基于储能系统的风电场功率控制研究

冯斐; 任远洋; 王德林

doi:10.16513/j.cnki.10-1427/tk.2017.02.003

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分布式能源 ›› 2017, Vol. 2 ›› Issue (2) : 20-24. DOI: 10.16513/j.cnki.10-1427/tk.2017.02.003

基于储能系统的风电场功率控制研究

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Wind Farm Power Control Based on Energy Storage System

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摘要

在分析储能系统的各物理模型的基础上，提出一种由数据流构建的适用于系统机电暂态计算的通用储能模型。通过调节储能系统充放电速率限制、储能容量等特性参数，模拟不同储能系统对平抑风电场输出功率波动的效果。利用Matlab/Simulink环境，将储能模型与风电场模型进行结合，以New England 10机39节点标准系统为例进行仿真；为优化储能系统的性能，利用粒子群(particle swarm optimization，PSO)算法对储能模块中的PI控制器参数进行寻优。最后，仿真结果验证了通用储能模型的有效性，该模型可为电力系统有功功率的稳定传输和动态稳定控制提供一定参考。

Abstract

Based on the analysis of various physical models of energy storage system, this paper proposes a universal energy storage model constructed from the data stream which is suitable for system electromechanical transient calculations. By adjusting the charging/discharging rate limit of energy storage system, storage capacity and other characteristic parameters, we simulate the impact of different energy storage systems on stabilizing wind farm output power fluctuation. In Matlab/Simulink environment, the energy storage model is in conjunction with that of the wind farm. Next, the simulation is performed using New England 10-machine 39-bus standard system. In order to optimize the performance of energy storage systems, we adopt particle swarm optimization (PSO) intelligent algorithm to optimize the PI controller parameters in energy storage module. Finally, the simulation results verify the validity of the universal energy storage model, which can provide some valuable reference for the stable transmission of active power and dynamic stability control in power system.

导出引用

冯斐, 任远洋, 王德林. 基于储能系统的风电场功率控制研究[J]. 分布式能源. 2017, 2(2): 20-24 https://doi.org/10.16513/j.cnki.10-1427/tk.2017.02.003

Fei FENG, Yuanyang REN, Delin WANG. Wind Farm Power Control Based on Energy Storage System[J]. Distributed Energy Resources. 2017, 2(2): 20-24 https://doi.org/10.16513/j.cnki.10-1427/tk.2017.02.003

参考文献

列表( 原文顺序 | 文献年度倒序 | 文中引用次数倒序 ) 可视化分析

[1]	LUNA-RUBIO R, TREJO-PEREA M, VARGAS-VAZQUEZ D, et al. Optimal sizing of renewable hybrids energy systems: a review of methodologies[J]. Solar Energy, 2012(86): 1077-1088. 本文引用 [1]

[2]	ABBEY C, JOOS G. A stochastic optimization approach to rating of energy storage systems in wind-diesel isolated grids[J]. IEEE Transactions on Power Systems, 2009, 24(1): 418-426. 本文引用 [1]

[3]	BAJPAI P, DASH V. Hybrid renewable energy systems for power generation in stand-alone applications: a review[J]. Renewable and Sustainable Energy Reviews, 2012, 16(5): 2926-2939. 本文引用 [1]

[4]	BREKKEN T K A, YOKOCHI A, JOUANNE A V, et al. Optimal energy storage sizing and control for wind power applications[J]. IEEE Transactions on Sustainable Energy, 2011, 2(1): 69-77. 本文引用 [1]

[5]	CONG T N. Progress in electrical energy storage system: A critical review[J]. Progress in Natural Science, 2009(3): 291-312. 本文引用 [1]

[6]	舒军. 风光储系统中储能单元的平滑控制方法研究[D]. 成都：电子科技大学，2012. 本文引用 [1]

[7]

陈中，杜文娟，王海风，等. 基于阻尼转矩分析法的储能系统抑制系统低频振荡[J]. 电力系统自动化，2009, 33(12): 8-11.

