Grey Wolf Optimizer for Optimal Sizing and Siting of Energy Storage System in Electric Distribution Network. Issue 6 (3rd April 2017)

• Record Type: Journal Article
• Authors: Fathy, Ahmed; Abdelaziz, Almoataz Y.
• Is Part Of: Electric power components and systems. Volume 45:Issue 6(2017)
• Page Start: 601
• Page End: 614
• Publication Date: 2017-04-03
• Subjects: energy storage system -- Grey Wolf Optimizer -- distribution network -- ESS optimal allocation and sizing; Electric machinery -- Periodicals; 621.3104205
• DOI: 10.1080/15325008.2017.1292567
• Languages: English
• ISSNs: 1532-5008

Abstract

Abstract: One of the most important issues that must be taken into consideration during the operation of distribution network is improving the network reliability. This objective can be achieved by connecting energy storage systems (ESSs) to the network; the correct size and location of these ESSs cause enhancing of the system reliability. This paper proposes an efficient methodology based on the Grey Wolf Optimizer (GWO) to determine the optimal size and location of ESSs in a distribution network so as to minimize the total annual cost of system comprising the cost of energy not supplied (ENS), the ESSs' investment costs and operating costs. The proposed methodology is applied to two radial distribution systems, a 30-bus, 11-kV system and a 69-bus, 12.6-kV system. The results obtained via the proposed GWO are compared to those obtained via classical approaches, dynamic programming (DP), and meta-heuristic algorithms (PSO). In the case of a 30-bus network, the total cost is saved by 14.12% from the base case, network without ESSs; and, in the case of a 69-bus system, the cost is saved by 39.03%. Additionally, particle swarm optimization (PSO) and artificial bee colony (ABC) algorithms are programmed and their results are compared with those obtained via the proposed GWO. The obtained locations and sizes of ESSs encourage the usage of the proposed methodology due to its ease and efficiency in solving the optimization problem under study.