混合动力系统电能质量扰动分析及治理

doi:10.12204/j.issn.1000-7229.2021.04.003

摘要/Abstract

摘要：

基于并联有源滤波器(shunt active power filter,SAPF)和动态电压调节器(dynamic voltage restorer,DVR),首先,搭建了包含光伏和风机的混合动力系统,用以模拟分布式电源接入配电网中产生的电能质量(power quality,PQ)扰动。其次,利用模糊逻辑、神经网络和自适应神经模糊推理系统控制算法对SAPF的动态性能进行优化,对电能质量扰动进行治理,使用人工智能技术进行管理,使光伏和风能系统均实现最大功率点跟踪(maximum power point tracking, MPPT)。最后,在搭建的仿真系统中进行验证,线性负载和非线性负载输出侧谐波畸变率分别降至0.20%和2.05%,满足配电系统对于电能质量的要求。

关键词: 电能质量(PQ), 分布式电源, 并联有源滤波器(SAPF), 自适应神经模糊推理系统

Abstract:

Applying shunt active power filter (SAPF) and dynamic voltage restorer (DVR), a hybrid power system including photovoltaic and wind turbine is built in this paper to observe power quality (PQ) disturbances caused by the distributed generation connecting to the distribution network. In addition, control algorithms such as fuzzy logic, neural network and adaptive neural fuzzy inference system are employed to optimize the dynamic performance of SAPF, to control power quality disturbances, to achieve maximum power point tracking (MPPT) in both photovoltaic and wind energy systems by adopting artificial intelligence technology. Finally, the harmonic distortion rates of the linear and nonlinear loads on the output side are reduced to 0.20% and 2.05% in the simulation system, respectively, which meet the power quality requirements in power distribution system.

Key words: power quality (PQ), distributed generation, shunt active power filter (SAPF), adaptive neural fuzzy inference system

中图分类号:

TM711

徐艳春, 阚锐涵, 高永康, 谢莎莎, MI Lu. 混合动力系统电能质量扰动分析及治理[J]. 电力建设, 2021, 42(4): 17-26.

XU Yanchun, KAN Ruihan, GAO Yongkang, XIE Shasha, MI Lu. Research on Power Quality Improvement of Hybrid Power System[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(4): 17-26.

图/表 16

图1 混合动力系统模型

Fig.1 Model of the hybrid governance system

图2 仿真系统运行流程

Fig.2 Operation flow chart of the simulation system

图3 二级管光伏电池模型

Fig.3 Model of a two-stage photovoltaic cell

图4 谐波电流控制器

Fig.4 Harmonic current controller

图5 DVR逻辑控制

Fig.5 Dynamic voltage regulation logic control

表1 径向基函数网络与多层网络的区别

Table 1 The difference between radial basis function network and multi-layer network

