Crow-Fuzzy Double Sorting Optimization For Many-objective Optimal Power Flow And Operation Decision-making

The optimal power flow problem is among the important tools used in operation and planning of power systems.At present the research on optimal power flow is mostly concentrated in double goals or three goals.With the never-ending growing needs for the human beings,such as environmental benefits,and the cost of power users,optimal power flow problem is no longer aiming at the single objective or two objectives of optimal power flow problem,but transforms into a many-objective optimal power flow problem.In recent years,scholars has achieved satisfactory results in the dual objectives or three optimal power flow problem using evolutionary algorithm based on the Pareto.However,evolutionary algorithm lost its original optimization ability in solving many-objective optimal power flow problem.To solve the problems,this paper established a many-objective optimal power flow model contains six objectives,and proposed a crow-fuzzy double sorting method to solve the model,the specific steps are as follows:First,this paper does the research about the effects on optimal power flow exerted by the increasing of objective dimension,and reveals the causes of problems produced by calculating many-objective optimal power flow with the existing multi-objective algorithms.The increasing objective dimension results in the exponential rise of non-dominated individuals,the number of individuals in population appear serious shortage relative to the huge objective space,makes the multi-objective evolutionary algorithm based on the Pareto dominance losing the original selection pressure,causing it difficult to convergence of the algorithm and can't get satisfy the requirements of the solution set.Then,according to the above problem,this paper proposed a crow-fuzzy double sorting method.This method can continuously differentiate individuals into different degrees of optimality beyond the classification of the original Pareto dominance.and combining the crowding distance,quantitative analysis of the dominated degree of many-objective optimal power flow.In the proposed design,the crow-fuzzy double sorting method incorporated into the original multi-objective differential evolution algorithm(MODE),form to CF-MODE.The simulation results show that CF-MODE can make a high quality solution set by calculating many-objective optimal power flow.while they perform better than others.Finally,in the perspective of multi-attribute decision-making point of view,the focus is to how to choose the final dispatch solution of a multi-objective power system dispatching,proposed a crow-fuzzy multiple attribute decision making method based on grey correlation.First,this method use mixed empowerment based on maximizing deviation for objective weights allocation.Then using the method of grey correlation coefficient to normalized processing of dispatch objective,can effectively evaluate uncertainty relation between various targets.The simulation results show that crow-fuzzy multiple attribute decision making method based on grey correlation can be more reasonable select the final decision solution.