Solving Non-Smooth Optimal Power Flow Problems Using a Developed Grey Wolf Optimizer

Mostafa Abdo, Salah Kamel, Mohamed Ebeed, Juan Yu and Francisco Jurado
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Mostafa Abdo: Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt
Salah Kamel: Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt
Mohamed Ebeed: Department of Electrical Engineering, Faculty of Engineering, Sohag University, Sohag 82524, Egypt
Juan Yu: State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing 400030, China
Francisco Jurado: Department of Electrical Engineering, University of Jaén, EPS Linares, 23700 Jaén, Spain

Energies, 2018, vol. 11, issue 7, 1-16

Abstract: The optimal power flow (OPF) problem is a non-linear and non-smooth optimization problem. OPF problem is a complicated optimization problem, especially when considering the system constraints. This paper proposes a new enhanced version for the grey wolf optimization technique called Developed Grey Wolf Optimizer (DGWO) to solve the optimal power flow (OPF) problem by an efficient way. Although the GWO is an efficient technique, it may be prone to stagnate at local optima for some cases due to the insufficient diversity of wolves, hence the DGWO algorithm is proposed for improving the search capabilities of this optimizer. The DGWO is based on enhancing the exploration process by applying a random mutation to increase the diversity of population, while an exploitation process is enhanced by updating the position of populations in spiral path around the best solution. An adaptive operator is employed in DGWO to find a balance between the exploration and exploitation phases during the iterative process. The considered objective functions are quadratic fuel cost minimization, piecewise quadratic cost minimization, and quadratic fuel cost minimization considering the valve point effect. The DGWO is validated using the standard IEEE 30-bus test system. The obtained results showed the effectiveness and superiority of DGWO for solving the OPF problem compared with the other well-known meta-heuristic techniques.

Keywords: power system optimization; optimal power flow; developed grew wolf optimizer (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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