] + self.avrSWAP[22] = self.init_torque # gen torque [Nm] + + # Initial blade pitch (all blades) + pitch_rad = np.deg2rad(self.pitch) + self.avrSWAP[3] = pitch_rad + self.avrSWAP[32] = pitch_rad + self.avrSWAP[33] = pitch_rad + + self.avrSWAP[27] = 1 # IPC flag + + # First-call init + self.avrSWAP[0] = 0 + + self.aviFAIL = c_int32() + self.accINFILE = self.param_name.encode("utf-8") + self.avcOUTNAME = self.sim_name.encode("utf-8") + self.avcMSG = create_string_buffer(1000) + + self.discon.DISCON.argtypes = [ + POINTER(c_float), + POINTER(c_int32), + c_char_p, + c_char_p, + c_char_p, + ] + + self.avrSWAP[48] = self.char_buffer + self.avrSWAP[49] = len(self.param_name) + self.avrSWAP[50] = len(self.avcOUTNAME) + self.avrSWAP[51] = self.char_buffer + + self.call_discon() # iStatus=0 init call + self.avrSWAP[0] = 1 # subsequent calls are normal + + if self.aviFAIL.value < 0: + raise ValueError("ROSCO dynamic library has returned an error") + + +# ----------------------------- +# Convergence helper structures +# ----------------------------- +@dataclass +class ConvergenceSettings: + """ + Tunable parameters for steady-state convergence detection. + + Attributes + ---------- + warmup_time : float + Time to ignore before evaluating convergence, in seconds. + window_time : float + Length of rolling analysis window, in seconds. + hold_time : float + Duration for which all criteria must remain satisfied, in seconds. + tol_rel_power_std : float + Threshold on relative power variability: std(P)/|mean(P)|. + tol_domega_dt : float + Threshold on max rotor acceleration magnitude, in rad/s^2. + tol_dpitch_dt : float + Threshold on max pitch-rate magnitude, in rad/s. + """ + warmup_time: float = 60.0 + window_time: float = 20.0 + hold_time: float = 5.0 + tol_rel_power_std: float = 1e-3 + tol_domega_dt: float = 1e-4 + tol_dpitch_dt: float = np.deg2rad(1e-3) + + +def init_convergence_tracker(dt: float, settings: ConvergenceSettings): + """ + Create and initialize rolling-window state for convergence checks. + + Parameters + ---------- + dt : float + Simulation timestep in seconds. + settings : ConvergenceSettings + Convergence timing and tolerance settings. + + Returns + ------- + dict + Tracker containing step counts, rolling histories, and stable counter. + Keys include: `warmup_steps`, `window_steps`, `hold_steps`, + `stable_count`, `p_hist`, `omega_hist`, `pitch_hist`. + """ + warmup_steps = int(np.ceil(settings.warmup_time / dt)) + window_steps = int(np.ceil(settings.window_time / dt)) + hold_steps = int(np.ceil(settings.hold_time / dt)) + + tracker = { + "warmup_steps": warmup_steps, + "window_steps": window_steps, + "hold_steps": hold_steps, + "stable_count": 0, + "p_hist": deque(maxlen=window_steps), # W + "omega_hist": deque(maxlen=window_steps), # rad/s + "pitch_hist": deque(maxlen=window_steps), # rad + } + return tracker + + +def update_convergence_tracker(tracker, gen_power, rot_speed, bld_pitch): + """ + Append latest simulation values to rolling convergence histories. + + Parameters + ---------- + tracker : dict + Tracker dictionary created by `init_convergence_tracker`. + gen_power : float + Generator electrical power, in W. + rot_speed : float + Rotor speed, in rad/s. + bld_pitch : float + Collective blade pitch, in rad. + """ + tracker["p_hist"].append(float(gen_power)) + tracker["omega_hist"].append(float(rot_speed)) + tracker["pitch_hist"].append(float(bld_pitch)) + + +def compute_window_metrics(tracker, dt): + """ + Compute window-based convergence metrics from rolling histories. + + Parameters + ---------- + tracker : dict + Convergence tracker containing `p_hist`, `omega_hist`, `pitch_hist`. + dt : float + Simulation timestep in seconds. + + Returns + ------- + dict + Dictionary with: + - `p_mean` : mean power over window [W] + - `rel_p_std` : relative power std, std(P)/max(|mean(P)|, 1) + - `max_domega_dt` : max |d(omega)/dt| over window [rad/s^2] + - `max_dpitch_dt` : max |d(pitch)/dt| over window [rad/s] + """ + p = np.asarray(tracker["p_hist"]) + om = np.asarray(tracker["omega_hist"]) + th = np.asarray(tracker["pitch_hist"]) + + p_mean = float(np.mean(p)) + rel_p_std = float(np.std(p) / max(abs(p_mean), 1.0)) + max_domega_dt = float(np.max(np.abs(np.diff(om))) / dt) + max_dpitch_dt = float(np.max(np.abs(np.diff(th))) / dt) + + return { + "p_mean": p_mean, + "rel_p_std": rel_p_std, + "max_domega_dt": max_domega_dt, + "max_dpitch_dt": max_dpitch_dt, + } + + +def check_convergence(n_iter, dt, tracker, settings: ConvergenceSettings): + """ + Evaluate steady-state convergence criteria. + + Criteria + -------- + After warmup and once the rolling window is full, convergence is considered + satisfied at a given step if: + 1) relative power std < `tol_rel_power_std` + 2) max rotor acceleration < `tol_domega_dt` + 3) max pitch rate < `tol_dpitch_dt` + + These conditions must hold for `hold_steps` consecutive evaluations. + + Parameters + ---------- + n_iter : int + Current simulation iteration index. + dt : float + Simulation timestep in seconds. + tracker : dict + Convergence tracker dictionary. + settings : ConvergenceSettings + Convergence timing and tolerance settings. + + Returns + ------- + tuple[bool, dict | None] + `(converged, metrics)` where: + - `converged` is True if hold condition is met. + - `metrics` is None until checks become active; otherwise window metrics + from `compute_window_metrics`. + """ + # not ready yet + if n_iter < tracker["warmup_steps"]: + return False, None + if len(tracker["p_hist"]) < tracker["window_steps"]: + return False, None + + metrics = compute_window_metrics(tracker, dt) + + ok_power = metrics["rel_p_std"] < settings.tol_rel_power_std + ok_omega = metrics["max_domega_dt"] < settings.tol_domega_dt + ok_pitch = metrics["max_dpitch_dt"] < settings.tol_dpitch_dt + + if ok_power and ok_omega and ok_pitch: + tracker["stable_count"] += 1 + else: + tracker["stable_count"] = 0 + + converged = tracker["stable_count"] >= tracker["hold_steps"] + return converged, metrics \ No newline at end of file diff --git a/MITRotor/FlorisInterface/ROSCOUtilities.py b/MITRotor/FlorisInterface/ROSCOUtilities.py new file mode 100644 index 0000000..e69de29 diff --git a/MITRotor/Geometry.py b/MITRotor/Geometry.py index 8a00144..7f0ae3f 100644 --- a/MITRotor/Geometry.py +++ b/MITRotor/Geometry.py @@ -40,14 +40,53 @@ def cartesian(self, yaw: float, tilt: float) -> Tuple[ArrayLike, ...]: Z = self.mu_mesh * np.cos(self.theta_mesh) # vertical return X, Y, Z + +# ---------- Function for averaging over the rotor ---------- # - def annulus_average(self, X: ArrayLike): - X_azim = 1 / (2 * np.pi) * np.trapezoid(X, self.theta_mesh, axis=-1) + def annulus_average(self, X): + X = np.asarray(X) + theta = np.asarray(self.theta).reshape(-1) + #Ensure last axis is Nθ + if X.shape[-1] != theta.shape[0]: + raise ValueError(f"Mismatch: X.shape={X.shape}, theta.shape={theta.shape}") + # Integrate over Nθ (last axis) + return (1 / (2 * np.pi)) * np.trapezoid(X, theta, axis=-1) - return X_azim + def rotor_average(self, X): + X = np.asarray(X) + mu = np.asarray(self.mu).reshape(-1) # (Nr,) + # Ensure last axis is Nr + if X.shape[-1] != mu.shape[0]: + raise ValueError(f"Mismatch: X.shape={X.shape}, mu.shape={mu.shape}") + # Integrate over Nr (last axis) + return 2 * np.trapezoid(X * mu, mu, axis=-1) + +# ---------- Function for adjusting axes for vectorization ---------- # - def rotor_average(self, X: ArrayLike): - # Takes annulus average quantities and performs rotor average +def expand_to_Np(x): # add setpoint axis + x = np.atleast_1d(x) + if x.ndim < 3: + return x[None, ...] + else: + return x - X_rotor = 2 * np.trapezoid(X * self.mu, self.mu) - return X_rotor +def expand_to_Nr_Ntheta(x): # add Nr and Nθ axis + x = np.atleast_1d(x) + if x.ndim < 3: + return x[:, None, None] + else: + return x + +def expand_to_Nr(x): # add Nr axis + x = np.atleast_1d(x) + if x.ndim < 2: + return x[:, None] + else: + return x + +def expand_to_Ntheta(x): # add Nθ axis + x = np.atleast_1d(x) + if x.ndim < 3: + return x[:, :, None] + else: + return x diff --git a/MITRotor/Momentum.py b/MITRotor/Momentum.py index 6fc4646..6834ff0 100644 --- a/MITRotor/Momentum.py +++ b/MITRotor/Momentum.py @@ -8,6 +8,7 @@ from pathlib import Path from UnifiedMomentumModel import Momentum as UMM from UnifiedMomentumModel.Utilities.Geometry import calc_eff_yaw, eff_yaw_inv_rotation +from .Geometry import expand_to_Nr_Ntheta, expand_to_Nr, expand_to_Ntheta if TYPE_CHECKING: from .Geometry import BEMGeometry @@ -62,13 +63,11 @@ def _func_rotor( geom.rotor_average( geom.annulus_average( np.clip(aero_props.C_x_corr, 0, 1.69) - ) - ) + ) + ) ) - - return self.compute_induction(rotor_avg_axial_force, yaw = yaw, tilt = tilt) - - + an = self.compute_induction(rotor_avg_axial_force, yaw = yaw, tilt = tilt) + return expand_to_Nr_Ntheta(an) def _func_annulus( self, @@ -81,15 +80,12 @@ def _func_annulus( tilt: float = 0.0, ) -> ArrayLike: - annulus_avg_axial_force = ( - - geom.annulus_average( - np.clip(aero_props.C_x_corr, -10, 10) - ) - )[:, None] * np.ones(geom.shape) - - - return self.compute_induction(annulus_avg_axial_force, yaw = yaw, tilt = tilt) + annulus_avg_axial_force = geom.annulus_average( + np.clip(aero_props.C_x_corr, 0, 1.69) + ) + yaw, tilt = expand_to_Nr(yaw), expand_to_Nr(tilt) + an = self.compute_induction(annulus_avg_axial_force, yaw = yaw, tilt = tilt) + return expand_to_Ntheta(an) def _func_sector( self, @@ -102,7 +98,7 @@ def _func_sector( tilt: float = 0.0, ) -> ArrayLike: axial_force = np.clip(aero_props.C_x_corr, -10, 10) - + yaw, tilt = expand_to_Nr_Ntheta(yaw), expand_to_Nr_Ntheta(tilt) return self.compute_induction(axial_force, yaw = yaw, tilt = tilt) def __call__( @@ -188,8 +184,8 @@ def __init__(self, def compute_induction(self, Cx: ArrayLike, yaw: float, tilt: float = 0.0) -> ArrayLike: - if tilt != 0: - raise ValueError("Tilt not supported by the Madsen momentum model. Use UMM.") + # if tilt != 0: + # raise ValueError("Tilt not supported by the Madsen momentum model. Use UMM.") if self.cosine_exponent: Ct = Cx / (np.cos(yaw)**2) else: diff --git a/MITRotor/ReferenceTurbines/ROSCO_IEA15MW.yaml b/MITRotor/ReferenceTurbines/ROSCO_IEA15MW.yaml new file mode 100644 index 0000000..85a5d3a --- /dev/null +++ b/MITRotor/ReferenceTurbines/ROSCO_IEA15MW.yaml @@ -0,0 +1,62 @@ +# --------------------- ROSCO controller tuning input file ------------------- + # Written for use with ROSCO_Toolbox tuning procedures + # Turbine: IEA 15MW Reference Wind Turbine + # NOTE: The comments describing inputs in this file are not maintained. + # The most up-to-date descriptions can be found in the ROSCO documentation: https://rosco.readthedocs.io/en/latest/source/toolbox_input.html +# ------------------------------ OpenFAST PATH DEFINITIONS ------------------------------ +path_params: + FAST_InputFile: 'IEA-15-240-RWT-UMaineSemi.fst' # Name of *.fst file + FAST_directory: '../Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi' # Main OpenFAST model directory, where the *.fst lives + # Optional (but suggested...) + rotor_performance_filename: '../Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/Cp_Ct_Cq.IEA15MW.txt' + +# -------------------------------- TURBINE PARAMETERS ----------------------------------- +turbine_params: + rotor_inertia: 310619488. # Rotor inertia [kg m^2], {Available in Elastodyn .sum file} + rated_rotor_speed: 0.7916813478 # Rated rotor speed [rad/s] + v_min: 3. # Cut-in wind speed [m/s] + v_rated: 10.74 # Rated wind speed [m/s] + v_max: 25.0 # Cut-out wind speed [m/s], -- Does not need to be exact (JUST ASSUME FOR NOW) + max_pitch_rate: 0.0349 # Maximum blade pitch rate [rad/s] + max_torque_rate: 4500000. # Maximum torque rate [Nm/s], {~1/4 VS_RtTq/s} + rated_power: 15000000. # Rated Power [W] + bld_edgewise_freq: 4.0324 # Blade edgewise first natural frequency [rad/s] + bld_flapwise_freq: 3.4872 # Blade flapwise first natural frequency [rad/s] + TSR_operational: 9.0 + +#------------------------------- CONTROLLER PARAMETERS ---------------------------------- +controller_params: + # Controller flags + LoggingLevel: 2 # {0: write no debug files, 1: write standard output .dbg-file, 2: write standard output .dbg-file and complete avrSWAP-array .dbg2-file + F_LPFType: 2 # {1: first-order low-pass filter, 2: second-order low-pass filter}, [rad/s] (currently filters generator speed and pitch control signals) + F_NotchType: 0 # Notch on the measured generator speed {0: disable, 1: enable} + IPC_ControlMode: 0 # Turn Individual Pitch Control (IPC) for fatigue load reductions (pitch contribution) {0: off, 1: 1P reductions, 2: 1P+2P reductions} + VS_ControlMode: 2 # Generator torque control mode in above rated conditions {0: constant torque, 1: constant power, 2: TSR tracking PI control} + PC_ControlMode: 1 # Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} + Y_ControlMode: 0 # Yaw control mode {0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC} + SS_Mode: 1 # Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} + WE_Mode: 0 # Wind speed estimator mode {0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator (Ortega et al.)} + PS_Mode: 3 # Pitch saturation mode {0: no pitch saturation, 1: peak shaving, 2: Cp-maximizing pitch saturation, 3: peak shaving and Cp-maximizing pitch saturation} + SD_Mode: 0 # Shutdown mode {0: no shutdown procedure, 1: pitch to max pitch at shutdown} + Fl_Mode: 2 # Floating specific feedback mode {0: no nacelle velocity feedback, 1: nacelle velocity feedback} + Flp_Mode: 0 # Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control} + PA_Mode: 2 # Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} + # Controller parameters + # U_pc: [14] + zeta_pc: 1.0 # Pitch controller desired damping ratio [-] + omega_pc: 0.2 # Pitch controller desired natural frequency [rad/s] + zeta_vs: 0.85 # Torque controller desired damping ratio [-] + omega_vs: 0.12 # Torque controller desired natural frequency [rad/s] + twr_freq: 3.355 # for semi only! + ptfm_freq: 0.213 # for semi only! + # Optional - these can be defined, but do not need to be + min_pitch: 0.0 # Minimum pitch angle [rad], {default = 0 degrees} + vs_minspd: 0.523598775 # Minimum rotor speed [rad/s], {default = 0 rad/s} + ps_percent: 0.8 # Percent peak shaving [%, <= 1 ], {default = 80%} + PA_CornerFreq: 1.5708 # Pitch actuator natural frequency [rad/s] + PA_Damping: 0.707 # Pitch actuator natural frequency [rad/s] + rgn2k_factor: 0.85926 + + DISCON: + IPC_KI: [1.2e-11, 0] + diff --git a/MITRotor/RotorDefinition.py b/MITRotor/RotorDefinition.py index 4e8d487..e036705 100644 --- a/MITRotor/RotorDefinition.py +++ b/MITRotor/RotorDefinition.py @@ -105,6 +105,13 @@ def from_windio(cls, windio: dict): airfoil_func = BladeAirfoils.from_windio(windio, hub_radius, R) + # Needed for ROSCO Control + tower_height = np.max(windio["components"]["tower"]["outer_shape_bem"]["reference_axis"]["z"]["values"]) + gearbox_efficiency = windio["components"]["nacelle"]["drivetrain"]["gearbox_efficiency"] * 100 + gearbox_ratio = windio["components"]["nacelle"]["drivetrain"]["gear_ratio"] + air_density = windio["environment"]["air_density"] + rosco_values = (tower_height, gearbox_efficiency, gearbox_ratio, air_density) + return cls( twist_func, solidity_func, @@ -117,6 +124,7 @@ def from_windio(cls, windio: dict): tsr_target, hub_radius, name=name, + rosco_values = rosco_values ) def __init__( @@ -132,6 +140,7 @@ def __init__( tsr_target, hub_radius, name=None, + rosco_values = None, ): self.name = name self.N_blades = N_blades @@ -147,6 +156,8 @@ def __init__( self.solidity_func = solidity_func self.airfoil_func = airfoil_func + self.rosco_values = rosco_values + def twist(self, mu): return self.twist_func(mu) diff --git