Application of Multi-Layered Perceptron Neural network (MLPNN) to Combined Economic and Emission Dispatch
J. Hamidi
Javad Hamidi, Electrical Engineering Department, Islamic Azad University, Sarakhs Branch, Sarakhs, Iran.
Manuscript received on December 05, 2011. | Revised Manuscript received on December 18, 2011. | Manuscript published on January 05, 2012. | PP: 242-246 | Volume-1 Issue-6, January 2012. | Retrieval Number: F0310111611/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper presents a multi-layered perceptron neural network (MLPNN) method to solve the combined economic and emission dispatch (CEED) problem. The harmful ecological effects caused by the emission of particulate and gaseous pollutants like sulfur dioxide (SO2 ) and oxides of nitrogen ( NOx ) can be reduced by adequate distribution of load between the plants of a power system. However, this leads to a noticeable increase in the operating cost of the plants. This paper presents the (MLPNN) method applied for the successful operation of the power system subject to economical and environmental constraints. The proposed MLP NN method is tested for a three plant thermal power system and the results are compared with the solutions obtained from the classical lambda iterative technique and simple genetic algorithm (SGA) refined genetic algorithm (RGA) method.
Keywords: Economic dispatch, Emission dispatch, the multi-layered perceptron neural network.