Learning-based Optimization of Active Distribution System Dispatch in Industrial Park Considering the Peak Operation Demand of Power Grid

被引：0

作者：

Tang H. ^{[1
]}

Liu C. ^{[1
]}

Yang M. ^{[2
]}

Tang B.-Q. ^{[3
]}

Xu D. ^{[4
]}

Lv K. ^{[1
]}

机构：

[1] Electrical Engineering and Automation, Hefei University of Technology, Hefei

[2] Electric Power Research Institute of State Grid Jiangsu Electric Power Company, Nanjing

[3] China Electric Power Research Institute (Nanjing), Nanjing

[4] Editorial China Electric Power Research Institute (Beijing), Beijing

来源：

Zidonghua Xuebao/Acta Automatica Sinica | 2021年 / 47卷 / 10期

基金：

国家重点研发计划;

关键词：

Active distribution system; Multiple types of flexible load; Peak operation; Reinforcement learning; Vanadium redox battery (VRB) energy storage system;

D O I：

10.16383/j.aas.c190079

中图分类号：

学科分类号：

摘要：

The dynamic economic dispatch problem of the active distribution system combined of photovoltaic (PV), vanadium redox battery (VRB) energy storage device and multiple types of flexible load in industrial parks with uncertain renewable sources and demands is focused in this paper. First, the random dynamic variations of photovoltaic, multiple loads demand and peak operation demand are described as continuous Markov processes, and the VRB energy storage system is modeled considering its charge-discharge characteristics. Then, decision epoch, outputs level of photovoltaic, multiple load demands level, peak operation demands level and state of charge (SOC) level of VRB are defined as states of the system, the adjustment level of VRB and multiple types of flexible load are set as the actions. Based on relevant restrictions including the power balance constraint, the dynamic optimal dispatch problem for the system was described as a stochastic dynamic programming model, which aims to meet the peak operation demand of power grid and realize economic operation of the system. Finally, a reinforcement learning method is adopted to obtain the optimal policy. Simulation results show that the operational efficiency is significantly enhanced and the peak operation demand of power grid is partly satisfied by the optimal policy. Copyright © 2021 Acta Automatica Sinica. All rights reserved.

引用

页码：2449 / 2463

页数：14

共 34 条

[21]

Jiang Qi, Lu Gai-Xiang, Tang Hao, Tan Qi, Access control of demand requests with response time flexibility in smart grids, Control and Decision, 7, pp. 1311-1315, (2014)

[22]

Li Yi-Jin, Tang Hao, Lv Kai, Guo Xiao-Rui, Xu Dan, Modeling and learning-based optimization of the energy dispatch for a combined cooling, heat and power microgrid system with uncertain sources and loads, Control Theory & Applications, 1, (2018)

[23]

Li Y Z, Niu J C., Forecast of Power Generation for Grid-Connected Photovoltaic System Based on Markov Chain, IEEE Power and Energy Engineering Conference, pp. 1729-1733, (2009)

[24]

Liang H, Tamang A K, Zhuang W, Et al., Stochastic Information Management in Smart Grid, IEEE Communications Surveys & Tutorials, 16, 3, pp. 1746-1770, (2014)

[25]

Hong Y Y, Lian R C., Optimal Sizing of Hybrid Wind/PV/Diesel Generation in a Stand-Alone Power System Using Markov-Based Genetic Algorithm, IEEE Transactions on Power Delivery, 27, 2, pp. 640-647, (2014)

[26]

Breipohl A M, Lee F N, Zhai D, Et al., A Gauss-Markov load model for application in risk evaluation and production simulation, IEEE Transactions on Power Systems, 7, 4, pp. 1493-1499, (1992)

[27]

Zhai D, Breipohl A M, Lee F N, Et al., The effect of load uncertainty on unit commitment risk, IEEE Transactions on Power Systems, 9, 1, pp. 510-517, (1994)

[28]

CHAHWAN J, ABBEY C, JOOS G., VRB modelling for the study of output terminal voltages, internal losses and performance, IEEE Electrical Power Conference, pp. 387-392, (2007)

[29]

Qiu Ya, Li Xin, Wei Da, Yu Ling, Flexible charge-discharge control of vanadium redox battery, Energy Storage Science and Technology, 6, 1, pp. 78-84, (2017)

[30]

Shen Yu-Ming, Hu Bo, Xie Kai-Gui, Xiang Bin, Wan Ling-Yun, Optimal economic operation of isolated microgrid considering battery life loss, Power System Technology, 38, 9, pp. 2371-2378, (2014)

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