Optimal design of distribution system expansion planning including distributed generation
No Thumbnail Available
Saudi Digital Library
Traditionally, Distribution System Planning (DSP) problem is concerned with optimal expansion of distribution system facilities to meet the load expansion as well as system constraints. Nowadays, Distributed Generation (DG) is a new option in the electricity industry to meet the electrical demand growth. This thesis provides a new approach to solve the single and multi-objective distribution expansion planning problem including DG. The algorithm is based on Binary Particle Swarm Optimization (BPSO) technique. The aim of the model is to satisfy operational and economical requirements by using DG as a candidate alternative for distribution system planning and avoiding or at least reducing: expanding existing substations, and upgrading existing feeders. The model decides the locations and size of the new facilities in the system as well as the amount of the purchased power from the main grid. The 9-bus and 30-bus distribution systems are used in this work to test the proposed algorithm with different DG penetration levels. The Conventional Weighted Aggregation (CWA) method is used to solve the multi-objective optimization problem so that further objectives functions and constraints can be easily added to the developed software package. The hierarchical clustering technique is used to reduce the number of non-dominated solutions for the decision maker. The results of the single-objective and multi-objective improved the voltage level of the studied systems and reduced the total expansion cost. A comparison between results of a single-objective problem and the multi-objective problem is also presented.