인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
논문을 무제한 열람 이용할 수 있어요.
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
ABSTRACT 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.
#Whale
#Longevity
#Stability (learning theory)
#Battery (electricity)
#Optimization algorithm
#Computer science
#Energy (signal processing)
#Algorithm
#Control (management)
#Control theory (sociology)
#Mathematical optimization
#Mathematics
#Biology
#Artificial intelligence
#Medicine
#Statistics
#Fishery
#Gerontology
#Machine learning
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