Distribution Networks State Estimation Based on Topological Contraction and Quality Tag

• Autorzy: Huang, Y. , Liu, D. , Xu, W. , Yu, W.

Warianty tytułu

PL

Określanie stanu sieci dystrybucyjnej na podstawie topologicznej kontrakcji i tagów jakości

• Języki publikacji: EN

Abstrakty

EN

By processing a set of raw measurement data, it provides a real-time system state solution which is the basis of the advanced applications. Currently, the incomplete and poor quality of measurement data is the key factor to impacting state estimation of distribution network. With the help of decision tree theory, the bad data identification method which combines the historical data and remote data from IDP (Integrated Data Platform) and a data processing method is proposed. Algorithm uses the laws of the distribution network data logic to determine the logic of the distribution network. With the help of the theoretical framework of decision tree we can establish the data quality assessment system and fix those bad data so as to increase the quality of the input data. On the basis of data evaluation and fixing, by collecting grid-based data of distribution network and using topology analysis and contracting technology, we can contract the actual network to the state estimation calculation network which meets the observation demand. Quality labels are used to modify the weight of the least squares state estimation algorithm to improve the accuracy of state estimation. Based on the status of data in city distribution network, a proper measurement data detecting and fixing method as well as topology contracting method is proposed. Two real cases of certain central power supply area in Shanghai have verified the effectiveness and feasibility of the method.

PL

W artykule zaproponowano metody badania stanu sieci dystrybucyjnej w czasie rzeczywistym. Metodę zilustrowano na przykładzie dwóch obszarów sieci zasilającej w Szanghaju.

Słowa kluczowe

PL

sieć zasilająca; jakość energii

EN

distribution network; state estimation; decision tree; Quality Tag

• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2012
• Tom: R. 88, nr 5b
• Strony: 1-6
• Opis fizyczny: Bibliogr. 19 poz., rys., tab.

Twórcy

autor

Huang, Y.

autor

Liu, D.

autor

Xu, W.

autor

Yu, W.

• Key Laboratory of Ministry of Education of Power transmission and power conversion control School of Electrical

Bibliografia

• [1]. Yu Erkeng. 1985, Power System State Estimation, Water Power Press, Beijing, China.
• [2]. F. F. Wu, 1990, "Power System State Estimation: A Survey", Electrical Power & Energy Systems， Vol. 12， No. 2， April．
• [3]. Celik M K, Abur Ali, 1992, "A robust WLAV state estimation using transformations ". IEEE Transactions on Power Systems, vol. 7(1)
• [4]. Liu Jian, Ma Li, Wei Li, Dong Haipeng, 2004, "Analysis of Large Scale Distribution Networks with Reduced Calculation", Power System Technology, vol. 28(8).
• [5]. Cai Zhongqin, Guo Zhizhong, 2000, "Newton Load Flow for Radial Distribution Network Based on Upstream Labeling Technique", Proceedings of the CSEE，vol. 20(6), 13-16．
• [6]. Sun Hongbin, Zhang Boming, Xiang Niande, 1999, "Study on Convergence of Back/Forward Sweep Distribution Power Flow", Proceedings of the CSEE, vol. 19(7), 26-29．
• [7]. Lu Jiangang , Wen Bojian, Jiang Caiyun, Gu Quan, 2002, "Research of Multi-source Data and Its Quality Control in Energy Management System", Automation of Electric Power Systems, vol.26(23):73-75
• [8]. Ye Feng, He Hua, Gu Quan, Zhang Gaofeng, 2006, "Bad Data Identification and Correction for Load Forecasting in Energy Management System", Automation of Electric Power Systems, vol.30(15):85-88.
• [9]. Liu Dong, Ding Zhenhua, Teng Letian, 2004, "Key Technology and Its Development in The Practicability of Distribution Automation Systems", Automation of Electric Power Systems, vol. 28(7), 16-19
• [10]. George F ． Luger, 2004, Artificial Intelligence: Structures and Strategies for Complex Problem Solving, Fifth Edition.China Machine Press, Beijing, China.
• [11]. Liu Jian, et al,1998, Analysis and Optimization of Large Scale Distribution Networks, Electrical Power Press, Beijing, China．
• [12]. Li Haiying, Li Yuzeng, Zhao Shaohua. An Energy Acquisition Model for a Distribution Company With Distributed Generation and Interruptible Load Options[J]. Proceedings of the CSEE, 2008, 28(10):88-93. (in Chinese)
• [13]. Bagen W, Billinton R. Incorporating well-being considerations in generating systems using energy storage. IEEE Transactions on Energy Conversion 2005; 20(1): 225–230.
• [14]. Billinton R, Bai G. Generating capacity adequacy associated with wind energy. IEEE Transactions on Energy Conversion 2004; 19(3): 641–646.
• [15]. Wangdee W, Billinton R. Considering load-carrying capability and wind speed correlation of WECS in generation adequacy assessment. IEEE Transactions on Energy Conversion 2006; 21(3): 734–741.
• [16]. Billinton R, Wangdee W. Reliability-based transmission reinforcement planning associated with large-scale wind farms. IEEE Transactions on Power Systems 2007; 22(1): 34–41.
• [17]. TradeWind Project. Integrating wind: developing Europe’s power market for the large-scale integration of wind power, EWEA, Feb. 2009.
• [18]. Liao Huaiqing, Liu Dong, Huang Yuhui. A Study on Compatibility of Smart Grid Based on Large scale Energy Storage System[J]. Automation of Electric Power Systems, 2010,34(2):15-19. (in Chinese)
• [19]. Huang Yuhui,Liu Dong,Liao Huaiqing. Network Reconfiguration Solution Space Optimization Considering Grid Characteristics[J]. Automation of Electric Power Systems (Accepted).