Offline battery degradation model

The model predicts battery capacity degradation based on state-of-charge profile and cell temperature, reference here.

Code in Matlab.

Piece-wise linear degradation model for optimization

This is a piece-wise linear model for incorporating nonlinear battery cycle degradation mechanisms into optimization, reference here.

Code in GAMS (requires Gurobi).

Optimal battery control and bidding in frequency regulation

This code demonstrates the optimal response control and bidding design for degradation-sensitive batteries in PJM pay-for-performance frequency regulation markets, reference here.

Code in Matlab.

Dynamic battery lifetime valuation

This code calculates the opportunity value of battery degradation based on historical price data using dynamic programming, reference here.

Code in Julia (requires Gurobi).

Battery price arbitrage using stochastic dynamic programming

The code uses an analytical algorithm to solve stochastic dynamic programming for optimizing battery price arbitrage in wholesale real-time electricity markets, reference here.

Code in Matlab.

Comparing different battery degradation models in power system optimization

The code compares different degradation models in grid optimization. Reference paper is here.

Code in Julia (requires Gurobi).

Transferable energy storage bidder

Algorithms for bidding energy storage to arbitrage in wholesale markets. Reference paper is here.

Code in Python.

Assessing market participation for energy storage

A two-stage market clearing simulation framework to assess energy storage participation in day-ahead and real-time markets. Reference paper is here.

Code in Matlab (requires Gurobi).

Predicting strategic energy storage behaviors

An inverse optimization approach that learns the unknown disutility function of a strategic storage agent from observed price and response data, using input convex neural networks embedded in a differentiable optimization layer. Reference paper is here.

Code in Python.

Energy storage arbitrage in two-settlement markets

An integrated bidding model for energy storage participating in both day-ahead and real-time markets, pairing a transformer-based real-time price forecaster for day-ahead bids with an LSTM and dynamic programming hybrid real-time bidder. Reference paper is here.

Code in Python.

Locational energy storage bid bounds

Chance-constrained bid bounds that serve as locational offer caps for energy storage, aligning storage bids with the social welfare objective while regulating economic withholding. Reference paper is here.

Code in Matlab (requires YALMIP and Gurobi).

Dimension-reduced optimization of multi-zone thermostatically controlled loads

A latent-variable representation learned through multi-task learning that reduces the dimension of multi-zone thermostatically controlled load optimization, with both model-based and model-free solution algorithms. Reference paper is here.

Code in Python.