Tieqiang Wang
ABSTRACT
Aiming at the problems of low efficiency and subjectivity of current grid operation states classification methods of power grid operation states, a novel classification approach based on deep neural network (DNN) is proposed. Firstly, operation states of power grid are analyzed and summarized. Secondly, combining with the characteristics of the grid, the key indicators representing the operation states of the grid are pre-processed. Finally, DNN is introduced and used to deeply study the state of the historical grid to realize the classification of the current operation state. By extracting effective historical information, the method can realize the classification of the grid operation state, and assist the dispatcher to adjust the grid in time to avoid serious accidents. The simulation results of the New England 10-unit 39-bus system show that compared with the traditional BP neural network, the method proposed in this paper has higher accuracy. The model can help the dispatcher to quickly judge the state of the system so as to give a quick decision. The more accurate and effective macroscopic classification of the historical section can facilitate further data mining.
- ZHANG Jian, PU Tianjiao, WANG Wei, et al. "A Comprehensive Assessment Index System for Smart Grid Demonstration Projects," Power System Technology, Dec.2011, pp. 35(6): 5--9, doi: 10.13335/j.1000-3673.pst.2011.06.001Google Scholar
- Amew. "Power system operation corporation limited," New Delhi: National Load Dispatch Centre, Dec. 2012Google Scholar
- GE Rui, DONG Wei, DONG Yuechun. "Analysis of Large-Scale Blackout in UCTE Power Grid and Lessons to be Drawn to Power Grid Operation in China," Power System Technology, Dec. 2007, pp. 31(3): 1--6, doi: 10.13335/j.1000-3673.pst.2007.03.001Google Scholar
- "Australian Energy Market Operator. Preliminary report---black system event in South Australia on 28 September 2016," Australian Energy Market Operator Limited, Dec. 2016Google Scholar
- HONG Wen, LIN Tao, CHEN Baoping. "Research on grid running state assessment method based on short circuit capability margin," Electrical Measurement and Instrumentation, Dec. 2018, pp. 24(2): 12--14.Google Scholar
- LI Lina, WANG Wenda, ZHANG Wei. "An evaluation method for low voltage distribution operation state based on loop resistance matrix," Automation and instrumentation, Dec. 2019, pp. 155--158, doi: 10.14016/j.cnki.1001-9227.2019.01.155Google Scholar
- DONG Guangzhong. "Research on State Estimation and Optimization Control of Microgrid System Based on Bayesian Method," University of Science and Technology of China, Dec. 2018, pp. 57--60Google Scholar
- DING Jianglin, "Research on Evaluation Method of Distribution Network Operation State Based on Cloud Model," Northeast Electric Power University, Dec. 2018Google Scholar
- LIANG Haiping, TIAN Chao, WANG Tieqiang, CAO Xin, YANG Xiaodong, LIU Yingpei. "Running section similarity matching based on improved K-means algorithm," Electric Power Automation Equipment, Dec. 2019, pp. 119--124+140, doi: 10.16081/j.issn.1006-6047.2019.07.018Google Scholar
- JIANG Wei, SONG Xin, HUANG Yingwei, LIU Cheng, HAO Wei, ZHANG Liuliu. "Design of Intelligent Grid Operation State Index System Based on Analytic Hierarchy Process," Electrical Applications, Dec. 2015, pp. 624--629Google Scholar
- LI Pengyuan, GU Xueping. "Fast Prediction of Overvoltage in Black Start Operation Based on Neural Network," Grid Techology, Dec. 2006, pp. 66--70, doi: 10.13335/j.1000-3673.pst.2006.03.014Google Scholar
- FENG Zhihong, LIU Qu. "Characteristic Structure Analysis Method for Voltage Static Stability of Multi-machine Power System," Journal of Tsinghua University: Natural Science Edition, Dec. 1991, pp. 19--27, doi: 10.16511/j.cnki.qhdxxb.1991.04.004Google Scholar
- ZHAO Wenqing, ZHU Lingyu, GAO Shuguo, LI Gang. "Research on Fault Diagnosis Method of Power Transformer Based on Multi-Source Information Fusion," Electric Power Information and Communication Technology, Dec. 2018, pp. 25--30, doi: 10.16543/j.2095-641x.electric.power.ict.2018.10.005Google Scholar
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