366-26

Receding Horizon Optimization of Residential Photovoltaic and Battery Storage Systems using Differential Evolution

J. Počivalnik(1), D. Kuhar(1), E. Simonič(1), B. Stergar(1), S. Seme(1,2), K. Sredenšek(1,2)

1. Faculty of Energy Technology, University of Maribor, Krško, Slovenia

2. Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia

2026-06-27

The paper examines the use of receding horizon optimization combined with differential evolution for the control of a residential battery storage system integrated with a photovoltaic system. The objective is to reduce grid power peaks and overall electrical energy exchange with the grid by optimizing the operating strategy of the battery storage system. The proposed approach is evaluated using real household electrical energy consumption data and modeled photovoltaic system production with a 15-minute time resolution. Three receding horizon optimization configurations with different horizon lengths are analyzed under a fixed optimization time constraint. The results demonstrate that the performance of the battery storage system strongly depends on the selected optimization horizon. Moderate horizons provide a favorable compromise between look-ahead capability and convergence quality, while excessively long horizons suffer from limited convergence. The findings confirm that coordinated operation of photovoltaic and battery storage systems can improve local energy utilization and reduce stress on the electrical energy transmission and distribution system.

Key words: Battery storage system, photovoltaic system, receding horizon optimization, differential evolution, grid interaction reduction

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