# A Lagrangian Policy for Optimal Energy Storage Control

arXiv: https://arxiv.org/abs/1901.09507 · HTML: https://mlsanity.com/paper/1901.09507/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Jan 2019.

## Built on by (most cited first, 1 of 1)

- [End-to-End Demand Response Model Identification and Baseline Estimation with Deep Learning](https://mlsanity.com/paper/2109.00741/) (2021)

## Abstract (arXiv)

This paper presents a millisecond-level look-ahead control algorithm for energy storage with constant space complexity and worst-case linear run-time complexity. The algorithm connects the optimal control with the Lagrangian multiplier associated with the state-of-charge constraint. It is compared to solving look-ahead control using a state-of-the-art convex optimization solver. Simulation results show that both methods obtain the same control result, while the proposed algorithm runs up to 100,000 times faster and solves most problems within one millisecond. The theoretical results from developing this algorithm also provide key insights into designing optimal energy storage control schemes at the centralized system level as well as under distributed settings.