Multi-photovoltaic Coordinated Control Strategy in DC Distribution Network Based on Discrete Consensus Algorithm

被引:0
|
作者
Tang M. [1 ]
Qu X. [1 ]
Yao R. [1 ]
Zhang Y. [1 ]
Chen W. [1 ]
Jia K. [2 ]
机构
[1] School of Electrical Engineering, Southeast University, Nanjing
[2] State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing
来源
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2020年 / 44卷 / 24期
基金
国家重点研发计划;
关键词
Coordinated control; DC distribution network; Discrete consensus algorithm; Distributed photovoltaic (PV); Power deviation; Renewable energy;
D O I
10.7500/AEPS20200513004
中图分类号
学科分类号
摘要
Aiming at the power fluctuation of multi-photovoltaic (multi-PV) DC distribution network systems in different application scenarios, this paper proposes a distributed multi-PV coordinated control strategy based on the discrete consensus algorithm. First, the information of the power deviation and the operation modes can be exchanged between neighbor PV controllers. The average value of power deviation and operation modes can be obtained through the discrete consensus algorithm. Then, the operation mode instructions and power reference instructions can be updated and the power deviation is balanced by utilizing power complementary between PVs. PVs can operate in the maximum power tracking mode or constant power mode adaptively. In such a way, power balance will be guaranteed even if the solar irradiance and rated capacity of PVs are uneven. Finally, the simulation results verify the effectiveness of the proposed control strategy. © 2020 Automation of Electric Power Systems Press.
引用
收藏
页码:89 / 95
页数:6
相关论文
共 25 条
  • [1] CHEN Pengwei, XIAO Xiangning, TAO Shun, Discussion on power quality problems for DC microgrid, Automation of Electric Power Systems, 40, 10, pp. 148-158, (2016)
  • [2] ZHU Y, ZHUO F, SHI H., Power management strategy research for a photovoltaic-hybrid energy storage system, 2013 IEEE ECCE Asia Downunder, (2013)
  • [3] OMRAN W A, KAZERANI M, SALAMA M A., Investigation of methods for reduction of power fluctuations generated from large grid-connected photovoltaic systems, IEEE Transactions on Energy Conversion, 26, 1, pp. 318-327, (2011)
  • [4] ZHANG Bo, TANG Wei, CAI Yongxiang, Et al., Distributed control strategy of residential photovoltaic inverter and energy storage based on consensus algorithm, Automation of Electric Power Systems, 44, 2, pp. 86-96, (2020)
  • [5] MAO Meiqin, LIU Yunhui, ZHANG Liuchen, Et al., Optimal configuration of generalized energy storage in distribution network with high-penetration renewable energy, Automation of Electric Power Systems, 43, 8, pp. 77-88, (2019)
  • [6] FANG Zhi, SONG Shaojian, LIN Yuzhang, Et al., State estimation for active distribution systems incorporating photovoltaic plant and battery energy storage system, Automation of Electric Power Systems, 43, 13, pp. 71-83, (2019)
  • [7] CHE Quanhui, WU Yaowu, ZHU Zhigang, Et al., Carbon trading based optimal scheduling of hybrid energy storage system in power system with large-scale photovoltaic power generation, Automation of Electric Power Systems, 43, 3, pp. 76-83, (2019)
  • [8] YANG Qiufan, HUANG Yubin, SHI Mengxuan, Et al., Consensus based distributed control for multiple PV-battery storage units in a DC microgrid, Proceedings of the CSEE, 40, 12, pp. 3919-3928, (2020)
  • [9] YAN Gangui, ZHU Wei, DUAN Shuangming, Et al., Power control strategy of energy storage system considering consistency of lead carbon battery pack, Automation of Electric Power Systems, 44, 11, pp. 61-74, (2020)
  • [10] YAN Gangui, LI Hongbo, DUAN Shuangming, Et al., Optimal operation control strategy of microgrid based on double-lead carbon battery energy storage system, Automation of Electric Power Systems, 43, 13, pp. 46-59, (2019)