Multi-objective optimization of multi-energy complementary systems integrated biomass-solar-wind energy utilization in rural areas

Abstract

Rural areas possess abundant renewable energy sources, such as solar and biomass energy; however, the current methods of energy utilization suffer from low efficiency and serious pollution issues. As rural residents’ living standards continue to improve, there is an urgent need to optimize and adjust the structure of rural energy systems. Multi-energy complementary systems (MECS) have the potential to enhance energy utilization efficiency, achieve high efficiency and energy savings, significantly reduce carbon emissions, and effectively address the challenges faced by rural energy development. This study explores a typical framework for rural MECS that integrates photovoltaic, wind turbine, and biomass biogas combined cooling, heating, and power technology while considering the partial load ratio of equipment components and coupling characteristics between different energy sources. Based on various scenarios of valley electricity utilization, multi-objective optimization models are established to determine the capacity of MECS with economy, environment, and primary energy saving rate as objective functions. The non-dominated sorting genetic algorithm (NSGA-II) along with Technique for Order Preference by Similarity to Ideal Solution decision-making method is adopted to obtain optimal solutions from the Pareto solution set. The case study conducted in a rural area of central China has demonstrated the effective enhancement of coupling capacity in MECS through battery storage. By actively storing energy during off-peak electricity periods, battery storage strengthens the complementary capabilities of photovoltaic systems, wind turbines, and itself. This approach allows for a reduction in planned capacity for photovoltaic and wind power systems within MECS while increasing the planned capacity for internal combustion engines, resulting in respective decreases in system investment costs by 16.19% and 13.18%. Furthermore, incorporating more biogas-fired cogeneration during off-peak electricity periods improves the system’s performance economically, environmentally, and with regards to primary energy saving rate.