2013 3rd International Conference on Electric Power and Energy Conversion Systems, Yildiz Teclmical University, Istanbul, Turkey, October 2-4,2013 Solution to Economic Emission Load Dispatch Problem Using Modiied Artiicial Bee Colony Algorithm H.T. Jadhav Shubham Raj Ranjit Roy Electrical Engineering Department Rajarambapu Institute of Technology Islampur, India. htj@ritindia.edu Electrical Engineering Department SV National Institute of Technology, Surat, India Electrical Engineering Department SV National Institute of Technology, Surat, India r@svnit.eed.ac.in shubhamraj 108@gmail.com Abstract- This paper presents an application of modiied artiicial bee colony algorithm (MABC) to determine the optimized solution of economic and emission load dispatch (EELD) problem. The EELD problem is formulated as a biobjective problem by taking minimization of fuel cost and emission levels as objectives. In order to convert a biobjective problem into a single objective function weighing factor is used. Effectiveness of the MABC algorithm is veriied by applying it on ive standard test systems and the outcomes are compared with the latest reported literatures. It is proved from the results that MABC algorithm is more powerful than other algorithms. Keywords- economic and emission load dispatch; modied aticial bee colony algorithm; price penalty factor; weighing factor I. INTRODUCTION A considerable segment of the world's power plants are using fossil uels like natural gas, coal, oil as principal resource for production of elecricity. It is becoming most important to make use of existing resources consciously and supply electricity at lowest rate. Economic dispatch (ED) is a key task in power system operation and planning. The primary objective of classical ED is to allocate the amount of power produced by generating units to among the loads and limit total operating cost while satisying all equality and inequality constraints of the system. As a result of global warming, the environmental pollution is becoming an alarming aspect to the world. Therefore the classical ED problem is modiied to economic emission load dispatch (EELO) to produce power in cost effective manner and also with minimum pollution [I]. Artiicial bee colony (ABC) algorithm invented by Karaboga has been proved to be more effective than some conventional biological-inspired algorithms like genetic algorithm (GA), differential evolution (DE) and particle swarm optimization (PSO). But, ABC is superior at exploration and poor at exploitation. This paper presents a recently developed optimization method, where ABC algorithm is modiied to guide the search of candidate solution towards the global optima [2]. The signiicant contributions of this paper are as follows: Modiied artiicial bee colony algorithm (MABC) is implemented to solve EELO problem and applied to ive standard test systems consisting of 6, 10, II, 14 and 40 thermal units. The corresponding results are compared with the methods available in recent literatures. Rest of the paper is aranged as follows: Section II provides the EELD problem formulation. In section III an overview of employed optimization techniques is presented. In section IV result and discussion of different test cases is provided. Finally, conclusions are drawn in section V. II. EELD PROBLEM FORMULATION The EELO problem seeks the best generation schedule for the generating plants to supply the required demand plus transmission losses with minimum production cost and emission. The objective unction and constraints for the EELO problem are as formulated below. A. Classical EELD p roblem In this paper the objective unction which represents total cost of operation (TC) consists of two independent objectives namely uel cost (FC) and emission (E). The bi-objective EELO problem is expressed in single-objective form as in (1) using a price penalty factor (h) [3]. Minimize; F 'HD = WI FC + wzhE subject to; I. Power balance constraint, n L� = P J + . i=l 2. Inequality constraint, Pimin :; Pi :; �m ax 3. Ramp rate limit, p _ pini :; UR I 1 I pint _ p :; DR I I I (1) (2) (3) (4) where F C : uel cost of ith thermal unit; E : emission in kg/h; w I and w 2 are weighing factors such that w I + w 2 = 1; h is price penalty factor; Pi: output power of ith generating unit in MW; n: number of generating units in 978-1-4799-0688-8/13/$31.00 ©2013 lEEE