Research on Power Quality Improvement of Hybrid Power System

doi:10.12204/j.issn.1000-7229.2021.04.003

Abstract

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

CLC Number:

TM711

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.

Figures/Tables 16

Fig.1 Model of the hybrid governance system

Fig.2 Operation flow chart of the simulation system

Fig.3 Model of a two-stage photovoltaic cell

Fig.4 Harmonic current controller

Fig.5 Dynamic voltage regulation logic control

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

Fig.6 Fuzzy logic inference controller

Fig.7 Training process of fuzzy logic reasoning

Table 2 System parameter configuration

Fig.8 Hybrid power system under PQ disturbance

Fig.9 PQ disturbance in photovoltaic system

Table 3 Analysis of FFT

Fig.10 PQ disturbance caused by wind power access

Fig.11 PQ recovery signal of equipment governance

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

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

References 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.