图6 模糊逻辑推理控制器

Fig.6 Fuzzy logic inference controller

图7 模糊逻辑推理训练流程

Fig.7 Training process of fuzzy logic reasoning

表2 系统参数配置

Table 2 System parameter configuration

图8 PQ扰动下的混合动力系统

Fig.8 Hybrid power system under PQ disturbance

图9 光伏接入PQ扰动

Fig.9 PQ disturbance in photovoltaic system

表3 FFT分析

Table 3 Analysis of FFT

图10 风能接入PQ扰动

Fig.10 PQ disturbance caused by wind power access

图11 设备治理PQ恢复信号

Fig.11 PQ recovery signal of equipment governance

图12 非线性负载侧电流谐波畸变率

Fig.12 Harmonic distortion rate of the current on nonlinear load side

图13 线性负载侧电流谐波畸变率

Fig.13 Harmonic distortion rate of the current on linear load side

参考文献 18

[1]	GARANAYAK P, PANDA G, RAY P K. Harmonic estimation using RLS algorithm and elimination with improved current control technique based SAPF in a distribution network[J]. International Journal of Electrical Power & Energy Systems, 2015,73:209-217. doi: 10.1016/j.ijepes.2015.04.023 URL
[2]	KUMAR R, BANSAL H O. Hardware in the loop implementation of wavelet based strategy in shunt active power filter to mitigate power quality issues[J]. Electric Power Systems Research, 2019,169:92-104. doi: 10.1016/j.epsr.2019.01.001 URL
[3]	DAS S R, RAY P K, MOHANTY A. Improvement in power quality using hybrid power filters based on RLS algorithm[J]. Energy Procedia, 2017,138:723-728. doi: 10.1016/j.egypro.2017.10.207 URL
[4]	PRADHAN M, MISHRA M K. Dual P-Q theory based energy-optimized dynamic voltage restorer for power quality improvement in a distribution system[J]. IEEE Transactions on Industrial Electronics, 2019,66(4):2946-2955. doi: 10.1109/TIE.2018.2850009 URL
[5]	OMAR A I, ABDEL ALEEM S H E, EL-ZAHAB E E A, et al. An improved approach for robust control of dynamic voltage restorer and power quality enhancement using grasshopper optimization algorithm[J]. ISA Transactions, 2019,95:110-129. doi: 10.1016/j.isatra.2019.05.001 URL
[6]	BARRADO J A, GRINO R, VALDERRAMA-BLAVI H. Power-quality improvement of a stand-alone induction generator using a STATCOM with battery energy storage system[J]. IEEE Transactions on Power Delivery, 2010,25(4):2734-2741. doi: 10.1109/TPWRD.2010.2051565 URL
[7]	DIAN R J, XU W, MU C X. Improved negative sequence current detection and control strategy for H-bridge three-level active power filter[J]. IEEE Transactions on Applied Superconductivity, 2016,26(7):1-5.
[8]	李彦林, 王乐三, 许胜, 等. 基于一阶矢量谐振器的基波正负序分量及谐波检测方法[J]. 高电压技术, 2018,44(10):3399-3406.
	LI Yanlin, WANG Lesan, XU Sheng, et al. Detection method of positive and negative sequence components based on one order vector proportional-integral resonant[J]. High Voltage Engineering, 2018,44(10):3399-3406.
[9]	SUPPIONI V P, GRILO A P, TEIXEIRA J C. Coordinated control for the series grid side converter-based DFIG at subsynchronous operation[J]. Electric Power Systems Research, 2019,173:18-28. doi: 10.1016/j.epsr.2019.04.006 URL
[10]	孟庭如, 邹贵彬, 许春华, 等. 一种分区协调控制的有源配电网调压方法[J]. 中国电机工程学报, 2017,37(10):2852-2860.
	MENG Tingru, ZOU Guibin, XU Chunhua, et al. A voltage regulation method based on district-dividing coordinated control for active distribution network[J]. Proceedings of the CSEE, 2017,37(10):2852-2860.
[11]	LIAO H L, MILANOVI Ć J V. Techno-economic analysis of global power quality mitigation strategy for provision of differentiated quality of supply[J]. International Journal of Electrical Power & Energy Systems, 2019,107:159-166. doi: 10.1016/j.ijepes.2018.11.006 URL
[12]	徐艳春, 高永康, 李振兴, 等. 改进LMD算法在微电网电能质量扰动信号检测中的应用[J]. 电网技术, 2019,43(1):332-341.
	XU Yanchun, GAO Yongkang, LI Zhenxing, et al. Application of improved LMD algorithm in signal detection of power quality disturbance in microgrid[J]. Power System Technology, 2019,43(1):332-341.
[13]	徐艳春, 高永康, 李振兴, 等. 基于VMD初始化S变换的混合动力系统电能质量扰动检测与分类[J]. 中国电机工程学报, 2019,39(16):4786-4798, 4980.
	XU Yanchun, GAO Yongkang, LI Zhenxing, et al. Power quality disturbance detection and classification of hybrid power system based on VMD initialization S-transform[J]. Proceedings of the CSEE, 2019,39(16):4786-4798,4980.
[14]	XU Y C, GAO Y K, LI Z H, et al. Detection and classification of power quality disturbances in distribution networks based on VMD and DFA[J]. CSEE Journal of Power and Energy Systems, 2019,6(1):122-130.
[15]	MARMOUH S, BOUTOUBAT M, MOKRANI L. Performance and power quality improvement based on DC-bus voltage regulation of a stand-alone hybrid energy system[J]. Electric Power Systems Research, 2018,163:73-84. doi: 10.1016/j.epsr.2018.06.004 URL
[16]	AGALAR S, KAPLAN Y A. Power quality improvement using STS and DVR in wind energy system[J]. Renewable Energy, 2018,118:1031-1040. doi: 10.1016/j.renene.2017.01.013 URL
[17]	张爽, 马磊, 潘晓敏, 等. 基于ISBM边界延拓和迭代HHT算法的电能质量扰动检测方法[J]. 智慧电力, 2020,48(3):76-82.
	ZHANG Shuang, MA Lei, PAN Xiaomin, et al. Power quality disturbance detection method based on ISBM boundary extension and iterative HHT algorithm[J]. Smart Power, 2020,48(3):76-82.
[18]	马嘉秀, 徐玮浓, 何复兴, 等. 基于WT和SVM的电能质量分类识别方法[J]. 智慧电力, 2019,47(3):16-22, 37.
	MA Jiaxiu, XU Weinong, HE Fuxing, et al. A novel power quality classification and identification method based on WT and SVM[J]. Smart Power, 2019,47(3):16-22, 37.