Quantum-Inspired Computational Intelligence for Economic Emission Dispatch Problem-Reference-Cited by-同舟云学术

Quantum-Inspired Computational Intelligence for Economic Emission Dispatch Problem

Published:2020 Issue: Volume: Page:634-657
ISSN:
Container-title:Foreign Direct Investments
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Author:

Mahdi Fahad Parvez¹,Vasant Pandian²^ORCID,Kallimani Vish¹,Abdullah-Al-Wadud M.³,Watada Junzo¹

Affiliation:

1. Universiti Teknologi Petronas, Malaysia

2. University of Technology Petronas, Malaysia

3. King Saud University, Saudi Arabia

Abstract

Economic emission dispatch (EED) problems are one of the most crucial problems in power systems. Growing energy demand, limited reserves of fossil fuel and global warming make this topic into the center of discussion and research. In this chapter, we will discuss the use and scope of different quantum inspired computational intelligence (QCI) methods for solving EED problems. We will evaluate each previously used QCI methods for EED problem and discuss their superiority and credibility against other methods. We will also discuss the potentiality of using other quantum inspired CI methods like quantum bat algorithm (QBA), quantum cuckoo search (QCS), and quantum teaching and learning based optimization (QTLBO) technique for further development in this area.

Publisher

IGI Global

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