Hierarchical Energy Management of Hybrid Battery Storage Systems for PV Capacity Firming and Spot Market Trading Considering Degradation Costs

被引:2
作者
Wicke, Margrit [1 ]
Bocklisch, Thilo [1 ]
机构
[1] Tech Univ Dresden, Chair Energy Storage Syst, D-01069 Dresden, Germany
关键词
Batteries; Energy storage; Aging; Lithium-ion batteries; Costs; Energy management; State of charge; Capacity planning; Hybrid power systems; Capacity firming; degradation costs; energy arbitrage; hierarchical control; hybrid energy storage system (HESS); lithium-ion battery aging; mixed-integer linear programming (MILP); multi-use; piecewise affine (PWA) approximation; photovoltaic (PV) power integration; CYCLE LIFE; OPTIMIZATION; PERFORMANCE; FRAMEWORK; MODELS;
D O I
10.1109/ACCESS.2024.3387748
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Lithium-ion batteries are currently one of the key technologies for a sustainable energy transition. However, they have a limited calendar and cycle lifetime, which are directly affected by operating conditions. Therefore, our goal is to maximize the benefits of a battery storage over its entire lifespan. Stacking multiple services (multi-use) can increase the utilization of battery storage, whereas coupling different storage technologies with complementary characteristics (hybrid energy storage systems) adds a degree of freedom for efficient and degradation-aware operation. To exploit these technological and economic advantages, we develop an energy management concept and demonstrate it in the application example of a grid-connected photovoltaic plant with hybrid battery storage. The multi-use application consists of capacity firming, participation in the electricity spot market, and peak shaving. To address the different temporal scales of the battery storage tasks, we propose a hierarchical energy management with two levels. The model predictive upper level energy management optimizes the grid power considering the time-varying electricity prices and marginal costs of battery storage operation. This multi-objective optimization problem is solved using a mixed-integer linear program with two-dimensional piecewise linearization of conversion losses and battery degradation costs. The strategy-based lower level energy management allocates power in real time to meet the grid power and ramp-rate requirements despite model and forecast errors. Extensive simulations demonstrate the advantages of the proposed approach owing to a better compliance with grid power requirements, lower conversion losses, and significantly higher benefits of the battery storage system over its lifetime.
引用
收藏
页码:52669 / 52686
页数:18
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