Owing to the rapid development of microgrids(MGs)and growing applications of renewable energy resources,multiobjective optimal dispatch of MGs need to be studied in detail.In this study,a multiobjective optimal dispat...Owing to the rapid development of microgrids(MGs)and growing applications of renewable energy resources,multiobjective optimal dispatch of MGs need to be studied in detail.In this study,a multiobjective optimal dispatch model is developed for a standalone MG composed of wind turbines,photovoltaics,diesel engine unit,load,and battery energy storage system.The economic cost,environmental concerns,and power supply consistency are expressed via subobjectives with varying priorities.Then,the analytic hierarchy process algorithm is employed to reasonably specify the weight coefficients of the subobjectives.The quantum particle swarm optimization algorithm is thereafter employed as a solution to achieve optimal dispatch of the MG.Finally,the validity of the proposed model and solution methodology are con firmed by case studies.This study provides refere nee for mathematical model of multiojective optimizati on of MG and can be widely used in current research field.展开更多
In multiobjective optimization, trade-off analysis plays an important role in determining most preferred solution. This paper presents an explicit interactive trade-off analysis based on the surrogate worth trade-off ...In multiobjective optimization, trade-off analysis plays an important role in determining most preferred solution. This paper presents an explicit interactive trade-off analysis based on the surrogate worth trade-off function to determine the best compromised solution. In the multiobjective framework thermal power dispatch problem is undertaken in which four objectives viz. cost, NOx emission, SOx emission and COx emission are minimized simultaneously. The interactive process is implemented using a weighting method by regulating the relative weights of objectives in systematic manner. Hence the weighting method facilitates to simulate the trade-offrelation between the conflicting objectives in non-inferior domain. Exploiting fuzzy decision making theory to access the indifference band, interaction with the decision maker is obtained via surrogate worth trade-off （SWT） functions of the objectives. The surrogate worth trade-off functions are constructed in the functional space and then transformed into the decision space, so the surrogate worth trade-off functions of objectives relate the decision maker＇s preferences to non-inferior solutions through optimal weight patterns. The optimal solution of thermal power dispatch problem is obtained by considering real and reactive power losses. Decoupled load flow analysis is performed to find the transmission losses. The validity of the proposed method is demonstrated on 11-bus, 17-lines IEEE system, comprising of three generators.展开更多
基金State Grid Corporation Science and Technology Project(520605190010).
文摘Owing to the rapid development of microgrids(MGs)and growing applications of renewable energy resources,multiobjective optimal dispatch of MGs need to be studied in detail.In this study,a multiobjective optimal dispatch model is developed for a standalone MG composed of wind turbines,photovoltaics,diesel engine unit,load,and battery energy storage system.The economic cost,environmental concerns,and power supply consistency are expressed via subobjectives with varying priorities.Then,the analytic hierarchy process algorithm is employed to reasonably specify the weight coefficients of the subobjectives.The quantum particle swarm optimization algorithm is thereafter employed as a solution to achieve optimal dispatch of the MG.Finally,the validity of the proposed model and solution methodology are con firmed by case studies.This study provides refere nee for mathematical model of multiojective optimizati on of MG and can be widely used in current research field.
文摘In multiobjective optimization, trade-off analysis plays an important role in determining most preferred solution. This paper presents an explicit interactive trade-off analysis based on the surrogate worth trade-off function to determine the best compromised solution. In the multiobjective framework thermal power dispatch problem is undertaken in which four objectives viz. cost, NOx emission, SOx emission and COx emission are minimized simultaneously. The interactive process is implemented using a weighting method by regulating the relative weights of objectives in systematic manner. Hence the weighting method facilitates to simulate the trade-offrelation between the conflicting objectives in non-inferior domain. Exploiting fuzzy decision making theory to access the indifference band, interaction with the decision maker is obtained via surrogate worth trade-off （SWT） functions of the objectives. The surrogate worth trade-off functions are constructed in the functional space and then transformed into the decision space, so the surrogate worth trade-off functions of objectives relate the decision maker＇s preferences to non-inferior solutions through optimal weight patterns. The optimal solution of thermal power dispatch problem is obtained by considering real and reactive power losses. Decoupled load flow analysis is performed to find the transmission losses. The validity of the proposed method is demonstrated on 11-bus, 17-lines IEEE system, comprising of three generators.
