Open AccessCombined Economic and Emission Dispatch Solution using Artificial Bee Colony Algorithm with Fuzzy Approach
Author(s) -
Mohd Noor Abdullah,
Guichang Sim,
Azwan Iskandar Azmi,
S H. Shamsudin
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.15.17405
Subject(s) - mathematical optimization , economic dispatch , electric power system , computer science , artificial bee colony algorithm , benchmark (surveying) , minification , electricity generation , fuzzy logic , convergence (economics) , power (physics) , mathematics , artificial intelligence , economics , physics , geodesy , quantum mechanics , economic growth , geography
The cost and emission minimization in power system operation become important issue in power dispatch due to increase of environmental pollution and fossil fuel price. Therefore, combined economic and emission dispatch (CEED) must be considered in generation scheduling in order to provide balanced solution for optimal cost and emissions level of power generation. In this paper, an Artificial Bee Colony (ABC) algorithm with Fuzzy best compromise solution is proposed to determine the optimal cost and emission level by converting the multi-objective (cost and emission) into single objective problem using weighted sum method approach. The best compromise solution among Pareto front solution was determined by fuzzy approach. The effectiveness of ABC algorithm has been validated in terms of the best solution, convergence behaviour and consistency for power system benchmark such as IEEE 30-bus 6-unit system and 10-unit system. The comparison study shows that ABC algorithm capable to obtain a better performance of minimizing the cost and emission level in power generation.