A fuzzy-based non-dominated sorting genetic algorithm-II for joint energy and reserves market clearing

摘要: In this paper, market clearing of joint energy and reserves auctions is framed as a multi-objective mathematical programming (MMP) to simultaneously consider the economic security objectives. Social welfare maximization, minimization lines overload voltage deviation well loadability limit maximization are competitive objectives proposed framework. Traditional MMP methods such direction scalarization $$\varepsilon $$?-constraint scalarize objective vector into single objective. Those cases time-consuming require number runs equal desired efficient solutions. fuzzy-based non-dominated sorting genetic algorithm-II (NSGA-II) find optimal schedule units reserves. method, improve performance NSGA-II, fuzzy inference system employed dynamically set parameters NSGA-II ($$P_\mathrm{c}$$Pc $$P_\mathrm{m})$$Pm). Results testing method on IEEE 24-bus Reliability Test System (IEEE RTS) presented compared with scalarization, weighted sum from efficiency, diversity computational burden requirement points view. These comparisons confirm efficiency developed method.