Study On The Application Of Particle Swarm Optimization In The System Power Economic Dispatch

Economic dispatch (ED) is a typical power system operation optimization problem. But it has non-smooth cost functions with equality and inequality constraints that make the problem of finding the global optimum difficult. According to the characteristics of economic dispatch problem, a variety of improved algorithms based on particle swarm optimization for solving economic dispatch strategy is researched in this paper. The main content of this paper includes the following areas.Firstly, combining the double-layer evolution structure of Cultural Algorithm (CA) with local search performance of Closed-loop Particle Swarm Optimization (CLPSO), Closed-loop Cultural Particle Swarm Optimization (CLCPSO) algorithm is proposed to deal with the ED problems in this paper. The algorithm adopts the framework of cultural algorithm. Two kinds of spaces, named population space and belief space, are set and the update of two spaces is via acceptance operation and impact operation with synchronous transmission mode. In order to keep the diversity of the population, feedback principle is used to control the evolution velocity of the particles. BP network model of Iris classification problem is used as a simulation example to verify the validity and effectiveness of the algorithm.Secondly, the CLCPSO is used to solve the single-objective economic dispatch of power system problems. The setting strategy of the parameters is analyzed and the balanced constraint is realized using a new mode. ED problems with 3-generators unit with 6-buses system is applied to test the performance of the CLCPSO. The results show that compare to CPSO and CLPSO, CLCPSO not only possesses the better global convergence but also the higher convergent speed. And all the improved algorithms provide better solution than that in the conference.Thirdly, considering the current competitive in the electricity market, the optimal scheduling objective is to pursue multi-faceted. And the CLCPSO is applied to solve multi-objective optimization problem. An impoved analytic hierarchy process (AHP) is adopted to turn multi-objective optimization problem into an appropriate single objective problem. Simulation results of multi-objective ED problems with 6-generators unit with IEEE30-buses system show that the results using the derived algorithm for the multi-objective problem is reasonableness.Lastly, According to the actual situation of the electricity market, the CLCPSO algorithm is applied to the simulated dispatch of thermal power plant in an area. Comparing with the data in the reference, PSO algorithm and improved particle swarm optimization owes validity and feasibility in solving economic dispatch of power system.