Decentralized price-driven grid balancing via repurposed electric vehicle batteries

Abstract

The share of electricity generated from intermittent renewable sources, e.g., wind and solar grows rapidly. This affects grid stability and power quality. If the share of renewable power generation is to be increased further, additional flexibilities must be introduced.Aggregating small, distributed loads and energy storage facilities is a good medium-term option. In this paper, the suitability of decentralized and on-site optimized storage system consisting of repurposed electric vehicle batteries for grid balancing is investigated. Battery operation is controlled via an optimization procedure, which relies on a one-way communicated pseudo-cost function (PCF). Day-ahead electricity stock market prices are used as the PCF.Based on one year simulations, a sequential quadratic programming (SQP) approach is compared to a dynamic programming (DP) and an integer linear programming (ILP) approach with respect to runtime and control objective. All approaches lead to very similar results, however ILP leads to the shortest runtimes. ILP is then used to investigate the grid balancing potential using last decade's hourly day-ahead prices. Higher market data resolutions featuring quarter-hours introduced in 2014 lead to higher earnings. For hourly day-ahead prices the optimal capacity-to-power ratio of the battery is approximately 6 h while for quarter-hourly prices it is about 3 h.