Abstract A multiobjective energy management strategy for a household photovoltaic (PV)–battery–grid system is developed using rule-based control integrated with the nondominated sorting genetic algorithm II. Three operational configurations, such as PV–battery–diesel, PV–grid, and PV–battery–grid, are evaluated using real household load and meteorological data. The optimized PV–battery–grid configuration achieves an annualized system cost of 486.46 USD, CO2 emissions of 2810.8 kgCO2/year, and a levelized cost of energy of 0.041 USD/kWh. A Monte Carlo-based uncertainty analysis with 1000 stochastic samples reveals minimal variability in economic and environmental outcomes, confirming the robustness of the optimal configuration under fluctuating climatic conditions. The results highlight the potential of hybrid household systems to support low-carbon electrification and inform policymaking for the deployment of distributed renewable energy.
Nguyen et al. (Thu,) studied this question.