A new modified artificial bee colony algorithm for the economic dispatch problem. (1st January 2015)

• Record Type: Journal Article
• Authors: Secui, Dinu Calin
• Is Part Of: Energy conversion and management. Volume 89(2015)
• Page Start: 43
• Page End: 62
• Publication Date: 2015-01-01
• Subjects: Economic/emission dispatch -- Artificial bee colony algorithm -- Chaotic maps -- Valve-point effects -- Transmission losses; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2014.09.034
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: A new modified ABC algorithm (MABC) is proposed to solve the EcD/EmD problem. Valve-point effects, ramp-rate limits, POZ, transmission losses were considered. The algorithm is tested on four systems having 6, 13, 40 and 52 thermal units. MABC algorithm outperforms several optimization techniques. Abstract: In this paper a new modified artificial bee colony algorithm (MABC) is proposed to solve the economic dispatch problem by taking into account the valve-point effects, the emission pollutions and various operating constraints of the generating units. The MABC algorithm introduces a new relation to update the solutions within the search space, in order to increase the algorithm ability to avoid premature convergence and to find stable and high quality solutions. Moreover, to strengthen the MABC algorithm performance, it is endowed with a chaotic sequence generated by both a cat map and a logistic map. The MABC algorithm behavior is investigated for several combinations resulting from three generating modalities of the chaotic sequences and two selection schemes of the solutions. The performance of the MABC variants is tested on four systems having six units, thirteen units, forty units and fifty-two thermal generating units. The comparison of the results shows that the MABC variants have a better performance than the classical ABC algorithm and other optimization techniques.