a/MITRotor/TangentialInduction.py b/MITRotor/TangentialInduction.py index cd493ec..d2dff09 100644 --- a/MITRotor/TangentialInduction.py +++ b/MITRotor/TangentialInduction.py @@ -3,7 +3,7 @@ from numpy.typing import ArrayLike from .Aerodynamics import AerodynamicProperties -from .Geometry import BEMGeometry +from .Geometry import BEMGeometry, expand_to_Nr_Ntheta from .RotorDefinition import RotorDefinition from UnifiedMomentumModel.Utilities.Geometry import calc_eff_yaw @@ -54,7 +54,8 @@ def __call__( geom: BEMGeometry, tilt: float = 0.0, ) -> ArrayLike: - eff_yaw = calc_eff_yaw(yaw, tilt) + eff_yaw = expand_to_Nr_Ntheta(calc_eff_yaw(yaw, tilt)) + tsr = expand_to_Nr_Ntheta(tsr) aprime = ( np.clip(aero_props.C_tau_corr, -2, 2) / (4 * np.maximum(geom.mu_mesh, 0.1) ** 2 * tsr * (1 - aero_props.an) * np.cos(eff_yaw)) diff --git a/examples/example_02_rotor_distributions.py b/examples/example_02_rotor_distributions.py index 517ea21..98e976f 100644 --- a/examples/example_02_rotor_distributions.py +++ b/examples/example_02_rotor_distributions.py @@ -17,7 +17,7 @@ def plot_radial_distributions(sol: BEMSolution, save_to: Path): [ax.legend(loc="lower center") for ax in axes] - axes[-1].set_xlabel("Radial position, $\mu$ [-]") + axes[-1].set_xlabel("Radial position, $\\mu$ [-]") plt.xlim(0, 1) plt.savefig(save_to, dpi=300, bbox_inches="tight") diff --git a/examples/example_04_yaw_tilt_rotor_comparison.py b/examples/example_04_yaw_tilt_rotor_comparison.py index 5b39520..9a809bf 100644 --- a/examples/example_04_yaw_tilt_rotor_comparison.py +++ b/examples/example_04_yaw_tilt_rotor_comparison.py @@ -41,7 +41,7 @@ axes[i, j].set_title(f"r/R ={np.round(r_mesh[0], decimals=2)}") fig.legend( - [f"Yaw ${rounded_deg_misalignment}^\circ$", f"Tilt ${rounded_deg_misalignment}^\circ$", f"Yaw ${np.rad2deg(yaw)}^\circ$ and Tilt ${np.rad2deg(yaw)}^\circ$"], # labels + [f"Yaw ${rounded_deg_misalignment}^\\circ$", f"Tilt ${rounded_deg_misalignment}^\\circ$", f"Yaw ${np.rad2deg(yaw)}^\\circ$ and Tilt ${np.rad2deg(yaw)}^\\circ$"], # labels loc='lower center', ncol=3, bbox_to_anchor=(0.5, 0.05) diff --git a/examples/example_06_floris_integration.py b/examples/example_06_floris_integration.py new file mode 100644 index 0000000..78d6e7b --- /dev/null +++ b/examples/example_06_floris_integration.py @@ -0,0 +1,376 @@ +import os +import numpy as np +import polars as pl +from pathlib import Path +import time +import warnings + +warnings.filterwarnings("ignore", category=RuntimeWarning) # JUST FOR NOW + + +import matplotlib.pyplot as plt +from matplotlib import cm +from matplotlib.colors import Normalize +from matplotlib.cm import ScalarMappable + +# Floris imports +from floris import FlorisModel, TimeSeries + +# MITRotor / UMM Imports +from MITRotor.FlorisInterface.FlorisInterface import MITRotorTurbine, default_bem_factory, default_pitch_interp, default_tsr_interp +from MITRotor.ReferenceTurbines import IEA15MW +from MITRotor.Momentum import UnifiedMomentum, UnifiedMomentumLUT +from MITRotor.Geometry import BEMGeometry +from MITRotor.TipLoss import NoTipLoss +from MITRotor.BEMSolver import BEM + +figdir = Path("fig") +floris_air_density = 1.225 +# ------------------ run basic case -------------------------------------------------------- +fmodel = FlorisModel("defaults") +time_series = TimeSeries( + wind_directions=np.array([270.0, 270.0, 280.0]), + wind_speeds=np.array([8.0, 10.0, 12.0]), + turbulence_intensities=np.array([0.06, 0.06, 0.06]), +) +yaw_angles = np.array([ + [0.0, 0.0], # condition 1 + [0.0, 0.0], # condition 2 + [0.0, 0.0], # condition 3 +]) + +fmodel.set( + layout_x = [0.0, 500.0], + layout_y = [0.0, 0.0], + wind_data = time_series, + yaw_angles = yaw_angles +) +fmodel.set_operation_model(MITRotorTurbine()) +fmodel.run() +print("Powers [W]:\n", fmodel.get_turbine_powers(), "\n") +print("Thrust coefficients [-]:\n", fmodel.get_turbine_thrust_coefficients(), "\n") +print("Axial induction factors [-]:\n", fmodel.get_turbine_axial_induction_factors(), "\n") + +# -------------------- plot pitch and tsr control curves, as well as CT for IEA15MW ------------------ +# Credit to Ilan Upfal for initial validation of MITRotor vs IEA15MW and much of the script below. +# Floris Interface written and tested by Skylar Gering. +module_dir = os.path.dirname(__file__) # examples/ +csv_file = os.path.join(module_dir, "..", "MITRotor", "FlorisInterface", "IEA_15mw_rotor.csv") +df = pl.read_csv(csv_file) + +wind_table = df["Wind [m/s]"].to_numpy() +wind_speeds = np.linspace(5, 25, 20) +wind_dirs = np.full_like(wind_speeds, 270.0) +turbulence_intensity = np.zeros_like(wind_speeds) + +# ------- plot pitch and tsr control curves for IEA15MW from figure 2 (https://docs.nrel.gov/docs/fy22osti/82134.pdf) -------- +pitch_interp = default_pitch_interp() +tsr_interp = default_tsr_interp() +tsrs = [tsr_interp(u) for u in wind_speeds] +pitches = [pitch_interp(u) for u in wind_speeds] + +# plot interpolated pitch and tsr data +fig, ax = plt.subplots(figsize=(8, 6)) +ax.scatter( + wind_speeds, + np.rad2deg(pitches), + s=40, + edgecolors="k", + label = "Interpolated Pitch [deg]" +) +ax.scatter( + wind_speeds, + tsrs, + s=40, + edgecolors="k", + label = "Interpolated Tip-Speed Ratio [-]" +) +# load and plot raw CSV data +ax.plot( + wind_table, + df["Pitch [deg]"].to_numpy(), + label = "Pitch [deg]" +) +ax.plot( + wind_table, + df["Tip Speed [m/s]"].to_numpy() / wind_table, + label = "Tip-Speed Ratio [-]" +) +ax.set_title("IEA 15MW: Fixed Bottom Trajectories", size = 18) +ax.set_xlabel("Wind Speed [m/s]", size = 16) +ax.tick_params(labelsize=14) +ax.legend(fontsize = 14) +plt.savefig(figdir / "example_6_pitch_tsr_interpolation.png", dpi=300) + +# -------- plot CT and CP values against one another and against IEA15MW from figure 3.1-C (https://docs.nrel.gov/docs/fy20osti/75698.pdf) ------- +# solve UMM-BEM though MITRotor - rotor averaged +bem_rotor_umm = default_bem_factory() +mit_rotor_umm_start = time.time() +pitches_rad = pitch_interp(wind_speeds) +tsrs = tsr_interp(wind_speeds) +yaws, tilts = np.zeros_like(pitches_rad), np.zeros_like(pitches_rad) +mit_sols_rotor_umm = bem_rotor_umm(pitch=pitches_rad, tsr=tsrs, yaw=yaws, tilt=tilts) +mit_rotor_umm_end = time.time() +mit_Ct_rotor_umm = mit_sols_rotor_umm.Ct() +mit_Cp_rotor_umm = mit_sols_rotor_umm.Cp() +print("MITRotor UMM-BEM Rotor-Averaged: " + str(mit_rotor_umm_end - mit_rotor_umm_start) + " seconds") + +# solve UMM-BEM though MITRotor - annulus averaged +bem_annulus_umm = BEM( + rotor=IEA15MW(), + momentum_model=UnifiedMomentum(averaging="annulus"), + geometry=BEMGeometry(Nr=10, Ntheta=20), + tiploss_model=NoTipLoss(), + ) +mit_annulus_umm_start = time.time() +mit_sols_annulus_umm = bem_annulus_umm(pitch=pitches, tsr=tsrs, yaw=yaws, tilt=tilts) +mit_annulus_umm_end = time.time() +mit_Ct_annulus_umm = mit_sols_annulus_umm.Ct() +mit_Cp_annulus_umm = mit_sols_annulus_umm.Cp() +print("MITRotor UMM-BEM Annulus-Averaged: " + str(mit_annulus_umm_end - mit_annulus_umm_start) + " seconds") + +# solve UMM-BEM though MITRotor - sector averaged +# bem_sector_umm = BEM( +# rotor=IEA15MW(), +# momentum_model=UnifiedMomentum(averaging="sector"), +# geometry=BEMGeometry(Nr=10, Ntheta=20), +# tiploss_model=NoTipLoss(), +# ) +# mit_sector_umm_start = time.time() +# mit_sols_sector_umm = bem_sector_umm(pitch=pitches, tsr=tsrs, yaw=yaws, tilt=tilts) +# mit_sector_umm_end = time.time() +# mit_Ct_sector_umm = mit_sols_sector_umm.Ct() +# mit_Cp_sector_umm = mit_sols_sector_umm.Cp() +# print("MITRotor UMM-BEM Sector-Averaged: " + str(mit_sector_umm_end - mit_sector_umm_start) + " seconds") + +# solve UMM-BEM with LUT though MITRotor - annulus averaged +print("Making LUT!") +bem_annulus_umm_LUT = BEM( + rotor=IEA15MW(), + momentum_model=UnifiedMomentumLUT(averaging="annulus", cache_fn = Path("cache")/ "lut.csv"), + geometry=BEMGeometry(Nr=10, Ntheta=20), + tiploss_model=NoTipLoss(), +) +mit_annulus_umm_LUT_start = time.time() +mit_sols_annulus_umm_LUT = bem_annulus_umm_LUT(pitch=pitches, tsr=tsrs, yaw=yaws, tilt=tilts) +mit_annulus_umm_LUT_end = time.time() +mit_Ct_annulus_umm_LUT = mit_sols_annulus_umm_LUT.Ct() +mit_Cp_annulus_umm_LUT = mit_sols_annulus_umm_LUT.Cp() +print("MITRotor UMM-BEM LUT Annulus-Averaged: " + str(mit_annulus_umm_LUT_end - mit_annulus_umm_LUT_start) + " seconds") + +# solve FLORIS with UMM-BEM though MITRotor - rotor averaged +time_series = TimeSeries( + wind_speeds=wind_speeds, + wind_directions=wind_dirs, + turbulence_intensities=turbulence_intensity, +) +fmodel_rotor_umm = FlorisModel("defaults") +fmodel_rotor_umm.set(layout_x = [0.0], layout_y = [0.0], wind_data = time_series) +fmodel_rotor_umm.set_operation_model(MITRotorTurbine()) # default bem_model uses rotor-averaging +floris_rotor_umm_start = time.time() +fmodel_rotor_umm.run() +floris_rotor_umm_end = time.time() +floris_Ct_rotor_umm = fmodel_rotor_umm.get_turbine_thrust_coefficients() +rotor_area = np.pi * bem_rotor_umm.rotor.R**2 +floris_power_rotor_umm = np.squeeze(fmodel_rotor_umm.get_turbine_powers()) +floris_Cp_rotor_umm = floris_power_rotor_umm / (0.5 * 1.225 * rotor_area * (wind_speeds)**3) +print("FLORIS UMM-BEM Rotor-Averaged: " + str(floris_rotor_umm_end - floris_rotor_umm_start) + " seconds") + +# solve FLORIS with UMM-BEM though MITRotor - annulus averaged +fmodel_annulus_umm = FlorisModel("defaults") +fmodel_annulus_umm.set(layout_x = [0.0], layout_y = [0.0], wind_data = time_series) +fmodel_annulus_umm.set_operation_model(MITRotorTurbine(bem_model = bem_annulus_umm)) # default bem_model uses rotor-averaging +floris_annulus_umm_start = time.time() +fmodel_annulus_umm.run() +floris_annulus_umm_end = time.time() +floris_Ct_annulus_umm = fmodel_annulus_umm.get_turbine_thrust_coefficients() +floris_power_annulus_umm = np.squeeze(fmodel_annulus_umm.get_turbine_powers()) +floris_Cp_annulus_umm = floris_power_annulus_umm / (0.5 * 1.225 * rotor_area * (wind_speeds)**3) +print("FLORIS UMM-BEM Annulus-Averaged: " + str(floris_annulus_umm_end - floris_annulus_umm_start) + " seconds") + +# solve FLORIS with UMM-BEM with LUT though MITRotor - annulus averaged +fmodel_annulus_umm_LUT = FlorisModel("defaults") +fmodel_annulus_umm_LUT.set(layout_x = [0.0], layout_y = [0.0], wind_data = time_series) +fmodel_annulus_umm_LUT.set_operation_model(MITRotorTurbine(bem_model = bem_annulus_umm_LUT)) # default bem_model uses rotor-averaging +floris_annulus_umm_LUT_start = time.time() +fmodel_annulus_umm_LUT.run() +floris_annulus_umm_LUT_end = time.time() +floris_Ct_annulus_umm_LUT = fmodel_annulus_umm_LUT.get_turbine_thrust_coefficients() +floris_power_annulus_umm_LUT = np.squeeze(fmodel_annulus_umm_LUT.get_turbine_powers()) +floris_Cp_annulus_umm_LUT = floris_power_annulus_umm_LUT / (0.5 * 1.225 * rotor_area * (wind_speeds)**3) +print("FLORIS UMM-BEM LUT Annulus-Averaged: " + str(floris_annulus_umm_LUT_end - floris_annulus_umm_LUT_start) + " seconds") + +# Presentation-friendly typography +plt.rcParams.update({ + "font.size": 20, + "axes.titlesize": 20, + "axes.labelsize": 22, + "xtick.labelsize": 20, + "ytick.labelsize": 20, +}) + +# plot CT values against one another and against IEA15MW from figure 3.1-C (https://docs.nrel.gov/docs/fy20osti/75698.pdf) +fig, (ax0, ax1) = plt.subplots(figsize=(17, 9), ncols = 2, sharex = True, sharey = True) +fig.suptitle("IEA 15 MW FLORIS Interface Validation") +alpha = 0.6 +ax0.plot( + wind_table, + df["Thrust Coefficient [-]"].to_list(), + linewidth=6, + label="IEA15MW", + color='tab:orange', + linestyle = "solid", + alpha = alpha, + zorder = 1, +) + +ax0.plot( + wind_speeds, + mit_Ct_rotor_umm, + label="MITRotor UMM Rotor-Averaged", + linewidth=6, + color='tab:blue', + linestyle = "solid", + alpha = alpha, + zorder = 1, +) +ax0.plot( + wind_speeds, + mit_Ct_annulus_umm_LUT, + label="MITRotor UMM LUT Annulus-Averaged", + linewidth=6, + color='tab:red', + linestyle = "solid", + alpha = alpha, + zorder = 1, +) + +ax0.plot( + wind_speeds, + mit_Ct_annulus_umm, + label="MITRotor UMM Annulus-Averaged", + linewidth=6, + color='tab:green', + linestyle = "solid", + alpha = alpha, + zorder = 1, +) + +ax0.scatter( + wind_speeds, + floris_Ct_rotor_umm, + label="FLORIS-MITRotor UMM Rotor-Averaged", + color='tab:blue', + alpha = alpha, + marker = "o", + zorder = 2, + s = 80, +) +ax0.scatter( + wind_speeds, + floris_Ct_annulus_umm, + label="FLORIS-MITRotor UMM Annulus-Averaged", + color='tab:green', + alpha = alpha, + zorder = 2, + s = 80, + marker = "s" +) +ax0.scatter( + wind_speeds, + floris_Ct_annulus_umm_LUT, + label="FLORIS-MITRotor UMM LUT Annulus-Averaged", + color='tab:red', + alpha = alpha, + zorder = 2, + s = 80, + marker = "v" +) + +ax0.set_xlabel("Wind Speed [m/s]") +ax0.set_ylabel("$C_T$") +ax0.tick_params() +ax0.set_title("$C_T$") + +# plot Cp values against one another and against IEA15MW from figure 3.1-C (https://docs.nrel.gov/docs/fy20osti/75698.pdf) +ax1.plot( + wind_table, + df["Aero Power Coefficient [-]"].to_list(), + label="IEA15MW", + linewidth=6, + color='tab:orange', + linestyle = "solid", + alpha = alpha, + zorder = 1 +) +ax1.plot( + wind_speeds, + mit_Cp_rotor_umm, + label="MITRotor UMM Rotor-Averaged", + linewidth=6, + color='tab:blue', + linestyle = "solid", + alpha = alpha, + zorder = 1 +) +ax1.plot( + wind_speeds, + mit_Cp_annulus_umm_LUT, + label="MITRotor UMM LUT Annulus-Averaged", + linewidth=6, + color='tab:red', + linestyle = "solid", + alpha = alpha, + zorder = 1 +) +ax1.plot( + wind_speeds, + mit_Cp_annulus_umm, + label="MITRotor UMM Annulus-Averaged", + linewidth=6, + color='tab:green', + linestyle = "solid", + alpha = alpha, + zorder = 1 +) + +ax1.scatter( + wind_speeds, + floris_Cp_rotor_umm, + label="FLORIS-MITRotor UMM Rotor-Averaged", + color='tab:blue', + marker = "o", + alpha = alpha, + s = 80, + zorder = 2 +) +ax1.scatter( + wind_speeds, + floris_Cp_annulus_umm, + label="FLORIS-MITRotor UMM Annulus-Averaged", + color='tab:green', + marker = "s", + alpha = alpha, + s = 80, + zorder = 2 +) +ax1.scatter( + wind_speeds, + floris_Cp_annulus_umm_LUT, + label="FLORIS-MITRotor UMM LUT Annulus-Averaged", + color='tab:red', + marker = "v", + alpha = alpha, + s = 80, + zorder = 2 +) + +ax1.set_xlabel("Wind Speed [m/s]") +ax1.set_ylabel("$C_P$") +ax1.set_title("$C_P$") +ax1.legend( + fontsize=16, + loc="upper right", +) + +plt.savefig(figdir / "example_6_IEA15mw_CT_CP.png", dpi=300) diff --git a/examples/example_07_LUT_timing.py b/examples/example_07_LUT_timing.py new file mode 100644 index 0000000..988b814 --- /dev/null +++ b/examples/example_07_LUT_timing.py @@ -0,0 +1,128 @@ +import numpy as np +from pathlib import Path +from MITRotor.Momentum import UnifiedMomentumLUT, UnifiedMomentum +from MITRotor.TipLoss import NoTipLoss +from MITRotor import BEM, IEA15MW, BEMGeometry +import pandas as pd +import time + +# Floris imports +from floris import FlorisModel, TimeSeries +from MITRotor.FlorisInterface.FlorisInterface import MITRotorTurbine, default_bem_factory + +bem_rotor_umm = default_bem_factory() +bem_annulus_umm_LUT = BEM( + rotor=IEA15MW(), + momentum_model=UnifiedMomentumLUT(averaging="annulus", cache_fn = Path("cache")/ "lut.csv"), + geometry=BEMGeometry(Nr=10, Ntheta=20), + tiploss_model=NoTipLoss(), +) +rotor_area = np.pi * bem_rotor_umm.rotor.R**2 + +bem_rotor_times = [] +bem_annulus_LUT_times = [] +wind_speeds_all = [] +bem_rotor_values = [] +bem_annulus_LUT_values = [] +ns = [5 * i for i in range(1, 21)] +for n in ns: + print(f"{n} wind speeds") + wind_speeds = np.linspace(5, 20, n) + wind_dirs = np.full_like(wind_speeds, 270.0) + turbulence_intensity = np.zeros_like(wind_speeds) + wind_speeds_all.extend( + np.squeeze(wind_speeds) + ) + + time_series = TimeSeries( + wind_speeds=wind_speeds, + wind_directions=wind_dirs, + turbulence_intensities=turbulence_intensity, + ) + + fmodel_rotor_umm = FlorisModel("defaults") + fmodel_rotor_umm.set(layout_x = [0.0], layout_y = [0.0], wind_data = time_series) + fmodel_rotor_umm.set_operation_model(MITRotorTurbine(bem_model = bem_rotor_umm)) # default bem_model uses rotor-averaging + floris_rotor_umm_start = time.time() + fmodel_rotor_umm.run() + floris_rotor_umm_end = time.time() + dt_rotor = floris_rotor_umm_end - floris_rotor_umm_start + print("FLORIS UMM-BEM Rotor-Averaged: " + str(dt_rotor) + " seconds") + bem_rotor_times.append(dt_rotor) + floris_Cp_rotor_umm = np.squeeze(fmodel_rotor_umm.get_turbine_powers()) / (0.5 * 1.225 * rotor_area * (wind_speeds)**3) + bem_rotor_values.extend( + np.squeeze(floris_Cp_rotor_umm) + ) + + # solve FLORIS with UMM-BEM with LUT though MITRotor - annulus averaged + fmodel_annulus_umm_LUT = FlorisModel("defaults") + fmodel_annulus_umm_LUT.set(layout_x = [0.0], layout_y = [0.0], wind_data = time_series) + fmodel_annulus_umm_LUT.set_operation_model(MITRotorTurbine(bem_model = bem_annulus_umm_LUT)) # default bem_model uses rotor-averaging + floris_annulus_umm_LUT_start = time.time() + fmodel_annulus_umm_LUT.run() + floris_annulus_umm_LUT_end = time.time() + dt_annulus_LUT = floris_annulus_umm_LUT_end - floris_annulus_umm_LUT_start + print("FLORIS UMM-BEM LUT Annulus-Averaged: " + str(dt_annulus_LUT) + " seconds") + bem_annulus_LUT_times.append(dt_annulus_LUT) + floris_Cp_annulus_umm_LUT = np.squeeze(fmodel_annulus_umm_LUT.get_turbine_powers()) / (0.5 * 1.225 * rotor_area * (wind_speeds)**3) + bem_annulus_LUT_values.extend( + np.squeeze(floris_Cp_annulus_umm_LUT) + ) + +# make timing CSV +vectorized = True +rows = [] + +for n, dt in zip(ns, bem_rotor_times): + rows.append({ + "n_wind_speeds": n, + "runtime_seconds": dt, + "model": "rotor_umm", + "vectorized": vectorized + }) + +for n, dt in zip(ns, bem_annulus_LUT_times): + rows.append({ + "n_wind_speeds": n, + "runtime_seconds": dt, + "model": "annulus_lut", + "vectorized": vectorized + }) + +df = pd.DataFrame(rows) + +csv_path = Path("cache")/ "timing_results.csv" + +if csv_path.exists(): + df.to_csv(csv_path, mode="a", header=False, index=False) +else: + df.to_csv(csv_path, index=False) + +# make values CSV +rows = [] +# Rotor +for wind, val in zip(wind_speeds_all, bem_rotor_values): + rows.append({ + "wind_speed": wind, + "power": val, + "model": "rotor_umm", + "vectorized": vectorized + }) + +# Annulus LUT +for wind, val in zip(wind_speeds_all, bem_annulus_LUT_values): + rows.append({ + "wind_speed": wind, + "power": val, + "model": "annulus_lut", + "vectorized": vectorized + }) + +df = pd.DataFrame(rows) + +csv_path = Path("cache") / "value_results.csv" + +if csv_path.exists(): + df.to_csv(csv_path, mode="a", header=False, index=False) +else: + df.to_csv(csv_path, index=False) diff --git a/examples/example_08_floris_rosco.py b/examples/example_08_floris_rosco.py new file mode 100644 index 0000000..99d2d38 --- /dev/null +++ b/examples/example_08_floris_rosco.py @@ -0,0 +1,301 @@ +# Python modules +import os +import matplotlib.pyplot as plt +import tempfile +from pathlib import Path +from ruamel.yaml import YAML +import numpy as np +import pandas as pd +import polars as pl +from scipy.interpolate import interp1d +import time + +# FLORIS modules +from floris import FlorisModel, TimeSeries + +# ROSCO toolbox modules +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox.inputs.validation import load_rosco_yaml + +# MITRotor modules +from MITRotor.Momentum import UnifiedMomentumLUT +from MITRotor import BEM, BEMGeometry, IEA15MW +from MITRotor.FlorisInterface.FlorisInterface import MITRotorTurbine, default_bem_factory, default_pitch_interp, default_tsr_interp +from MITRotor.FlorisInterface.ROSCOInterface import get_rosco_control_interps, query_controls + +figdir = Path("fig") + +def change_control_param(param_key, param_value, template_yaml, bem): + yaml = YAML() + with tempfile.TemporaryDirectory() as tmpdir: + temp_yaml = Path(tmpdir) / "rosco_temp.yaml" + + with open(template_yaml) as f: + data = yaml.load(f) + + data["controller_params"][param_key] = param_value + + with open(temp_yaml, "w") as f: + yaml.dump(data, f) + + pitch_interp, tsr_interp, rated_rotor_speed = get_rosco_control_interps(temp_yaml, bem) + return pitch_interp, tsr_interp, rated_rotor_speed + +def get_turbine_power_coefficent(fturbine, fmodel, wind_speeds): + rotor_area = np.pi * fturbine.bem_model.rotor.R**2 + floris_power = np.squeeze(fmodel.get_turbine_powers()) + floris_Cp = floris_power / (0.5 * 1.225 * rotor_area * (wind_speeds)**3 * fturbine.eff_ratio) + return floris_Cp, floris_power / 1e6 # MW + +def main(): + # wind condtions + wind_speeds = np.linspace(3, 25, 25) + wind_dirs = np.full_like(wind_speeds, 270.0) + turbulence_intensity = np.zeros_like(wind_speeds) + time_series = TimeSeries( + wind_speeds=wind_speeds, + wind_directions=wind_dirs, + turbulence_intensities=turbulence_intensity, + ) + + # load example trajectories from ROSCO Paper Figure 2: + # Abbas, N. J., Zalkind, D. S., Pao, L., & Wright, A. (2022). + # A reference open-source controller for fixed and floating offshore wind turbines. + # Wind Energy Science, 7(1), 53-73. + abbas_pitch = pd.read_csv("examples/examples_in/IEA15_pitch.csv") # note that this is in degrees + abbas_tsr = pd.read_csv("examples/examples_in/IEA15_TSR.csv") + abbas_pitch_interp = interp1d(abbas_pitch["x"], abbas_pitch["y"], kind="linear", fill_value="extrapolate", bounds_error=False) + abbas_tsr_interp = interp1d(abbas_tsr["x"], abbas_tsr["y"], kind="linear", fill_value="extrapolate", bounds_error=False) + + # create new MITRotor BEM model with a LUT for UMM + print("Generating new LUT for BEM.") + cache_dir = Path("cache") + cache_dir.mkdir(exist_ok=True, parents=True) + cache_file = cache_dir / "lut.csv" + lut_model = UnifiedMomentumLUT( + cache_fn=cache_file, + regenerate=False, + LUT_Cts=np.linspace(-0.5,1.5,40), + LUT_yaws=np.linspace(0.0,40.0,40), + ) + print("LUT for BEM done generating. ") + bem = BEM(rotor = IEA15MW(), momentum_model = lut_model, geometry = BEMGeometry(Nr=10, Ntheta=20)) + + # Load IEA15MW ROSCO parameters to make controllers + start = time.time() + rosco_yaml_PS_Mode_3 = "MITRotor/ReferenceTurbines/ROSCO_IEA15MW.yaml" + rosco_PS_Mode_3_pitch_interp, rosco_PS_Mode_3_tsr_interp, rosco_PS_Mode_3_rated_rotorspeed = get_rosco_control_interps( + rosco_yaml_PS_Mode_3, bem, + regenerate = False, save_control_file = "control.csv") + end = time.time() + print(f"Time to make control CSV: {end - start}") + + # rosco_PS_Mode_0_pitch_interp, rosco_PS_Mode_0_tsr_interp, rosco_PS_Mode_0_rated_rotorspeed = change_control_param("PS_Mode", 0, rosco_yaml_PS_Mode_3, bem) + + # Plot IEA15MW control from ROSCO paper, ROSOC control with PS_Mode = 3, and ROSOC control with PS_Mode = 0 + pitch_abbas = abbas_pitch_interp(wind_speeds) + # pitch_ps0 = np.rad2deg(rosco_PS_Mode_0_pitch_interp(wind_speeds)) + pitch_ps3 = np.rad2deg(query_controls(rosco_PS_Mode_3_pitch_interp, wind_speeds, 0.0)) + + tsr_abbas = abbas_tsr_interp(wind_speeds) + # tsr_ps0 = rosco_PS_Mode_0_tsr_interp(wind_speeds) + tsr_ps3 = query_controls(rosco_PS_Mode_3_tsr_interp, wind_speeds, 0.0) + + # Create figure + fig, ax = plt.subplots(1, 2, figsize = (10,4), sharey = True, constrained_layout=True) + fig.suptitle(fr"Setpoint Trajectories") + # Plot pitch + # ax[0].plot(wind_speeds, pitch_ps0, label="ROSCO: PS_Mode = 0", lw=3) + ax[0].plot(wind_speeds, pitch_ps3, label="ROSCO: PS_Mode = 3", lw=3, linestyle = "dashed") + ax[0].plot(wind_speeds, pitch_abbas, label="Abbas et al. Fig 2", lw=3, linestyle = "dotted") + + ax[0].set_xlabel("Wind Speed [m/s]") + ax[0].set_ylabel("Pitch [deg]") + ax[0].set_title("Pitch Schedule") + ax[0].grid(True) + + # Plot TSR + # ax[1].plot(wind_speeds, tsr_ps0, label="MITRotor+FLORIS+ROSCO: PS_Mode = 0", lw=3) + ax[1].plot(wind_speeds, tsr_ps3, label="MITRotor+FLORIS+ROSCO: