| Summary: | The typical stand-alone microgrid (MG) composed of wind turbine (WT), photovoltaic (PV), diesel generator (DE), and battery energy storage (BES) is taken as the research object. Firstly, a multi-objective optimal capacity configuration model considering economic efficiency, reliability, and environmental protection is established. Secondly, in view of the complex characteristics of the optimization model, such as strong nonlinearity and multi-constrained conditions, combining the enumeration that can find the complete real Pareto solution set with the intelligent algorithm that has the characteristics of fast convergence, a search algorithm referencing adjacent points based on SPEA2 (SARAP) is proposed. The algorithm obtains the contour of the real Pareto optimal solution set by SPEA2, and then repeatedly extracts the adjacent points that satisfy certain conditions from the solution set solved by SPEA2. A small search space based on the adjacent points is constructed, and an omnidirectional search in this space to achieve the complete real Pareto optimal solution set is performed. The algorithm performance analysis of both computational complexity and convergence shows that the operation speed of SARAP is approximately five times higher than that of the enumeration, and the obtained result is close to the complete real Pareto optimal solution set. Finally, the optimization calculation and typical daily production simulation are carried out according to the resource and load characteristics of a region, and the results further prove the rationality and validity of the proposed algorithm.
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