Dual Layer Optimization Model for Capacity Configuration of Rural Multi-Microgrid System with Biogas Energy Generation

[Objective] To solve the problem of new energy system capacity allocation in rural areas， respond to the requirements of rural revitalization and low carbon， and improve the rate of renewable energy consumption， a microgrid system capacity allocation method based on the interaction between sub-microgrids and considering biogas energy generation are proposed. [Methods] First， the structure of rural multi-microgrids was analyzed， and a multi-microgrid system model for biogas energy generation containing an inter-microgrid energy scheduling strategy was established. Subsequently， a two-layer model for capacity allocation and operation co-optimization of a multi-microgrid system incorporating biogas generation was established. The upper-level objective is to minimize the annual integrated cost of the multi-microgrid system while maximizing the utilization of renewable energy sources. Contrarily， the lower-level objective is to minimize the operating cost of the system. The model was solved using a particle swarm optimization algorithm combined with the CPLEX solver. To ensure fair cost allocation among microgrids， the Shapley value method was employed. [Results] Matlab simulation results and example analyses show that the proposed introduction of biogas energy as a power generation unit can increase the penetration rate of new energy. The proposed rural inter-microgrid power interaction effectively reduced the overall capacity allocation of the new energy and energy storage， thereby lowering the annual investment cost. It also decreased the cost of purchasing external power by 9%， although the amount of power sales was correspondingly reduced. The microgrid cost was apportioned using the Shapley value method， and the actual cost of each microgrid was reduced by 6.3%， 2%， and 4%， compared to the scenario of independent operation. Using the Shapley value method to apportion the costs of the microgrids， the actual costs of each microgrid were reduced by 6.3%， 2%， and 4.4%， compared with scenarios in which the microgrids were operated independently. [Conclusions] The proposed two-layer optimization model for the capacity allocation of rural multi-microgrid systems containing biogas energy generation resulted in lower annual integrated costs， reduced carbon emissions， increased internal consumption of new energy sources， and reduced dependence on the grid on the rural load side， which can achieve both economic and environmental friendliness.