Economic Load Dispatch Using Strength Pareto Gravitational Search Algorithm with Valve Point Effect H. A. Shayanfar * Center of Excellence for Power System Automation and Operation, Elect. Eng. Dept., Iran University of Science and Technology, Tehran, Iran N. Amjady Electrical Engineering Department, Semnan University, Semnan, Iran A. Ghasemi Young Researcher Club, Ardabil Branch, Islamic Azad University, Ardabil, Iran O. Abedinia Electrical Engineering Department, Semnan University, Semnan, Iran hashayanfar@yahoo.com, ghasemi.agm@gmail.com, n_amjady@yahoo.com, oveis.abedinia@hotmail.com Abstract— The Strength Pareto Gravitational Search Algorithm (SPGSA) to solve Economic Load Dispatch (ELD) is presents this paper with various generator constraints in power systems. The ELD problem in a power system is to determine the optimal combination of power outputs for all generating units which will minimize the total fuel cost while satisfying all practical constraints. For practical generator operation, many nonlinear constraints of the generator, such as ramp rate limits, prohibited operating zone, generation limits, transmission line loss and non-smooth cost functions are all considered using the proposed technique. The proposed algorithm applied on different test standard power system. The effectiveness of the proposed method is compared with other heuristic algorithm. Results showed the efficiency of the proposed algorithm. Keywords: SPGSA, Economic Load Dispatch, Valve Point. I. INTRODUCTION The efficient and optimum economic operation of electric power systems has always occupied an important position in electric power industry. In recent decades, it is becoming very important for utilities to run their power systems with minimum cost while satisfying their customer demand all the time and trying to make profit. With limited availability of generating units and the large increase in power demand, fuel cost and supply limitation, the committed units should serve the expected load demand with the changes in fuel cost and the uncertainties in the load demand forecast in all the different time intervals in an optimal manner. The basic objective of ELD of electric power generation is to schedule the committed generating unit outputs, so as to meet the load demand at minimum operating cost while satisfying all unit and system equality and inequality constraints [1]. The ELD problem has been tackled by many researchers in the past [2]. ELD problem involves different problems. The first is Unit Commitment or pre-dispatch problem where in it is required to select optimally out of the available generating sources to operate to meet the expected load and provide a specified margin of operating reserve over a specified period of time. The second aspect of ELD is on-line economic dispatch where in it is required to distribute the load among the generating units actually parallel with the system in such a manner as to minimize the total cost of supplying power. In case of ELD, The generations are not fixed but they are allowed to take values again within certain limits so as to meet a particular load demand with minimum fuel consumption. The ELD problem is inherently a large-scale, nonlinear, non-convex, non continuous optimization problem. Many techniques are applied to deal with ELD problem both conventional optimization approaches [3-4] such as Linear Programming (LP) or Quadratic Programming (QP) and Artificial Intelligence (AI)-based optimization techniques such as Simulated Annealing (SA) [5], Tabu Search (TS) [6], Genetic Algorithm (GA) [7-8], hybrid TS/SA [9], Evolutionary Programming (EP) [9], and Improved Evolutionary Programming (IEP) [11] etc. Gravitational Search Algorithm (GSA), a new optimization algorithm is applied to solve the above problem. Algorithm, as mentioned earlier is a new search algorithm that has been proven efficient in solving many problems. In the case of ELD, the main use of GSA would be to obtain a solution close to the global optimum in a short period of time. * Correspanding Author. E-Mail Address: hashayanfar@yahoo.com (H. A. Shayanfar)