OPTIMIZED DESIGN METHOD OF PV-BATTERY ENERGY SYSTEM FOR RESIDENTIAL BUILDINGS IN CHINA SOLAR-RICH AREA
This paper constructs models for the various components of the system,with the annual total cost and the building self-sufficiency as the objective functions and PV installation parameters and capacity,and battery capacity as the decision variables.By balancing energy flow and equipment efficiency,we obtained the design parameters of the PV-battery system by utilizing non-dominated sorting genetic algorithm(NSGA-Ⅱ).The enhanced TOPSIS method was employed to determine the optimal system capacity across varying scenarios.Using residential buildings in Lhasa as a case study,we explored and validated the methodology's practicality.Our findings show that this approach effectively determines the PV-battery system's installation and capacity parameters,meeting dual objectives of building autonomy and cost-effectiveness.Meanwhile,the decision of whether excess electricity is fed back to the grid significantly influences the design of the energy system.
solar energybattery storageoptimizationNSGA-Ⅱ algorithmTOPSIS
NETL
NSTL
万方数据
