Shapley Value and Global Harmony Search Algorithm-Based Multi-Objective Configuration Optimization for Rural Microgrids

The development of renewable energy in rural areas presents significant potential. Integrating renewable energy sources, such as wind power and photovoltaics, into microgrids as distributed generation systems offers a viable approach for local energy utilization. In recent years, the rapid advancement of agriculture, forestry, animal husbandry, and fisheries has led to an increasing demand for electricity in these regions. However, the existing power infrastructure remains underdeveloped, resulting in a pronounced imbalance between supply and demand. This paper investigates the optimization of rural microgrid configurations by incorporating demand response strategies and the synergistic interactions among wind turbines, photovoltaic systems, batteries, and loads. A multi-objective optimization model is developed to maximize annual profits and environmental externality (namely, the proposed microgrid achieves equivalent carbon dioxide emissions reductions by replacing thermal power generation through either selling green electricity to the main grid or meeting rural load demands), which is subsequently transformed into a single-objective formulation using the Shapley value method and solved via a global harmonic search algorithm. Simulation results validate the applicability of the proposed solution method and demonstrate the economic performance, development potential, and environmental benefits of the optimized microgrid configurations.