Optimized Control of Hybrid Energy Storage Systems Using Whale Optimization Algorithm for Enhanced Battery Longevity and Stability in Microgrids

被引:0
作者
Siddiqui, Nouman Alam [1 ]
Tahir, Hira [2 ]
Akram, Muhammad [1 ]
Manzoor, Habib Ullah [3 ]
机构
[1] UET Lahore, Elect Engn Dept, Lahore, Pakistan
[2] King Fahd Univ Petr & Minerals, Interdisciplinary Res Ctr Smart Mobil & Logist, Dhahran, Saudi Arabia
[3] Univ Glasgow, James Watt Sch Engn, Glasgow, Scotland
关键词
battery; energy storage; optimization; smart grid; MANAGEMENT-SYSTEM;
D O I
10.1002/eng2.70199
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The target of achieving net-zero emissions by 2050 requires integrating a significant share of renewable energy. However, this integration can cause instability in microgrid operations. Hybrid energy storage systems (HESS), consisting of battery energy storage systems (BESS) and supercapacitors, address these challenges but necessitate complex control strategies. Traditional frequency-based methods (FBM) enhance HESS performance but do not guarantee continuous operation and may lead to BESS degradation. This article proposes an optimized FBM control approach using the whale optimization algorithm (WOA) to improve HESS operation. The method optimizes two key variables: current sharing coefficients and the smoothing constant, enabling continuous HESS functionality. The proposed FBM-WOA reduces high-frequency current stress on BESS, minimizes BESS usage, and ensures supercapacitor state-of-charge levels remain within safe limits. The proposed approach achieves the lowest BESS life loss and voltage fluctuations in both test load and microgrid load cases. It decreases BESS life loss by 11.59% and 0.25% compared to rule-based (FB-RB) and current sharing coefficient (FB-COEFF) methods, respectively, for test load cases. Similarly, it reduces average BESS life loss by 1.45% and 2.35% compared to FB-RB and FB-COEFF methods for real load cases over five different days.
引用
收藏
页数:15
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