Abstract

Photovoltaic battery energy storage systems can increase the self-consumption from residential PV systems and therefore contribute to a decentralized renewable electricity system. Rising electricity prices and decreasing battery prices enhance the economics of residential battery storage. Intelligent operation strategies could further improve the economics and lead to grid relief as well.This paper presents new forecast-based operation strategies for increased battery lifetime and reduced curtailment of PV power feed-into enhance system economics. In addition, these strategies are compared to different commonly used operation strategies in terms of economics and self-sufficiency of the system. Increased battery lifetime is achieved by reducing the average state of charge of the battery by limiting the stored energy according to the predicted energy demand during night. Forecast-based operation strategies are used in combination with variable power feed-in limits of the PV battery storage system to relieve the grid. Two different forecast strategies are discussed: the perfect forecast, which is used as the best case, and the persistence forecast, representing the worst case in terms of forecast accuracy.The operation strategies are evaluated by simulating a DC-coupled PV and battery system. The model is parameterized with measured data from cell testing and battery aging tests. The levelized cost of electricity is used for the economic evaluation of the operation strategies.Results show that the developed forecast-based operation strategy can drastically increase battery lifetime and thus total energy throughput and therefore reduce the levelized cost of electricity by up to 12%. This has been shown effectively for two different types of battery cell, a low-cost consumer cell and a high-quality battery cell. The combination of forecast-based operation strategies with variable feed-in limits can nearly eliminate curtailed PV energy for the simulated system. Sensitivity analyses of component sizing and load profile confirm the findings. The developed strategy can easily be implemented on real residential PV battery energy storage systems since no additional communication interface is required.

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