Deep reinforcement learning-based optimal data-driven control of battery energy storage for power system frequency support

被引：14
|
作者：
Yan, Ziming [1 ]
Xu, Yan [1 ]
Wang, Yu [1 ]
Feng, Xue [2 ]
机构：
[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore, Singapore
[2] Singapore Inst Technol, Singapore, Singapore
来源：
IET GENERATION TRANSMISSION & DISTRIBUTION | 2020年 / 14卷 / 25期
关键词：
power generation control; optimisation; frequency control; secondary cells; battery storage plants; optimal control; learning (artificial intelligence); power engineering computing; battery lifetime degradation; battery cycle aging cost; generation cost; total operational cost; power system frequency support; BESS controller performance; optimal BESS control method; three-area power system; optimal data-driven control; battery energy storage system; power system frequency control; battery aging; intensive charge-discharge cycles; high-operating costs; deep reinforcement learning; data-driven approach; real-time power imbalance mitigation; unscheduled interchange price; actor-critic model; ION BATTERIES; DEGRADATION; COST;
D O I：
10.1049/iet-gtd.2020.0884
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A battery energy storage system (BESS) is an effective solution to mitigate real-time power imbalance by participating in power system frequency control. However, battery aging resulted from intensive charge-discharge cycles will inevitably lead to lifetime degradation, which eventually incurs high-operating costs. This study proposes a deep reinforcement learning-based data-driven approach for optimal control of BESS for frequency support considering the battery lifetime degradation. A cost model considering battery cycle aging cost, unscheduled interchange price, and generation cost is proposed to estimate the total operational cost of BESS for power system frequency support, and an actor-critic model is designed for optimising the BESS controller performance. The effectiveness of the proposed optimal BESS control method is verified in a three-area power system.
引用
收藏
页码：6071 / 6078
页数：8
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