This research study is the application of Geographic Information System (GIS) for distribution substation. The main purpose is to satisfy user by planning to support the increase of load at present and in the future. Moreover increase in creditability of distribution system by increasing new substation or expand the area of exist substation. Then Geographic Information System is necessary for the mentioned reason. Geographic Information System is the process of geographical data in computer system that defined useful information and related to spatial data such as residential property house number location latitude and longitude. Geographic Information System consists of capture store manipulate analyze manage and present all types of geographical data according to user’s objective. So Geographic Information System is the utility that be useful for distribution substation project. The research is planning to use Geographic Information System for finding Break-even point between increasing new substation or expand the area of exist substation which is 2 case studies.

This research study is the economic load dispatch ELD is the method of determining the most efficient low-cost and reliable operation of a power system by dispatching the available electricity generation resources to supply the load on the system. The main objective of ELD is to schedule the committed generating units output to meet the required load demand at minimum cost satisfying all unit and system operational constraints. With the proper scheduled outputs of generating units it can lead to a significant cost saving of generating systems. This paper presents an optimization technique to economic load dispatch (ELD) problems with considering the daily load patterns and generator constraints using a particle swarm optimization (PSO). The objective is to minimize the fuel cost. The optimization problem is subject to system constraints consisting of power balance and generation output of each units. The application of a constriction factor into PSO is a useful strategy to ensure convergence of the particle swarm algorithm. The proposed method is able to determine the output power generation for all of the power generation units so that the total constraint cost function is minimized. The performance of the developed methodology is demonstrated by case studies in test system of fifteen-generation units. The results show that the proposed algorithm gives the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction.