Optimization of Battery Storage Capacity and Operation for Balancing Residential PV Installation

Abstract

The paper deals with economic optimization of the installed capacity of residential battery storage, as well as the day-ahead scheduling of energy storage to minimize the prosumer's price and volume risk at the balancing market in the case of small residential PV installations. A deterministic Linear Programming model has been used for battery dimensioning and a Stochastic Linear Programming model based on a day-ahead PV production forecast has been applied for the optimal use of available storage capacity. Both models have been tested using data from a small residential PV installation and household, prices from the Polish market. The paper focused on scenarios with a fully-fledged retail market, with balancing rules consistent with the wholesale segment. The results show that the current prices on the balancing market and high investment costs do not encourage the installation of energy storage, but the price trend of storage tank costs indicates that this situation may change soon. Stochastic linear programming turned out to be an adequate tool for planning the work of residential battery storage facilities, improving the economic effects of using battery storage with deterministic methods.