PS_Mode = 3", lw=3, linestyle = "dashed") + ax[1].plot(wind_speeds, tsr_abbas, label="Abbas et al. ROSCO Control", lw=3, linestyle = "dotted") + + ax[1].set_xlabel("Wind Speed [m/s]") + ax[1].set_ylabel("TSR [-]") + ax[1].set_title("Tip-Speed Ratio (TSR) Schedule") + ax[1].grid(True) + ax[1].legend() + + plt.savefig(figdir / "example_8_IEA15mw_controls.png", dpi=300) + + # make FLORIS turbines + # floris_default_turbine = MITRotorTurbine( + # bem_model = bem, + # ) + + # floris_abbas_turbine = MITRotorTurbine( + # bem_model = bem, + # pitch_interp = abbas_pitch_interp, + # pitch_rad = False, + # tsr_interp = abbas_tsr_interp, + # ) + + # floris_PS_Mode_0_turbine = MITRotorTurbine( + # bem_model = bem, + # pitch_interp = rosco_PS_Mode_0_pitch_interp, + # pitch_rad = True, + # tsr_interp = rosco_PS_Mode_0_tsr_interp, + # rated_rotor_speed = rosco_PS_Mode_0_rated_rotorspeed, + # ) + + floris_PS_Mode_3_turbine = MITRotorTurbine( + bem_model = bem, + pitch_interp = rosco_PS_Mode_3_pitch_interp, + pitch_rad = True, + tsr_interp = rosco_PS_Mode_3_tsr_interp, + rated_rotor_speed = rosco_PS_Mode_3_rated_rotorspeed, + ) + yaw = 0.0 # degrees + yaw_angles = [[yaw] for _ in np.arange(len(wind_speeds))] + # fmodel_default = FlorisModel("defaults") + # fmodel_default.set(layout_x = [0.0], layout_y = [0.0], wind_data = time_series, yaw_angles = yaw_angles) + # fmodel_default.set_operation_model(floris_default_turbine) + # fmodel_default.run() + # Ct_default = fmodel_default.get_turbine_thrust_coefficients() + # Cp_default, P_default = get_turbine_power_coefficent(floris_default_turbine, fmodel_default, wind_speeds) + + # fmodel_abbas = FlorisModel("defaults") + # fmodel_abbas.set(layout_x = [0.0], layout_y = [0.0], wind_data = time_series, yaw_angles = yaw_angles) + # fmodel_abbas.set_operation_model(floris_abbas_turbine) + # fmodel_abbas.run() + # Ct_abbas = fmodel_abbas.get_turbine_thrust_coefficients() + # Cp_abbas, P_abbas = get_turbine_power_coefficent(floris_abbas_turbine, fmodel_abbas, wind_speeds) + + + # fmodel_PS_Mode_0 = FlorisModel("defaults") + # fmodel_PS_Mode_0.set(layout_x = [0.0], layout_y = [0.0], wind_data = time_series, yaw_angles = yaw_angles) + # fmodel_PS_Mode_0.set_operation_model(floris_PS_Mode_0_turbine) + # fmodel_PS_Mode_0.run() + # Ct_PS_Mode_0 = fmodel_PS_Mode_0.get_turbine_thrust_coefficients() + # Cp_PS_Mode_0, P_PS_Mode_0 = get_turbine_power_coefficent(floris_PS_Mode_0_turbine, fmodel_PS_Mode_0, wind_speeds) + + fmodel_PS_Mode_3 = FlorisModel("defaults") + fmodel_PS_Mode_3.set(layout_x = [0.0], layout_y = [0.0], wind_data = time_series, yaw_angles = yaw_angles) + fmodel_PS_Mode_3.set_operation_model(floris_PS_Mode_3_turbine) + fmodel_PS_Mode_3.run() + Ct_PS_Mode_3 = fmodel_PS_Mode_3.get_turbine_thrust_coefficients() + Cp_PS_Mode_3, P_PS_Mode_3 = get_turbine_power_coefficent(floris_PS_Mode_3_turbine, fmodel_PS_Mode_3, wind_speeds) + + # plot CT values against one another and against IEA15MW from figure 3.1-C (https://docs.nlr.gov/docs/fy20osti/75698.pdf) + fig, (ax1, ax2, ax3) = plt.subplots(ncols = 3, sharey = False, figsize = (16,4), constrained_layout=True) + fig.suptitle(fr"$C_T$ and $C_P$ with Yaw = {yaw} for Different Control Strategies") + # ax1.plot( + # wind_speeds, Ct_default, label="FLORIS+MITROTOR + Gaertner et al. Control", + # lw=3, linestyle = "solid", zorder = 1, + # ) + # ax1.plot( + # wind_speeds, Ct_abbas, label="FLORIS+MITROTOR Abbas et al. Control", + # lw=3, linestyle = "solid", zorder = 1, + # ) + # ax1.plot( + # wind_speeds, Ct_PS_Mode_0, label="FLORIS+MITROTOR+ROSCO: PS_Mode = 0", + # lw=3, linestyle = "dashed", zorder = 1, + # ) + ax1.plot(wind_speeds, Ct_PS_Mode_3, label="FLORIS+MITROTOR+ROSCO: PS_Mode = 3", + lw=3, linestyle = "dotted", zorder = 1, + ) + ax1.set_xlabel("Wind Speed [m/s]") + ax1.set_ylabel("$C_T [-]$") + ax1.set_title("$C_T$") + ax1.grid(True) + ax1.legend() + + # ax2.plot( + # wind_speeds, Cp_default, label="Gaertner et al. IEA15MW Ref", + # lw=3, linestyle = "solid", zorder = 1, + # ) + # ax2.plot( + # wind_speeds, Cp_abbas, label="Abbas et al. ROSCO Control", + # lw=3, linestyle = "solid", zorder = 1, + # ) + # ax2.plot( + # wind_speeds, Cp_PS_Mode_0, label="FLORIS + MITROTOR + ROSCO: PS_Mode = 0", + # lw=3, linestyle = "dashed", zorder = 1, + # ) + ax2.plot(wind_speeds, Cp_PS_Mode_3, label="FLORIS + MITROTOR + ROSCO: PS_Mode = 3", + lw=3, linestyle = "dotted", zorder = 1, + ) + ax2.set_xlabel("Wind Speed [m/s]") + ax2.set_ylabel("$C_P [-]$") + ax2.set_title("$C_P$") + ax2.grid(True) + ax2.legend() + + # ax3.plot( + # wind_speeds, P_default, label="Gaertner et al. IEA15MW Ref", + # lw=3, linestyle = "solid", zorder = 1, + # ) + # ax3.plot( + # wind_speeds, P_abbas, label="Abbas et al. ROSCO Control", + # lw=3, linestyle = "solid", zorder = 1, + # ) + # ax3.plot( + # # wind_speeds, P_PS_Mode_0, label="FLORIS + MITROTOR + ROSCO: PS_Mode = 0", + # # lw=3, linestyle = "dashed", zorder = 1, + # # ) + ax3.plot(wind_speeds, P_PS_Mode_3, label="FLORIS + MITROTOR + ROSCO: PS_Mode = 3", + lw=3, linestyle = "dotted", zorder = 1, + ) + ax3.axhline(y = 15, lw=3, linestyle = "dotted", zorder = 0, color = "k", label = "15MW") + ax3.set_xlabel("Wind Speed [m/s]") + ax3.set_ylabel("$Power [MW]$") + ax3.set_title("$Power$") + ax3.grid(True) + ax3.legend(loc = 'lower left') + + plt.savefig(figdir / "example_8_IEA15mw_CT_CP.png", dpi=300) + + # plot the difference in CT/CP curves for different yaw values + yaw_list = [0.0, 10.0, 20.0] # degrees + fig, (ax1, ax2, ax3) = plt.subplots(ncols = 3, sharey = False, figsize = (10,4), constrained_layout=True) + fig.suptitle(fr"$C_T$ and $C_P$ under Yaw for FLORIS + MITROTOR + ROSCO: PS_Mode = 3") + for (i, yaw) in enumerate(yaw_list): + yaw_angles = [[yaw] for _ in np.arange(len(wind_speeds))] + fmodel_PS_Mode_3 = FlorisModel("defaults") + fmodel_PS_Mode_3.set(layout_x = [0.0], layout_y = [0.0], wind_data = time_series, yaw_angles = yaw_angles) + fmodel_PS_Mode_3.set_operation_model(floris_PS_Mode_3_turbine) + fmodel_PS_Mode_3.run() + ct = fmodel_PS_Mode_3.get_turbine_thrust_coefficients() + cp, p = get_turbine_power_coefficent(floris_PS_Mode_3_turbine, fmodel_PS_Mode_3, wind_speeds) + + ax1.plot(wind_speeds, ct, label=fr"Yaw = ${yaw}^\circ$", + lw=3, linestyle = "solid", zorder = 1, + ) + ax2.plot(wind_speeds, cp, label=fr"Yaw = ${yaw}^\circ$", + lw=3, linestyle = "solid", zorder = 1, + ) + ax3.plot(wind_speeds, p, label=fr"Yaw = ${yaw}^\circ$", + lw=3, linestyle = "solid", zorder = 1, + ) + + ax1.set_xlabel("Wind Speed [m/s]") + ax1.set_ylabel("$C_T [-]$") + ax1.set_title("$C_T$") + ax1.grid(True) + + ax2.set_xlabel("Wind Speed [m/s]") + ax2.set_ylabel("$C_P [-]$") + ax2.set_title("$C_P$") + ax2.grid(True) + + ax3.axhline(y = 15, lw=3, linestyle = "dotted", zorder = 0, color = "k", label = "15MW") + ax3.set_xlabel("Wind Speed [m/s]") + ax3.set_ylabel("$Power [MW]$") + ax3.set_title("$Power$") + ax3.grid(True) + ax3.legend() + plt.savefig(figdir / "example_8_IEA15mw_CT_CP_yawed.png", dpi=300) + + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/examples/example_timing.py b/examples/example_timing.py new file mode 100644 index 0000000..169e3d7 --- /dev/null +++ b/examples/example_timing.py @@ -0,0 +1,129 @@ +import numpy as np +from pathlib import Path +from MITRotor.Momentum import UnifiedMomentumLUT, UnifiedMomentum +from MITRotor.TipLoss import NoTipLoss +from MITRotor import BEM, IEA15MW, BEMGeometry +import pandas as pd +import time + +# Floris imports +from floris import FlorisModel, TimeSeries +from MITRotor.FlorisInterface.FlorisInterface import MITRotorTurbine, default_bem_factory + +bem_rotor_umm = default_bem_factory() +bem_annulus_umm_LUT = BEM( + rotor=IEA15MW(), + momentum_model=UnifiedMomentumLUT(averaging="annulus", cache_fn = Path("cache")/ "lut.csv"), + geometry=BEMGeometry(Nr=10, Ntheta=20), + tiploss_model=NoTipLoss(), +) +rotor_area = np.pi * bem_rotor_umm.rotor.R**2 + +bem_rotor_times = [] +bem_annulus_LUT_times = [] +wind_speeds_all = [] +bem_rotor_values = [] +bem_annulus_LUT_values = [] +ns = [5 * i for i in range(1, 21)] +for n in ns: + print(f"{n} wind speeds") + wind_speeds = np.linspace(5, 20, n) + wind_dirs = np.full_like(wind_speeds, 270.0) + turbulence_intensity = np.zeros_like(wind_speeds) + wind_speeds_all.extend( + np.squeeze(wind_speeds) + ) + + time_series = TimeSeries( + wind_speeds=wind_speeds, + wind_directions=wind_dirs, + turbulence_intensities=turbulence_intensity, + ) + + fmodel_rotor_umm = FlorisModel("defaults") + fmodel_rotor_umm.set(layout_x = [0.0], layout_y = [0.0], wind_data = time_series) + fmodel_rotor_umm.set_operation_model(MITRotorTurbine(bem_model = bem_rotor_umm)) # default bem_model uses rotor-averaging + floris_rotor_umm_start = time.time() + fmodel_rotor_umm.run() + floris_rotor_umm_end = time.time() + dt_rotor = floris_rotor_umm_end - floris_rotor_umm_start + print("FLORIS UMM-BEM Rotor-Averaged: " + str(dt_rotor) + " seconds") + bem_rotor_times.append(dt_rotor) + floris_Cp_rotor_umm = np.squeeze(fmodel_rotor_umm.get_turbine_powers()) / (0.5 * 1.225 * rotor_area * (wind_speeds)**3) + bem_rotor_values.extend( + np.squeeze(floris_Cp_rotor_umm) + ) + + # solve FLORIS with UMM-BEM with LUT though MITRotor - annulus averaged + fmodel_annulus_umm_LUT = FlorisModel("defaults") + fmodel_annulus_umm_LUT.set(layout_x = [0.0], layout_y = [0.0], wind_data = time_series) + fmodel_annulus_umm_LUT.set_operation_model(MITRotorTurbine(bem_model = bem_annulus_umm_LUT)) # default bem_model uses rotor-averaging + floris_annulus_umm_LUT_start = time.time() + fmodel_annulus_umm_LUT.run() + floris_annulus_umm_LUT_end = time.time() + dt_annulus_LUT = floris_annulus_umm_LUT_end - floris_annulus_umm_LUT_start + print("FLORIS UMM-BEM LUT Annulus-Averaged: " + str(dt_annulus_LUT) + " seconds") + bem_annulus_LUT_times.append(dt_annulus_LUT) + floris_Cp_annulus_umm_LUT = np.squeeze(fmodel_annulus_umm_LUT.get_turbine_powers()) / (0.5 * 1.225 * rotor_area * (wind_speeds)**3) + bem_annulus_LUT_values.extend( + np.squeeze(floris_Cp_annulus_umm_LUT) + ) + +# make timing CSV +vectorized = False +rows = [] + +for n, dt in zip(ns, bem_rotor_times): + rows.append({ + "n_wind_speeds": n, + "runtime_seconds": dt, + "model": "rotor_umm", + "vectorized": vectorized + }) + +for n, dt in zip(ns, bem_annulus_LUT_times): + rows.append({ + "n_wind_speeds": n, + "runtime_seconds": dt, + "model": "annulus_lut", + "vectorized": vectorized + }) + +df = pd.DataFrame(rows) + +csv_path = Path("cache")/ "timing_results.csv" + +if csv_path.exists(): + df.to_csv(csv_path, mode="a", header=False, index=False) +else: + df.to_csv(csv_path, index=False) + +# make values CSV +rows = [] +# Rotor +for wind, val in zip(wind_speeds_all, bem_rotor_values): + rows.append({ + "wind_speed": wind, + "power": val, + "model": "rotor_umm", + "vectorized": vectorized + }) + +# Annulus LUT +for wind, val in zip(wind_speeds_all, bem_annulus_LUT_values): + rows.append({ + "wind_speed": wind, + "power": val, + "model": "annulus_lut", + "vectorized": vectorized + }) + +df = pd.DataFrame(rows) + +csv_path = Path("cache") / "value_results.csv" + +if csv_path.exists(): + df.to_csv(csv_path, mode="a", header=False, index=False) +else: + df.to_csv(csv_path, index=False) + diff --git a/examples/example_timing_plots.py b/examples/example_timing_plots.py new file mode 100644 index 0000000..0bc9835 --- /dev/null +++ b/examples/example_timing_plots.py @@ -0,0 +1,96 @@ +import pandas as pd +import matplotlib.pyplot as plt +from pathlib import Path + +# ---- Load data ---- +figdir = Path("fig") +time_df = pd.read_csv(Path("cache")/ "timing_results.csv") +value_df = pd.read_csv(Path("cache")/ "value_results.csv") + +#------------------------------------ +# Timing plot +#------------------------------------ +df_avg = ( + time_df.groupby(["n_wind_speeds", "model", "vectorized"], as_index=False) + .agg( + runtime_mean=("runtime_seconds", "mean"), + runtime_std=("runtime_seconds", "std"), + ) +) + +# ---- Create label column for plotting ---- +def make_label(row): + base = { + "rotor_umm": "UMM Rotor-Averaged", + "annulus_lut": "UMM LUT Annulus-Averaged", + }[row["model"]] + + if row["vectorized"]: + return base + " (Vectorized)" + else: + return base + +df_avg["label"] = df_avg.apply(make_label, axis=1) + +label_order = [ + "UMM Rotor-Averaged", + "UMM LUT Annulus-Averaged", + "UMM Rotor-Averaged (Vectorized)", + "UMM LUT Annulus-Averaged (Vectorized)", +] + +# ---- Plot ---- +plt.figure(figsize=(6, 4)) + +for label in label_order: + group = df_avg[df_avg["label"] == label] + group = group.sort_values("n_wind_speeds") + + plt.errorbar( + group["n_wind_speeds"], + group["runtime_mean"], + yerr=group["runtime_std"], + marker="o", + capsize=3, + label=label, + linewidth = 2, + ) + # plt.yscale("log") + +plt.xlabel("Number of Wind Speeds Run\n(evenly-spaced between 5-20 m/s)") +plt.ylabel("Runtime (seconds)") +plt.title("Runtime vs Number of Wind Speeds") +plt.legend() +plt.grid(True) +plt.tight_layout() +plt.savefig(figdir / "example_timings.png", dpi=300) + +#------------------------------------ +# Value plot +#------------------------------------ +plt.figure(figsize=(6, 4)) + +value_df["label"] = value_df.apply(make_label, axis=1) + +for label in label_order: + group = value_df[value_df["label"] == label] + group = group.sort_values("wind_speed") + is_vectorized = group["vectorized"].iloc[0] + linestyle = "dashed" if is_vectorized else "solid" + zorder = 2 if is_vectorized else 1 + plt.plot( + group["wind_speed"], + group["power"], + linewidth = 3, + label=label, + linestyle = linestyle, + zorder = zorder, + ) + +plt.xlabel("Wind Speed [m/s]") +plt.ylabel("Coefficent of Power ($C_P$)") +plt.title("$C_P$ vs Wind Speed") +plt.legend() +plt.grid(True) +plt.tight_layout() +plt.savefig(figdir / "example_values.png", dpi=300) \ No newline at end of file diff --git a/examples/examples_in/IEA15_TSR.csv b/examples/examples_in/IEA15_TSR.csv new file mode 100644 index 0000000..0c9e459 --- /dev/null +++ b/examples/examples_in/IEA15_TSR.csv @@ -0,0 +1,17 @@ +x,y +3.0474198047419803, 20.782122905027933 +3.7726638772663876, 16.75977653631285 +4.609483960948396, 13.743016759776536 +5.557880055788005, 11.396648044692737 +6.95258019525802, 9.050279329608937 +8.737796373779638, 8.938547486033519 +10.132496513249652, 8.938547486033519 +11.192468619246862, 8.491620111731843 +12.838214783821478, 7.374301675977653 +15.0139470013947, 6.256983240223463 +16.715481171548117, 5.58659217877095 +18.11018131101813, 5.251396648044692 +19.393305439330543, 4.804469273743017 +21.15062761506276, 4.4692737430167595 +22.517433751743376, 4.134078212290502 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(>=0.24)", "matplotlib (>=3.10)", "nc-time-axis", "seaborn"] + [metadata] lock-version = "2.1" -python-versions = ">=3.10,<4.0" -content-hash = "fbfaf93683678bf7892ad47c20c98b358472a8122c7e2c210a885cb80c79fbed" +python-versions = ">3.10, <3.15" +content-hash = "06e1ae0fa2d7a9ffaef337f0c3f5bd81c913f6884ee640d925b8c206da6d7d4d" diff --git a/pyproject.toml b/pyproject.toml index 239968e..d01e8b4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,11 +7,15 @@ readme = "README.md" packages = [{ include = "MITRotor" }] [tool.poetry.dependencies] -python = ">=3.10,<4.0" +python = ">3.10, <3.15" numpy = "^2.2.1" scipy = ">=1.6" unified-momentum-model = {git = "https://github.com/Howland-Lab/Unified-Momentum-Model.git"} pyyaml = "^6.0.1" +floris = {git = "https://github.com/misi9170/floris.git", branch = "feature/user-def-op-mod"} +rosco = "^2.10.4" +ruamel-yaml = "^0.19.1" +seaborn = "^0.13.2" [tool.poetry.group.dev.dependencies] black = { extras = ["jupyter"], version = "^23.9.1" } @@ -30,14 +34,14 @@ matplotlib = "^3.7.3" polars = "^0.19.2" tqdm = "^4.66.1" - [build-system] requires = ["poetry-core"] build-backend = "poetry.core.masonry.api" - [tool.black] line-length = 120 [tool.ruff] line-length = 120 + +include = ["MITRotor/FlorisInterface/*.csv"] diff --git a/tests/test_bem.py b/tests/test_bem.py index b721efd..e58e7f4 100644 --- a/tests/test_bem.py +++ b/tests/test_bem.py @@ -1,4 +1,4 @@ -from MITRotor import BEM, IEA15MW, UnifiedMomentum, BEMGeometry +from MITRotor import BEM, IEA15MW, UnifiedMomentum, UnifiedMomentumLUT, BEMGeometry from UnifiedMomentumModel.Utilities.Geometry import calc_eff_yaw import numpy as np from pytest import approx @@ -6,7 +6,6 @@ def test_IEA15MW(): IEA15MW() - def test_BEM_initialise(): rotor = IEA15MW() BEM(rotor=rotor) @@ -102,4 +101,72 @@ def test_model_yaw_tilt_rotor_phase(): # tilt and yaw should be offset by 90 degrees assert np.isclose(np.abs(theta_mesh[yaw_max_idx] - theta_mesh[tilt_max_idx]), np.pi / 2, atol = deg_atol) # yaw and evenly split yaw/tilt should be offset by 45 degrees - assert np.isclose(np.abs(theta_mesh[yaw_max_idx] - theta_mesh[yaw_and_tilt_max_idx]), np.pi / 4, atol = deg_atol) \ No newline at end of file + assert np.isclose(np.abs(theta_mesh[yaw_max_idx] - theta_mesh[yaw_and_tilt_max_idx]), np.pi / 4, atol = deg_atol) + +def _expected_shape(grid, Np, Nr, Ntheta): + if grid == "rotor": + return () if Np == 0 else (Np,) + elif grid == "annulus": + return (Nr,) if Np == 0 else (Np, Nr) + elif grid == "sector": + return (Nr, Ntheta) if Np == 0 else (Np, Nr, Ntheta) + else: + raise ValueError(grid) + + +def test_BEM_dimensionality(): + Nr, Ntheta = 20, 40 + rotor = IEA15MW() + + bems = [ + BEM(rotor=rotor, + momentum_model=UnifiedMomentum(averaging="rotor"), + geometry=BEMGeometry(Nr=Nr, Ntheta=Ntheta)), + + BEM(rotor=rotor, + momentum_model=UnifiedMomentumLUT(averaging="annulus"), + geometry=BEMGeometry(Nr=Nr, Ntheta=Ntheta)), + + BEM(rotor=rotor, + momentum_model=UnifiedMomentumLUT(averaging="sector"), + geometry=BEMGeometry(Nr=Nr, Ntheta=Ntheta)), + ] + + # --- inputs --- + pitch_s, tsr_s, yaw_s, tilt_s = 0.0, 7.0, 0.0, 0.0 + + pitch_v = np.array([0.0, 0.1, 0.2]) + tsr_v = np.array([6.0, 7.0, 8.0]) + yaw_v = np.array([0.0, 0.1, 0.2]) + tilt_v = np.array([0.0, -0.1, -0.2]) + + cases = [ + (pitch_s, tsr_s, yaw_s, tilt_s, 0), + (pitch_v, tsr_v, yaw_v, tilt_v, 3), + ] + + fields = ["Cp", "Cp_corr", "Ct", "a", "aoa"] + + for pitch, tsr, yaw, tilt, Np in cases: + for bem in bems: + sol = bem(pitch, tsr, yaw=yaw, tilt=tilt) + + # ========================= + # 1. u4, w4 dimensionality + # ========================= + u4 = np.asarray(sol.u4) + w4 = np.asarray(sol.w4) + + expected = () if Np == 0 else (Np,) + assert u4.shape == expected + assert w4.shape == expected + + # ========================= + # 2. Shape checks for fields + # ========================= + for grid in ["rotor", "annulus", "sector"]: + expected_shape = _expected_shape(grid, Np, Nr, Ntheta) + + for name in fields: + val = np.asarray(getattr(sol, name)(grid=grid)) + assert val.shape == expected_shape, f"{name}, {grid}" diff --git a/tests/test_floris_interface.py b/tests/test_floris_interface.py new file mode 100644 index 0000000..ad109ad --- /dev/null +++ b/tests/test_floris_interface.py @@ -0,0 +1,115 @@ +import os +import numpy as np +import pytest +import polars as pl +from numpy.testing import assert_almost_equal, assert_allclose +from floris import FlorisModel, TimeSeries +from MITRotor.FlorisInterface.FlorisInterface import MITRotorTurbine, default_bem_factory, default_pitch_interp, default_tsr_interp + + +def test_pitch_tsr_interpolation(): + # create default interpolators + tsr_interp = default_tsr_interp() + pitch_interp = default_pitch_interp() + + # load raw CSV data + module_dir = os.path.dirname(__file__) # tests/ + validation_csv = os.path.abspath(os.path.join(module_dir, "..", "MITRotor", "FlorisInterface", "IEA_15mw_rotor.csv")) + df = pl.read_csv(validation_csv) + wind_data = df["Wind [m/s]"].to_numpy() + pitch_data = df["Pitch [deg]"].to_numpy() + tip_speed_data = df["Tip Speed [m/s]"].to_numpy() + tsr_data = tip_speed_data / wind_data + + # interpolator reproduces raw data + assert_allclose(tsr_interp(wind_data), tsr_data, rtol=1e-12, atol=1e-12) + assert_allclose(pitch_interp(wind_data), pitch_data, rtol=1e-12, atol=1e-12) + + # reasonable values + x_interp_vals = np.linspace(0.0, 25.0, 100) + tsr_interp_vals = tsr_interp(x_interp_vals) + pitch_interp_vals = pitch_interp(x_interp_vals) + assert np.all(np.isfinite(tsr_interp_vals)) + assert np.all(np.isfinite(pitch_interp_vals)) + assert np.all(tsr_interp_vals > 0.0) + assert np.all(pitch_interp_vals >= -10.0) # deg, loose bound + assert np.all(pitch_interp_vals <= 40.0) + + +# compute MITRotor BEM outputs directly +def compute_mitrotor_cp_ct_a(wind_speeds, yaw_deg = 0.0, tilt_deg = 0.0): + bem_model = default_bem_factory() # default BEM (IEA15MW) used in floris interface + pitch_interp = default_pitch_interp() # IEA15MW pitch curve + tsr_interp = default_tsr_interp() # IEA15MW tsr curve + + n = len(wind_speeds) + Ct = np.empty(n) + a = np.empty(n) + for i, ws in enumerate(wind_speeds): + pitch = np.deg2rad(pitch_interp(ws)) + tsr = tsr_interp(ws) + sol = bem_model(pitch, tsr, yaw=np.deg2rad(yaw_deg), tilt = np.deg2rad(tilt_deg)) + Ct[i] = sol.Ct() + a[i] = sol.a() + + return Ct, a + +@pytest.mark.parametrize("n_turbines", [1, 2]) +def test_mitrotor_floris_wind_speeds(n_turbines): + wind_speeds = np.array([6.0, 8.0, 10.0, 12.0]) + wind_dirs = np.full_like(wind_speeds, 270.0) + turbulence_intensity = np.zeros_like(wind_speeds) + + time_series = TimeSeries( + wind_speeds=wind_speeds, + wind_directions=wind_dirs, + turbulence_intensities=turbulence_intensity, + ) + + layout_x = np.linspace(0.0, 500.0 * (n_turbines - 1), n_turbines) + layout_y = np.zeros_like(layout_x) + + fmodel = FlorisModel("defaults") + fmodel.set(layout_x=layout_x, layout_y=layout_y, wind_data=time_series) + fmodel.set_operation_model(MITRotorTurbine()) + + fmodel.run() + + floris_Ct = fmodel.get_turbine_thrust_coefficients() + floris_a = fmodel.get_turbine_axial_induction_factors() + + mit_Ct, mit_a = compute_mitrotor_cp_ct_a(wind_speeds) + + # First turbine matches MITRotor BEM (<1% error) + assert_almost_equal(floris_Ct[:, 0], mit_Ct, decimal=2) + assert_almost_equal(floris_a[:, 0], mit_a, decimal=2) + + if n_turbines > 1: + # first turbine produces more power than the second (wake effects) + floris_power = fmodel.get_turbine_powers() + assert np.all(floris_power[:, 0] > floris_power[:, 1]) + + # yawing the first turbine decreases first turbine power and increases second turbine power + fmodel = FlorisModel("defaults") + yaw_angles = np.tile(np.array([5.0, 0.0]), (4,1)) + fmodel.set(layout_x=layout_x, layout_y=layout_y, wind_data=time_series, yaw_angles = yaw_angles) + fmodel.set_operation_model(MITRotorTurbine()) + fmodel.run() + yawed_floris_power = fmodel.get_turbine_powers() + assert np.all(floris_power[:, 0] > yawed_floris_power[:, 0]) + assert np.all(floris_power[:, 1] < yawed_floris_power[:, 1]) + + # TODO: uncomment if tilt is able to be set for Floris + # tilting the first turbine decreases first turbine power and increases second turbine power + # fmodel = FlorisModel("defaults") + # tilt_angles = np.tile(np.array([5.0, 0.0]), (4,1)) + # fmodel.set(layout_x=layout_x, layout_y=layout_y, wind_data=time_series, tilt_angles = tilt_angles) + # fmodel.set_operation_model(MITRotorTurbine()) + # fmodel.run() + # tilted_floris_power = fmodel.get_turbine_powers() + # assert np.all(floris_power[:, 0] > tilted_floris_power[:, 0]) + # assert np.all(floris_power[:, 1] < tilted_floris_power[:, 1]) + + # # yawing and tilting turbines is equivalent + # assert_almost_equal(yawed_floris_power[:, 0], tilted_floris_power[:, 0], decimal=4) + # assert_almost_equal(yawed_floris_power[:, 1], tilted_floris_power[:, 1], decimal=4)