Double-Layer Cycle Capacity Optimization Model of Rural Biogas-Solar-Wind Integrated Energy System

with the development of rural areas and the application of low-carbon energy technologies, the construction of rural energy system has encountered problems such as high cost, environmental pollution, and low consumption rate of new energy. In this paper, a rural biogas-solar-wind integrated energy system framework was designed. Then, a double-layer cycle capacity optimization model for integrated energy systems(IES) in rural areas was proposed. The outer layer capacity configuration model takes the lowest total annual cost, the lowest carbon dioxide emission and the highest primary energy saving rate as the objective function, and non-dominated sorting genetic algorithm(NSGA-III) were used to calculate the optimal capacity of each equipment in the IES. The inner layer optimization scheduling model takes the total annual operating cost of the system as the objective function, and the CPLEX solver were used to calculate optimal scheduling result of IES equipment. The inner and outer layer models are mutually constrained. Finally, the solution is obtained from the Pareto curve using the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS) method. The simulation results verify the effectiveness of the proposed model, which can take into account the economy, environmental protection and new energy consumption, and effectively realize the collaborative optimization of the system.