Application of Cuckoo Search Algorithm on the Battery Size and Schedule of a Residential PV-BESS using an Appropriate State of Charge for Cost Optimization

Self-consumption of locally generated electricity from photovoltaic (PV) systems is becoming a significant application area of stationary battery energy storage systems (BESS). Many papers used different optimization techniques in optimizing a PV-BESS system. In this paper, an optimization of battery size and load scheduling using Cuckoo Search Algorithm was done to minimize the overall cost of the consumer using the optimal minimum and maximum states of charge. The optimization and testing process was conducted in MATLAB
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. The result showed that the optimal minimum and maximum state of charge were 34% and 90% respectively. The overall cost of the optimized PV-BESS system was 35.37% lower than the un-optimized PV-BESS system. It was statistically verified that there was a significant difference between the overall cost of an optimized and unoptimized PV-BESS system.