Placement Optimization for Renewable Energy Sources: Ontology, Tools, and Wake Models

Khan, M.Y. and Ali, M. and Qaisar, S. and Naeem, M. and Chrysostomou, C. and Iqbal, M. (2020) Placement Optimization for Renewable Energy Sources: Ontology, Tools, and Wake Models. IEEE Access, 8. pp. 72781-72800. ISSN 21693536

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Abstract

Due to intermittent nature of renewable energy sources (RESs) and their strong dependence on various environmental factors, it is imperative to carefully deploy these sources. A survey of recent works published in the area of optimal deployment of RESs is presented in this article. The existing works are categorized according to the type of energy source, objective function and model of operation. An optimal mix of hybrid-RESs along with energy storage system (ESS) is presented as solution to overcome the randomness and inconstancy of a single RES such as wind or solar power. We outline mathematical formulations for different objective functions, i.e., minimization of cost, maximization of power generation, maximization of the average cosine efficiency and minimization of the distribution losses. We present different wake models and simulation tools being used for the wind form layout optimization. These simulation tools are used to grade particular RESs according to technical and financial feasibility. This review paper depicts multifaceted coverage of the subject to provide the readers with state of the art developments in the area and can serve as a foundation for further research in the area. In addition, it can be used to find optimal mix of RESs for particular geographical area to satisfy the energy demands of that particular area. © 2013 IEEE.

Item Type: Article
Additional Information: cited By 7
Uncontrolled Keywords: Functions; Natural resources; Solar energy; Wakes, Energy storage systems; Environmental factors; Mathematical formulation; Minimization of costs; Objective functions; Placement optimization; Renewable energy source; Strong dependences, Electromagnetic wave emission
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 10 Nov 2023 03:28
Last Modified: 10 Nov 2023 03:28
URI: https://khub.utp.edu.my/scholars/id/eprint/13890

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