RBF Neural Networks Based On Genetic Algorithm Used In Line Losses Calculation For Distribution Network

The line losses of power distribution network, which had caught much attention of power enterprises and many related organizations, plays a very important role in evaluating the economics of a power system. Since the reform of the power industry, line losses has directly affected the power price, which is vital to the benefit of enterprises.Accurate and convenient methods of calculating the line losses is very important not only to the evaluation of line losses management, but also to the formulations of losses decreasing measurement.Firstly existing methods for calculation of the theoretical line losses is investigated in detail in this paper, and the limitation of them is also pointed out. According to the characteristics of power distribution system in our country, this paper presents a RBFNN based on Genetic Algorithm, which is applied in calculating the line losses of power distribution systems. The radial basis fuction (RBF) neural network, due to its nonlinear processing ability, is used to map complex nonlinear relationship between the line losses and the feature factors in power distribution systems. But in the traditional methods, the parameters of the hidden layer and the output layer are trained separately. The Genetic Algorithm (GA), a global optimization algorithm simulating organic evolution, is used to optimize the parameters of the RBF network. The coding method put all the parameters in one chromosome optimize them synchronously. It can strengthen the cooperation between the hidden layer and the output layer, and optimizes the neural work to avoid the network parameters suffering into partial minimum.In order to validate the practicability and feasibility of this method, this paper has two simulations respectively. A distribution network in some aera with 68 lines and the distribution network of Binhai power company with 67 lines are used as examples. The simulation recults show that the RBF neural network based on GA has so many advantages such as simple configuration, high convergence speed, high precision and so on. It can memory the complex nonlinear relationship between the line losses and the feature factors in distribution network accurately. So the method presented in this paper has good practicability and should be popularized in other areas.At last, based on the OOP (Object Oriented Programming) ideology, this paper developed visual software for distribution network losses calculation on C++ Builder platform. The proposed software has many fuctions including that circuit diagram painting, parameter input, data base management, distribution network losses calculation, report output and so on. It has better performances in software visualization and friendly interface. Provided many shortcuts, which are according to the international standard styles, it is easy for users to study and operate. After the designing phrase, the software was tested for many times in order to make sure the integrality, security and dependability.