CHEN

Zhong

, DU

Wenjuan

, WANG

Haifeng

, et al. Research on storage equipment to suppressing power system of low frequency oscillation with DTA algorithm[J]. Automation of Electric Power Systems, 2009, 33(12): 8-11(in Chinese)．

本文引用 [1]

[8]	汪新园. 大规模风电接入电力系统的可靠性评估及储能策略研究[D]. 杭州：浙江大学，2013. 本文引用 [1]

[9]	朱武，操瑞发，应彭华，等. 超级电容器系统在改善并网风电场输出中的应用[J]. 电网技术，2008, 32(S2): 256-259. ZHU Wu, CAO Ruifa, YING Penghua, et al. Application of SCESS in improving stability of power system connected with wind farms[J]. Power System Technology, 2008, 32(S2): 256-259(in Chinese)．本文引用 [1]

[10]

王剑，刘天琪，李兴源. 风电场及储能装置对发输电系统可靠性的影响[J]. 电网技术，2011, 35(5): 165-170.

WANG

Jian

, LIU

Tianqi

, LI

Xingyuan

. Influences of connecting wind farms and energy storage devices to power grid on reliability of power generation and transmission system[J]. Power System Technology, 2011, 35(5): 165-170(in Chinese)．

本文引用 [1]

[11]	李妍，荆盼盼，王丽，等. 通用储能系统数学模型及其PSASP建模研究[J]. 电网技术，2012, 36(1): 51-57. LI Yan, JING Panpan, WANG Li, et al. A mathematical model of versatile energy storage system and its modeling by power system analysis software package[J]. Power System Technology, 2012, 36(1): 51-57(in Chinese)．本文引用 [2]

[12]	张崇巍，张兴. PWM整流器及其控制[M]. 北京：机械工程出版社，2003. 本文引用 [1]

[13]	于群，曹娜. MATLAB/Simulink电力系统建模与仿真[M]. 北京：机械工业出版社，2011. 本文引用 [1]

[14]	ZIELINSKI K, WEITKEMPER P, LAUR R, et al. Optimization of power allocation for interference cancellation with particle swarm optimization[J]. IEEE Transactions on Evolutionary Computation, 2009, 13(1): 128-150. 本文引用 [1]

[15]	PEDRASA M, SPOONER T D, MACGILL I F. Scheduling of demand side resources using binary particle swarm optimization[J]. IEEE Transactions on Power Systems, 2009, 24(3): 1173-1181. 本文引用 [1]

[16]	张智晟，林涛. 电力系统经济负荷分配的量子粒子群算法[J]. 电工电能新技术，2008(4): 1-4, 13. ZHANG Zhisheng, LIN Tao. Research on power system of economic load dispatch with quantum-behaved particle swarm optimization algorithm[J]. Advanced Technology of Electrical Engineering and Energy, 2008(4): 1-4, 13(in Chinese)．本文引用 [1]

[17]	于赞梅，刘观起，刘森. 基于双适应度微粒群优化算法的最优潮流计算[J]. 电气应用，2007(4): 25-29. YU Zanmei, LIU Guanqi, LIU Sen. Research on optimal power flow with double fitness particle swarm optimization algorithm[J]. Electrotechnical Application, 2007(4): 25-29(in Chinese)．本文引用 [1]

[18]	史峰，王辉，郁磊，等. MATLAB智能算法30个案例分析[M]. 北京：北京航空航天大学出版社，2011. 本文引用 [1]

[19]	周志超，王成山，郭力. 变速变桨距风电机组的全风速限功率优化控制[J]. 中国电机工程学报，2015, 35(8): 1837-1844. ZHOU Zhichao, WANG Chengshan, GUO Li. Output power curtailment control of variable-speed variable-pitch wind turbine generator at all wind speed regions[J]. Proceedings of the CSEE, 2015, 35(8): 1837-1844(in Chinese)．本文引用 [1]