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Multi-objective optimization for voltage and frequency control of smart grids based on controllable loads

2021-06-03

文章导读

促进分布式电源接入是能源互联网建设的规划重点之一。近年来分布式电源不断接入电网，其输出功率的不确定性严重影响了系统的频率和电压水平。与此同时，电网用户侧智能终端设备数量逐年增加，各节点的功率控制能力得到明显提高。因此，为使系统频率和电压幅值保持在额定值附近，本文提出了一种基于可控负荷的电压频率控制多目标优化模型。为了克服传统多目标求解方法主观性强的缺点，将所提多目标优化问题转化为博弈问题，并根据监测到的态势数据以及电压、频率对节点有功、无功功率改变量的敏感度分析，对优化变量进行层次聚类构建策略空间。

Multi-objective optimization for voltage and frequency control of smart grids based on controllable loads

基于可控负荷的智能电网电压频率多目标优化控制

Yaxin Wang, Donglian Qi, Jianliang Zhang

（College of Electrical Engineering, Zhejiang University, Hangzhou 310027, P.R. China）

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Abstract

The output uncertainty of high-proportion distributed power generation severely affects the system voltage and frequency. Simultaneously, controllable loads have also annually increased, which markedly improve the capability for nodal-power control. To maintain the system frequency and voltage magnitude around rated values, a new multi-objective optimization model for both voltage and frequency control is proposed. Moreover, a great similarity between the multi- objective optimization and game problems appears. To reduce the strong subjectivity of the traditional methods, the idea and method of the game theory are introduced into the solution. According to the present situational data and analysis of the voltage and frequency sensitivities to nodal-power variations, the design variables involved in the voltage and frequency control are classified into two strategy spaces for players using hierarchical clustering. Finally, the effectiveness and rationality of the proposed control are verified in MATLAB.

Keywords

Multi-objective optimization, Voltage control, Frequency control, Power flow, Controllable loads, Game theory.

Fig.1 Generator active power–frequency characteristic

Fig.2 Generator reactive power–voltage characteristic

Fig.3 Improved IEEE33 node distribution network

Fig.4Cluster tree of the design variables

Fig.5 Optimization process of the voltage index in the final iteration

Fig.6 Optimization process of the frequency deviation in the final iteration

Fig.7 Nodal voltage of the system before and after the control

本文引文信息

Wang Y, Qi D, Zhang J J (2021) Multi-objective optimization for voltage and frequency control of smart grids based on controllable loads, 4(2): 136-144

王雅新，齐冬莲，张建良 (2021) 基于可控负荷的智能电网电压频率多目标优化控制. 全球能源互联网（英文），4(2): 136-144

Biographies

Yaxin Wang

Yaxin Wang received B.E. degree at Zhengzhou University, Zhengzhou, China, in 2019. She is currently pursuing the Ph.D degree with the College of Electrical Engineering, Zhejiang University, Hangzhou, China. Her current research interests include voltage and frequency optimization control in smart grid, and game theory and distributed optimization, with applications to power systems.

Donglian Qi

Donglian Qi received the Ph.D. degree in control theory and control engineering from Zhejiang University, Hangzhou, China, in March 2002. Since then, she has been with the College of Electrical Engineering, Zhejiang University where she is currently a Professor. Her research interests include the basic theory and application of cyber physical power system (CPPS), digital image processing, artificial intelligence, and electric operation and maintenance robots. She is an Editor for the Clean Energy, the IET Energy Conversion and Economics, and the Journal of Robotics, Networking and Artificial Life.

Jianliang Zhang

Jianliang Zhang received his Ph.D degree in control theory and control engineering from Zhejiang University, Hangzhou, China, in June 2014. Since then, he has been working with College of Electrical Engineering, Zhejiang University (ZJU). He was a visiting scholar at Hongkong Polytechnic University (PolyU) (2016-2017). His current research interests include distributed optimization, with applications to energy/ power systems, and cyber-physical security with application in smart grid, etc.

编辑：王闻昊王彦博

审核：王伟

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