# Guaranteeing a physically realizable battery dispatch without charge-discharge complementarity constraints

arXiv: https://arxiv.org/abs/2103.07846 · HTML: https://mlsanity.com/paper/2103.07846/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Mar 2021.

## Built on by (most cited first, 2 of 2)

- [Learning to Optimize for Mixed-Integer Non-linear Programming with Feasibility Guarantees](https://mlsanity.com/paper/2410.11061/) (2024)
- [Multi-market Energy Optimization with Renewables via Reinforcement Learning](https://mlsanity.com/paper/2306.08147/) (2023)

## Abstract (arXiv)

The non-convex complementarity constraints present a fundamental computational challenge in energy constrained optimization problems. In this work, we present a new, linear, and robust battery optimization formulation that sidesteps the need for battery complementarity constraints and integers and prove analytically that the formulation guarantees that all energy constraints are satisfied which ensures that the optimized battery dispatch is physically realizable. In addition, we bound the worst-case model mismatch and discuss conservativeness. Simulation results further illustrate the effectiveness of this approach.