PARTICLE SWARM OPTIMIZATION FOR OPTIMAL SIZING OF BATTERY ENERGY STORAGE SYSTEM IN MICROGRID
DESIGN DETAILS
The main challenge in integrating a Battery Energy Storage System (BESS) into a microgrid is to evaluate an optimum size of BESS to prevent the microgrid from instability and system collapse. The installation of BESS at a random size or non-optimum size can increase in cost, system losses and larger BESS capacity. This design is to solve the sizing and allocation of BESS placement via particle swarm optimization (PSO) to reduce power loss. The importance of the operating condition is represented by the benefit regarding the sizing and location of power grids. Consequently, the power supporting energy demand from each load type of the power grid with the optimal condition of the BESS should be managed and provided. The energy consumed by the power grid was defined in terms of each load supplied to the BESS energy support. The design tested using Matlab 2020a/2021b version to calculate the capacity, sizes, and cost of the battery along with Reliability indices (LOLE, LOEE and LPSP).
OBJECTIVE FUNCTION
The purpose of the objective function f_1 is to evaluate an optimal size of BESS to prevent the microgrid from instability and system collapse after the loss of the utility grid (e.g., blackout or disasters).
Minimize f_1=min(P_BESS)
REFERENCES
Reference Paper-1: Optimization of a battery energy storage system using particle swarm optimization for stand-alone microgrids
Author’s Name: Thongchart Kerdphol, Kiyotaka Fuji, Yasunori Mitani, Masayuki Watanabe, Yaser Qudaih
Source: Elsevier
Year: 2014
Reference Paper-2: Optimal sizing of Battery Energy Storage System in Microgrid by using Particle Swarm Optimization Technique
Author’s Name: Rajesh Kamble, Gauri Karve, Amarnath Chakradeo, Geetanjali Vaidya1
Source: Journal of Integrated Science & Technology
Year: 2018
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