Please use this identifier to cite or link to this item: https://dspace.upt.ro/xmlui/handle/123456789/6576
Title: Environmentally sustainable economic dispatch using grey wolves optimization [articol]
Authors: Kadali, Kalyan Sagar
Loganathan, Rajaji
Veerasamy, Moorthy
Jawalker, Viswanatharao
Subjects: Nonlinear operating model
Biobjective optimization
Non-convex operating model
Economic-environmental impacts
Gray wolves optimization
Interpolated price penalty factor
Issue Date: 2020
Publisher: Timișoara : Editura Politehnica
Citation: Kadali, Kalyan Sagar; Loganathan, Rajaji; Veerasamy, Moorthy; Jawalker, Viswanatharao. Environmentally sustainable economic dispatch using grey wolves optimization. Timişoara: Editura Politehnica, 2020.
Series/Report no.: Journal of Electrical Engineering;Vol 20 No 4
Abstract: This paper delineates a computational framework to ascertain optimum thermal generation schedule using newfangled grey wolves optimization (GWO) technique corresponding to environmentally sustainable, economic operation. This scheduling problem is devised as a biobjective optimization and linear interpolated price penalty model is developed based on simple analytical geometry equations which blends two non-commensurable objectives perfectly. In order to obtain high-quality solutions within lesser executing time, the algorithm parameters are nicely replaced with system parameters that carry out global and local search process in the feasible region collaboratively. Further, an appropriate constraint handling mechanism is suitably incorporated in the algorithm that intern produces a stable convergence characteristic. The effectiveness of the proposed approach is illustrated on six unit thermal systems with due consideration of transmission line loss and valve point loading effect. The desired GWO technique reports a new feasible solution for quadratic and non-convex thermal operating model which is compared with the solution that has evolved earlier and the comparison shows that the GWO technique has outstripped other algorithms effectively.
URI: https://dspace.upt.ro/xmlui/handle/123456789/6576
ISSN: 1582-4594
Appears in Collections:Articole științifice/Scientific articles

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