Abstract
The purpose of harmonic pollution level assessment is to judge whether the harmonic pollution of a bus or a region is beyond the limit. Considering the fuzziness of the index criteria values caused by harmonic variation, this paper proposes an assessment method for harmonic pollution level based on the extended cloud similarity measurement. Firstly, according to the main characteristics of harmonic pollution, a set of evaluation index of harmonic pollution level is formed, including the total harmonic distortion rate of voltage, the fifth harmonic current RMS value, the seventh harmonic current RMS value, the eleventh harmonic current RMS value, and thirteenth harmonic current RMS value. Secondly, considering the group decision-making behavior of the harmonic pollution level assessment, the group eigenvalue method is utilized to integrate the weight of multiple operators and to calculate the comprehensive weight of the assessment index. On this basis, the harmonic pollution are divided into four levels, and the index criteria values are expressed as triangular fuzzy numbers. Besides, the fuzzy numbers are unified by the extended cloud. Finally, the extended cloud similarity and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is utilized to get the evaluation results. The monitoring data of seven 10 kV buses in Guangzhou is adopted to verify the validity and rationality of the evaluation method.
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References
Boby, M., Pramanick, S., Kaarthik, R.S., Arun Rahul, S., Gopakumar, K., Umanand, L.: Fifth- and seventh-order harmonic elimination with multilevel dodecagonal voltage space vector structure for IM drive using a single DC source for the full speed range. IEEE Trans. Power Electron. 32(1), 60–68 (2017)
Xavier, L.S., Cupertino, A.F., de Resende, J.T., Mendes, V.F., Pereira, H.A.: Adaptive current control strategy for harmonic compensation in single-phase solar inverters. Electr. Power Syst. Res. 142(1), 84–95 (2017)
Sun, Z.M., He, Z.Y., Zang, T.L., Liu, Yilu: Multi-interharmonic spectrum separation and measurement under asynchronous sampling condition. IEEE Trans. Instrum. Meas. 65(8), 1902–1912 (2016)
Zang, T.L., He, Z.Y., Fu, L., Wang, Y., Qian, Q.Q.: Adaptive method for harmonic contribution assessment based on hierarchical K-means clustering and Bayesian partial least squares regression. IET Gener. Transm. Distrib. 10(13), 3220–3227 (2016)
Zang, T.L., He, Z.Y., Fu, L., Chen, J., Qian, Q.Q.: Harmonic source localization approach based on fast kernel entropy optimization ICA and minimum conditional entropy. Entropy 18(6), 214 (2016)
Jiang, H., Peng, J.C., Ou, Y.P., Li, Z.Y.: Power quality unitary quantification and evaluation based on probability and vector algebra. J. Hunan Univ. (Nat. Sci.) 30(1), 66–70 (2003)
Jia, Q.Q., Song, J.H., Lan, H., Yang, Y.H., Yin, C.X.: Quality of electricity commodity and its fuzzy evaluation. Power Syst. Technol. 24(6), 46–49 (2000)
Zhao, X., Zhao, C.Y., Jia, X.F., Li, J.Y.: Fuzzy synthetic evaluation of power quality based on changeable weight. Power Syst. Technol. 29(6), 11–16 (2005)
Huang, J., Zhou, L., Li, Q.H., Zhang, F., Liu, H.Y.: Evaluation of power quality based on the method of matter-element. J. Chongqing Univ. (Nat. Sci. Ed.) 30(6), 25–29 (2007)
Ding, L., Jia, X.F., Zhao, C.Y., Li, G.Y.: Synthetic evaluation of power quality based on extenics. Electr. Power Autom. Equip. 27(12), 44–47, 52 (2007)
Liu, Y.Y., Li, G.D., Gu, Q., Xu, Y.H.: The comprehensive evaluation of power quality based on the RBF neural network. Electrotech. Appl. 26(1), 45–48 (2007)
Zhou, L., Li, Q.H., Zhang, F.: Application of genetic projection pursuit interpolation model on power quality synthetic evaluation. Power Syst. Technol. 31(7), 32–35 (2007)
Li, Q.H., Zhou, L., Liu, H.Y., Zhang, F.: Evaluation of power quality by accelerating genetic algorithm and Shepard interpolation. High Volt. Eng. 33(7), 139–143 (2007)
Cavallini, A., Cacciari, M., Loggini, M., Montanari, G.C.: Evaluation of harmonic levels in electrical networks by statistical indexes. IEEE Trans. Ind. Appl. 34(4), 1116–1126 (1994)
Lai, L.L., Chan, W.L., Tse, C.T., So, A.T.P.: Real-time frequency and harmonic evaluation using artificial neural networks. IEEE Trans. Power Delivery 14(1), 52–59 (1999)
Zang, T.L., He, Z.Y., Qian, Q.Q.: Distribution network service restoration multiple attribute group decision-making using entropy weight and group eigenvalue. In: Proceedings of the 3rd International Conference on Intelligent System Design and Engineering Applications, Hong Kong, China, pp. 602–606 (2013)
Acknowledgment
The authors acknowledge the support by Science and Technology Support Program of Sichuan Province (No. 2016RZ0079), Open Project of Key Laboratory of electric Power Big Data of Guizhou Province and Guizhou Fengneng Science and Technology Development Co., Ltd.
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Zang, T., Wang, Y., He, Z., Qian, Q. (2017). Harmonic Pollution Level Assessment in Distribution System Using Extended Cloud Similarity Measurement Method. In: Zou, B., Han, Q., Sun, G., Jing, W., Peng, X., Lu, Z. (eds) Data Science. ICPCSEE 2017. Communications in Computer and Information Science, vol 728. Springer, Singapore. https://doi.org/10.1007/978-981-10-6388-6_32
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DOI: https://doi.org/10.1007/978-981-10-6388-6_32
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