Optimal reactive power resources sizing for power system operations enhancement based on improved grey wolf optimiser. Issue 14 (22nd May 2018)

• Record Type: Journal Article
• Authors: Taha, Ibrahim B. M.; Elattar, Ehab E.
• Is Part Of: IET generation, transmission & distribution. Volume 12:Issue 14(2018)
• Page Start: 3421
• Page End: 3434
• Publication Date: 2018-05-22
• Subjects: reactive power -- concave programming -- minimisation -- nonlinear programming -- power systems; power system operation enhancement -- improved grey wolf optimiser -- exploration–exploitation balance -- weighted distance strategy -- optimal reactive power resource sizing problem -- nonconvex optimisation problem -- nonlinear optimisation problem -- objective functions -- generating cost minimisation -- transmission power loss minimisation -- voltage profile improvement -- IGWO method -- standard IEEE systems -- contingency conditions; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2018.0053
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : In recent years, optimal sizing and location of reactive power resources are drawing much attention to help the operators of the utilities to enhance the power system operations. Therefore, this work presents a new version of grey wolf optimiser (GWO) to solve the problem of optimal reactive power resources sizing for power system operation enhancement. The proposed method which called improved grey wolf optimiser (IGWO) can be derived by modifying the exploration–exploitation balance in the conventional GWO to enhance its rate of convergence. Also, the weighted distance strategy is employed in the proposed IGWO to overcome the drawback of the conventional GWO. Optimal reactive power resources sizing problem is non‐linear and non‐convex optimisation problem. To solve this problem, different objective functions are used. These objective functions are minimisation of generating cost, minimisation of transmission power loss and voltage profile improvement. The validity and superiority of the proposed IGWO method are tested using three standard IEEE systems for normal and contingency conditions. Then the results are compared with those obtained from other recently published algorithms. The simulation results show that the proposed IGWO method is more accurate and efficient than other recently published algorithms.