| The problem of lake or distribution unreasonable reactive power compensation always exists during construction of the network. And because of lacking of unified planning and optimization to reactive power, causes reactive power unbalancing, power factor and voltage dropping, capability of network transmission declining, and active power loss increasing, equipments not being sufficiently utilized, even being damaged. The reactive power distribution of the network is improved , quality of power supply is improved, active power loss is decreased, and voltage quality is improved by using reactive power optimization. There has great significance in theory and practical application.The model and relative solution of reactive power optimization is studied in the paper. Since the reactive power optimization is an integer programming problem with multi-variable and multiple constraints, mathematical model is built based on single objective function of minimum power loss, and model of multi-objective function is built including minimum network loss, average voltage deviation and maximize voltage stable redundancy. Gradient Particle Swarm Optimization(GPSO)algorithm is studied deeply, and an advanced GPSO is presented because of slow convergence and local optimal of GPSO. Firstly apply this algorithm to single objective reactive power optimization of power system with adjusting dynamically penalty function. For the multi-objective reactive power optimization problem, an new intelligent algorithm of Optimization Algorithm on Simulating the Fisher Fishing (SOFA), is introduced in the paper. To meeting the demands of users as much as possible, weight distribution in the constraints of individual preference is applied to handle the weight processing problem in multi-objective optimization. The IEEE-14 and IEEE-30 is simulated by MATLAB 7.0 and comparing with the results of GPSO. The global optimal solution is obtained, and correctness, fitness and economy of models and algorithms are verified. |
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