虚拟发电厂
自动发电控制
方案(数学)
自动频率控制
频率偏差
控制工程
功率(物理)
计算机科学
火力发电站
工程类
控制(管理)
控制理论(社会学)
分布式发电
电力系统
可再生能源
电气工程
物理
数学分析
人工智能
量子力学
数学
作者
Arman Oshnoei,Morteza Kheradmandi,Frede Blaabjerg,Nikos D. Hatziargyriou,S. M. Muyeen,Josep M. Guerrero
出处
期刊:Applied Energy
[Elsevier]
日期:2022-11-01
卷期号:325: 119734-119734
被引量:14
标识
DOI:10.1016/j.apenergy.2022.119734
摘要
This paper proposes a coordinated control strategy for a Virtual Power Plant (VPP) contribution to load frequency control. The considered VPP comprises distributed Battery Energy Storage Systems (BESSs) and Heat Pump Water Heaters (HPWHs). The frequency regulation signal is distributed between thermal generator and the VPP based on distribution coefficients which are calculated through conducting a multi-objective optimization problem. The optimization framework incorporates the dynamic regulation performance as well as the total regulation cost. A fuzzy strategy is adopted to obtain the final solution according to user-defined conditions. The regulation signal of VPP is dispatched based on the speed and the available power capacity of VPP components. The performance of the proposed coordination scheme is compared to the scheme without coordination and that with no involvement of VPP in frequency regulation. The regulation performance is also evaluated for varying time delays expected in the communication channels. An approach based on brain emotional learning is developed to coordinate the VPP and conventional generation unit to avoid large frequency deviations caused by the communication delays. Case studies are conducted on a multi-area power system in MATLAB/Simulink environment, and the results are verified by the OPAL-RT real-time simulator.
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