Tehnički vjesnik, Vol. 30 No. 5, 2023.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20221109072844
Spider Monkey Optimization Based Optimal Sizing of Battery Energy Storage for Micro-Grid
Jayashree S
; Department of Electrical & Electronics Engineering, SNS College of Technology, Coimbatore-641035, Tamil Nadu, India
Malarvizhi K
; Department of Electrical & Electronics Engineering, Kumaraguru College of Technology, Coimbatore-641049, Tamilnadu, India
Sažetak
The ever-increasing need for power in today's environment calls for a secure and effective energy supply network. Distributed renewable options such as Diesel Generator (DG), wind turbine (WT) and photovoltaic (PV) solar energy may be integrated inside a micro grid (MG) to supply electricity to customers in a sensible manner. In order to provide a more efficient and affordable source of electricity, the battery storage device is built into the micro grid. This article identifies the cost-based approach to calculate the optimum size of the Battery energy storage (BES) for MG operations. Some constraints, i.e., the power output of the Distributed Generators (DGs), the power and energy capacity of BES, the charging/discharge performance of BES, the working reserve and the fulfilment of the load requirement, should also be considered. In this article the Spider Monkey (SM) algorithm is a modern evolutionary technology that is used to build correction policies and to execute less costly dispatch. Four different cases have been studied. The results are compared with recently developed Fire Fly (FF) algorithm to corroborate the effectiveness of the proposed algorithm. The results show that the proposed algorithm has low power loss and the operating cost of the proposed SM technique is 0.0129% less than existing FF algorithm based micro-grid system. Here, IEEE 33 bus system performed to prove the effectiveness of the proposed SM algorithm over the FF algorithm.
Ključne riječi
battery energy storage; diesel generator; micro grid; optimal sizing; renewable energy; spider monkey algorithm
Hrčak ID:
307744
URI
Datum izdavanja:
31.8.2023.
Posjeta: 577 *