Study Of STLF And Transmission Network Expansion Planning Based On Ant Colony Optimization Algorithm

Study work of this paper includes two sections: the study of short-term loadforecasting (STLF) based on recurrent neural network (NN) using ant colonyoptimization algorithm (ACOA) and the study of self-adaptive ACOA withperturbation for transmission network expansion planning. Although STLF researchhas been done for a long history, the precision is seldom high enough for the demandof power system;With the development of power system, there are some newproblems about transmission network expansion planning.This paper is studied based on NN principle for STLF. Back Propagation (BP)and improved BP were widely used in NN forecasting model, but it has someshortcomings, such as slow convergence rate, easy to fall into local minimum and lowgeneralization ability of NN, which result in low forecasting precision. So the study oftraining algorithm for NN forecasting model is an important impact to enhance theprecision of STLF.In this paper the STLF based on recurrent NN model using ACOA is firstproposed. The simulation results of daily and weekly loads forecasting for actual powersystem show that the proposed forecasting model can effectively improve the accuracyof short-term load forecasting (SLTF) and this model is stable and adaptable for bothworkday and rest-day, in addition, its forecasting performance is far better than that ofBP-RNN and GA-RNN.To overcome the stagnation and long searching time appeared in transmissionnetwork expansion planning, a self-adaptive ACOA with perturbation is presented inuse for transmission network expansion planning, the corresponding mathematicalmode is established and solution algorithms are developed. The presented method hasbeen tested on two systems, and the results show its advantage on computing speedand convergence.In this paper, the study of STLF based on recurrent NN using ACOA and thestudy of self-adaptive ACOA with perturbation for transmission network expansionplanning are presented. Through testing, the proposed method has the obviousadvantage and can solve the problem effectively. This paper's study is significative intheory and is worthful in the practice.