Study On Electrical Distribution Network Planning Project Evaluation Based On Life Cycle Cost

With the development of economy, and deepening the degree of market in power industry, the reliability of the electric power supply has got more attention from the power supply enterprise and the user, the key of distribution network planning is how to meeting the power supply reliability requirements of the premise to obtain the optimal economic benefits and social benefits of distribution network planning project in the life cycle. On the based of widely read domestic and foreign relevant literatures about distribution network planning, this paper summarizes previous research results and do in-depth study of multi-stage optimization of distribution network structure planning.From the perspective of the life cycle of distribution network planning project, considering the costs of each stage during planning period of the electrical distribution networks planning project, taking the time value of money into account, meanwhile considering the power balance of the distribution network and other constraints, to minimal the present value of costs of electricity as the objective function that the model of multi-stage optimization of distribution network structure planning is put forward, then we will get the optimal planning that coordinate the reliability and economy.Because of considering the life cycle cost, the model that had been put forward in the paper has more optimization variables and parameter, and also with complex constraints, it needs a better optimization algorithm. Based on researching various types of optimization algorithms, stochastic particle swarm optimization with passive congregate is put forward to overcome the problem of premature convergence on particle swarm optimization, dividing initial population with clustering thought, introducing the idea of passive congregate among population members and taking measures of optimum retention and stochastic particles supplement, convergence precision and ability of global optimization of the particle swarm optimization are improved. Finally using test functions to verify efficacy and practicality of the particle swarm optimization. Based on Microsoft Visual Studio2005development environment, using C#language realized the proposed model in the paper and using stochastic particle swarm optimization with passive congregate to solve the mathematical model, then we will get the optimal planning. Through the analysis of an example, the model proposed by this paper is verified to be correct and feasible.