Bilevel Optimization for Energy Storage Bidding

This project implements a bilevel optimization model for strategic storage bidding in electricity markets. The upper level optimizes storage bidding decisions, while the lower level solves the economic dispatch problem that clears the market.

Key Features

• Bilevel Optimization: Implements both convex and non-convex bilevel formulations for storage bidding
• Economic Dispatch: Solves lower-level market clearing with variable renewable energy (VRE) integration
• Storage Modeling: Supports configurable storage capacity, duration, and efficiency parameters
• Scalable Scenarios: Supports different VRE penetration levels, storage capacities, and other sensitivity factors
• Batch Processing: Includes scripts for running multiple scenarios on HPC clusters

Installation

Prerequisites

• Julia (version 1.6 or later recommended)
• Gurobi Optimizer (academic license available)
• Required Julia packages: JuMP, Gurobi, BilevelJuMP, DataFrames, CSV, Plots, VegaLite

Setup

1. Clone the repository:

   git clone https://github.com/Power-Lab/EnergyEcon_Storage_2026.git
   cd EnergyEcon_Storage_2026

2. Install Julia dependencies:

   using Pkg
   Pkg.add(["JuMP", "Gurobi", "BilevelJuMP", "DataFrames", "CSV", "Plots", "VegaLite", "Statistics", "PrettyTables", "FileIO"])

3. Set up Gurobi license (follow Gurobi installation instructions)

Usage

Basic Example

Run a simple simulation:

julia code/run.jl

This will execute a bilevel optimization for a 4-day period with default parameters (20 GW storage capacity, 4-hour duration, wind scale 3x, solar scale 3x).

Batch Processing

For running multiple periods, use the batch scripts:

# Run on HPC
cd batch
sbatch b20_hrs4_w3_s3_days4_ptc10.sh

# Or run directly on a local PC
julia code/run_all_tscc.jl b20_hrs4_w3_s3_days4_ptc10

The run name format is: b{storage_gw}_hrs{duration}_w{wind_scale}_s{solar_scale}_days{simulation_days}_ptc{production_incentive}

Custom Parameters

Modify key parameters in code/run_all_tscc.jl for HPC runs or code/run_all_pc.jl for local runs:

• storage_cap_gw: Storage capacity in GW
• storage_duration: Storage duration in hours
• one_way_efficiency: Storage one-way efficiency
• wind_cap_scale: Wind capacity multiplier
• solar_cap_scale: Solar capacity multiplier
• ramping_charge_scenario: Ramping charge cost scenario
• ramping_charge: Storage ramping charge cost
• bidding_ptc: Renewable production tax incentive in $/MW

Project Structure

├── code/                       # Julia source code
│   ├── bilevel_cvx.jl          # Convex bilevel formulation
│   ├── ed.jl                   # Economic dispatch model
│   └── run.jl                  # Single period run
│   └── run_all_tscc.jl         # HPC run for multiple periods
│   └── run_all_pc.jl           # Local run for multiple periods
├── data/                       # Input datasets
│   ├── data_WECC_small_mod/    # WECC system data
│   ├── data_WECC_large/        # WECC system data (more detailed)
├── batch/                      # SLURM batch scripts
├── figure/                     # Output figures
├── result/                     # Output results
└── LICENSE                     # MIT License

Data Sources

The project uses WECC (Western Electricity Coordinating Council) system data and synthetic datasets for testing. Data includes:

• Generator parameters and costs
• Load profiles
• Variable renewable energy capacity factors
• Fuel prices

License

This project is licensed under the MIT License - see the LICENSE file for details.

Maintainer

Zhenhua Zhang
Email: zhenhua@ucsd.edu
Affiliation: University of California, San Diego