Investment Planning Problem in Power System Using Artificial Neural Network

Abstract

This paper presents a model to solve Distribution Expansion Planning (DEP) problem. An effective method is proposed to determine an optimal solution for strategic investment planning in distribution system. The proposed method will be formulated by using mean-variance analysis (MVA) approach in the form of mixed-integer quadratic programming problem. Its target is to minimize the risk and maximize the expected return. The proposed method consists of two layers neural networks combining Hopfield network at the upper layer and Boltzmann machine in the lower layer resulting the fast computational time. The originality of the proposed model is it will delete the unit of the lower layer, which is not selected in upper layer in its execution. Then, the lower layer is restructured using the selected units. Due to this feature, the proposed model will improve times and the accuracy of obtained solution. The significance of output from this project is the improvement of computational time and the accurate solution will be obtained. This model might help the decision makers to choose the optimal solution with variety options provided from this proposed method. Therefore, the performance of strategic investment planning in solving DEP problem certainly enhanced.