Determining Cost-Efficient Controls of Electrical Energy Storages Using Dynamic Programming

TL;DR

This paper presents a dynamic programming approach to optimize the cost-efficient control of electrical energy storage, considering discrete energy inputs and nonlinear loss functions, to minimize energy costs for companies.

Contribution

It introduces a rounding-based dynamic programming method that accounts for nonlinear storage losses and offers computational speed-up over traditional integer programming.

Findings

Significant reduction in energy costs for storage control.

Enhanced computational efficiency with the proposed method.

Effective handling of nonlinear energy loss functions.

Abstract

Volatile electrical energy prices are a challenge and an opportunity for small and medium-size companies in energy-intensive industries. By using electrical energy storage and/or an adaptation of production processes, companies can significantly profit from time-depending energy prices and reduce their energy costs. We consider a time-discrete optimal control problem to reach a desired final state of the energy storage at a certain time step. Thereby, the energy input is discrete since only multiples of 100 kWh can be purchased at the EPEX SPOT market. We use available price estimations to minimize the total energy cost by a rounding based dynamic programming approach. With our model non-linear energy loss functions of the storage can be considered and we obtain a significant speed-up compared to the integer (linear) programming formulation.