Optimization of Electric Power Generation for Expansion Planning and Cost-Saving Using Decomposition Techniques: A Case of Developing Countries S. L. Braide, D.C. Idoniboyeobu Abstract-This paper formulated the framework of optimization of electric power generation for expansion planning and cost saving. The inability of the power systems in developing countries to generate enough electric power has led to extra-ordinary power losses on the line due to the over load dependence thereby making the power system planning and running cost outrageous. This paper considered the application of decomposition techniques for an optimization search in order to break-down the capacity allocation (that is, the forecasted load or energy demand for twenty (20yrs) projection was determined, which served as the input data for the capacity allocation to the generating stations especially in a developing country like Nigeria, include the following capacities of generating stations:2250MW Afam power, 2350MW Sapele power and 3000MW to Egbin power as expected power to be generated from these stations). The paper examined the existing capacity of the generating stations and considered a capacity-mix combination as: (200MW, 250MW and 300MW) which served as the input data: row-element matrix while the column-element matrix need to be determined or factor-out into different number of unit combination arrangement to achieve different options for the best selection. Five optimization plans was developed with respect to five different number of unit-combination arrangement in order to have a total respective operational cost of the following: N 8,176,503,40,800, N 7,654,267,24,800, N 7,499,530,60,800, N 7,460,846,44,800 and N 5,206,095,83,900. The research paper strongly identified the functional relationship between capacity and cost this shows that as capacity of the generating plant increases, the operational running cost of the power plant also increases this is being validated with two-tail test and spearman’s rank correlation coefficient with ( k R : 0.99375) approximately +1 which shows that there is a correlation that exist between capacity and cost Index Terms: optimization planning, generation expansion, cost-saving, decomposition techniques of electric power, profit. S. L. Braide: Department of Electrical Engineering, Rivers State University, (Nigeria), braidesepiribo@yahoo.com ; sepiribo.braide@ust.edu.ng , +2348036660873 D.C. Idoniboyeobu: Department of Electrical Engineering, Rivers State University, Port Harcourt, Nigeria, dikioidoniboyeobu@yahoo.com ; +2348037120018 I INTRODUCTION onsidering the growing demand, increasing diversities of services, and advances in generation, transmission and distribution system which are prompting industries, companies, private-sector, individuals etc.[1]. to rapidly expand and modernize their networks in order to satisfy the consumer (the end-user in terms of energy demand [2]. The main function of a power generating station is to deliver power to the targeted number of consumers. However, the electric power demands of different consumers vary in accordance with their level of activities [3]. The result of this variation in demand is that the load on the power station is never constant; rather it varies from time to time[4]. Most of the complexities of modern power plan- operation gave rise from the inherent variability of the load demand by the users. Unfortunately, electrical power cannot be stored and the power station must produce power when demanded to meet the requirements of the consumer. Similarly, the power engineers would like the alternators in the power station to run at their rated capacity for maximizing efficiency, but the demands of consumers have wide variation. This makes the control of a power generating station highly complex to solve mathematically. Power stations control and operation are done, using engineering modeling, engineering optimization by decomposition technique etc [5]. Most of these models involve optimization approach or techniques. Ideally, without large scale storage, power supply and demand must be matched at all times, therefore, optimization of electric power generation for expansion planning and cost-solving can be solved in isolation from one period to the next in a consistent and continuous programme for different look-ahead periods. This paper presented a simple decomposition technique that would strongly put into consideration of the planning programme of the load forecast-result (for energy demand) with the aim of minimizing cost and maximizing profit (optimization- plan) [6]. C Proceedings of the World Congress on Engineering and Computer Science 2019 WCECS 2019, October 22-24, 2019, San Francisco, USA ISBN: 978-988-14048-7-9 ISSN: 2078-0958 (Print); ISSN: 2078-0966 (Online) WCECS 2019