Multiobjective Optimization of Photo Voltaic Battery System Sizing for Grid-Connected Residential Prosumers Under Time-of-Use Tariff Structures

The integration of photovoltaic and battery energy storage systems into utility grids is favorable for electricity customers, especially for high consumption load patterns due to the high electricity bill. To increase the annual bill savings and decrease the dependency on the utility grid, a procedure of optimally sizing the PV battery system is presented in this paper. A MATLAB-based code of the genetic algorithm is used to maximize the system self-sufficiency and minimize the discounted payback period while guaranteeing the system profitability. The optimization technique is introduced under the time-of-use tariff structure for residential prosumers in two scenarios. The first introduces a sellback energy price equal to the off-peak energy price, and the second introduces a sellback energy price equal to the on-peak energy price. The economic and technical effects of this optimization are described and analyzed. The effect of PV system capital cost, battery capital cost, and discount rate variations is evaluated by sensitivity analysis. The results indicate that for a sellback price equal to the off-peak price, a minimum discounted payback period can be achieved by installing the maximum PV system size without batteries, and it is reduced to half of its value for a sellback price equal to the on-peak price at the same PV system capacity. For a sellback price equal to the off-peak price, the minimum DPBP of 5.8 years can be achieved by installing a 20 kW
_p
PV system without batteries with 47% self-sufficiency and 2.4 years for a sellback price equal to the on-peak price by installing the same system capacity. The proposed approach highlights that increasing the battery size leads to high self-sufficiency without a considerable decrease in the annual bill savings that encourage customers to invest in the PV battery system.