Real-time Battery Energy Management for Residential Solar Power System

An energy storage system is a key element of renewable-based power generation. Its flexible operational capabilities reduce not only the impact of intermittent power generation but also operational costs. In this paper, a dynamic penalty function is proposed to the charging term of the cost function to efficiently manage the battery energy and thereby reducing operational costs. The charging/discharging periods of the battery are effectively controlled based on the solar power generation and residential real-time electricity prices (RRTP). The optimisation problem formulated for the application of real-time energy management is solved with the help of particle swarm optimisation (PSO). It is shown that the proposed cost function can reduce operational costs over a time horizon of 96 hours by 4.2 per cent as compared to the cost function reported in the literature. Simulation studies are carried out to demonstrate the effectiveness of the proposed cost function over the existing cost function. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.