American Journal of Mathematical and Computer Modelling 2016; 1(1): 1-14 http://www.sciencepublishinggroup.com/j/ajmcm doi: 10.11648/j. ajmcm.20160101.11 Identifying a Satisfactory Operation Point for Fuzzy Multiobjective Environmental/Economic Dispatch Problem A. A. Mousa 1, 2 , M. A. El-Shorbagy 1 1 Department of Basic Engineering Science, Faculty of Engineering, Menoufia University, Shebin El-Koum, Egypt 2 Department of Mathematics and Statistics, Faculty of Sciences, Taif University, Taif, Saudi Arabia Email address: a_mousa15@yahoo.com (A. A. Mousa), mohammed_shorbagy@yahoo.com (M. A. El-Shorbagy) To cite this article: A. A. Mousa, M. A. El-Shorbagy. Identifying a Satisfactory Operation Point for Fuzzy Multiobjective Environmental/Economic Dispatch Problem. American Journal of Mathematical and Computer Modelling. Vol. 1, No. 1, 2016, pp. 1-14. doi: 10.11648/j. ajmcm.20160101.11 Received: October 2, 2016; Accepted: October 19, 2016; Published: November 9, 2016 Abstract: In this paper, reference point based neural network (NN) algorithm is proposed for solving fuzzy multiobjective environmental/economic dispatch problem (FM-EEDP). There are instabilities in the global market, implications of global financial crisis and the rapid fluctuations of prices, for this reasons a fuzzy representation of environmental/economic dispatch problem (EEDP) has been investigated. Our approach has two characteristic features. Firstly, FM-EEDP has been defuzzified. Secondly reference point based NN algorithm is implemented in such a way that the decision-maker (DM) participate early in the optimization process instead of leaving him/her alone with the final choice. The target is to identify the Pareto-optimal region closest to the DM preference so as to achieve the pollution limitations which controlled using environmental protection rules and to carry out the maximum cost limitation. Moreover to help the DM to identify the best compromise solution from a finite set of alternatives, TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) method is implemented. On the basis of the application of the standard IEEE 30-bus 6-genrator test system, we can conclude that the proposed method can provide a sound optimal power flow by considering the multiobjective problem. Also, with a number of trade-off solutions in the region of interests, we proved that the DM able to make a better and more reliable decision. Keywords: Environmental/Economic Dispatch Problem, Neural Network, Reference Point, Fuzzy Numbers, TOPSIS Method 1. Introduction EEDP is one of the most important optimization problems from the view point of power system to derive optimal Environmental/Economic. Traditional economic dispatch to minimize the fuel cost is inadequate when environmental emissions are also to be included in the operation of power plants. With the increase in the environmental awareness and the passage of environmental regulations, the environmental constraints are having a significant impact on the operation of power systems. The purpose of EEDP is to figure out the optimal amount of the generated power for the fossil-based generating units in the system by minimizing the fuel cost and emission level simultaneously, subject to various equality and inequality constraints including the security measures of the power transmission/distribution. The instabilities in the global market, implications of global financial crisis and the rapid fluctuations of prices [1] are the main reasons to fuzzy representation of the multiobjective EEDP; where the input data involve many parameters whose possible values may be assigned by the experts. In practice, it is natural to consider that the possible values of these parameters as fuzzy numerical data which can be represented by means of fuzzy subsets of the real line known as fuzzy numbers. In this paper, an attempt is made to identify a satisfactory operation point for FM-EEDP. Based on Alpha concept, FM- EEDP is defuzzified at certain degree of α (α-cut level) [2-4]. Also, a combination between one of the preference based strategy and NN methodology to obtain a set of solutions near the reference points. Moreover, to help the DM to identify the best compromise solution from a finite set of alternatives, TOPSIS method is implemented. It is based upon simultaneous minimization of distance from an ideal point (IP) and maximization of distance from a nadir point (NP). Such procedures will provide the DM with a best compromise solution to achieve his/her requirements, so that