Title: An application of grey wolf optimisation for combined heat and power dispatch

Authors: N. Jayakumar; S. Subramanian; E.B. Elanchezhian; S. Ganesan

Addresses: Department of Electrical Engineering, Faculty of Engineering and Technology, Annamalai University, Annamalainagar, Chidambaram-608 002, Tamilnadu, India. ' Department of Electrical Engineering, Faculty of Engineering and Technology, Annamalai University, Annamalainagar, Chidambaram-608 002, Tamilnadu, India. ' Department of Electrical Engineering, Faculty of Engineering and Technology, Annamalai University, Annamalainagar, Chidambaram-608 002, Tamilnadu, India. ' Department of Electrical Engineering, Faculty of Engineering and Technology, Annamalai University, Annamalai Nagar, Chidambaram-608 002, Tamil Nadu, India

Abstract: The purpose of this paper is to obtain the best feasible solution for combined heat and power dispatch (CHPD) problems. Being inspired by the hunting and searching behaviours of grey wolves, a swarm intelligence algorithm, grey wolf optimisation (GWO) has been developed and is used as an optimisation tool for the chosen problem. In addition to the nonlinear and non-convex operational characteristics of generating units, the practical operational constraints such as feasible operating regions of cogenerators, prohibited operating zones of thermal generators are considered. The GWO is implemented in the standard test systems for economic and combined economic emission dispatch operations. The obtained results are higher, feasible than or as good as the best known solutions by state-of-the-art algorithms reported in the literature. It is evident that the GWO attains a high quality solution to CHPD problems.

Keywords: cogeneration systems; grey wolf optimisation; GWO; valve-point effects; prohibited operating zones; POZ; emissions; combined heat and power; CHP dispatch; swarm intelligence.

DOI: 10.1504/IJETP.2015.069821

International Journal of Energy Technology and Policy, 2015 Vol.11 No.2, pp.183 - 206

Available online: 12 Jun 2015 *

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