王振国,康丽莉,李特,姜凯华,刘超,侯慧
WANG Zhenguo,KANG Lili,LI Te,JIANG Kaihua,LIU Chao,HOU Hui

• 1:国网浙江省电力有限公司电力科学研究院
• 2:浙江省气象科学研究所
• 3:武汉理工大学自动化学院

摘要(Abstract)：

浙江是我国重要沿海省份，为减少台风灾害引起的损失，对电力系统的风险区域划分尤为重要。首先从登陆点分布、路径特征、时间特征、风速特征及降水特征等方面，利用历史数据总结分析浙江沿海地区台风气象特征。其次，对浙江电力系统进行台风灾害特征分析，得到输电系统故障点分布、变电系统与台风登陆点距离关系、配电系统停电用户占比分布等。最后，采用浙江台风气象及电力系统历史数据绘制台风灾害风险区域图，特别是对倒塔高风险区、风偏高风险区及地质灾害高风险区进行了详细划分。分析结果可为各级电网应对台风灾害的风险评估与处置提供支持。
Zhejiang, as a crucial coastal province in China, deems the delineation of risk zones in its power system imperative for minimizing losses caused by typhoon disasters. Initially, the paper leverages historical data to comprehensively analyze meteorological features of typhoons in the Zhejiang coastal areas, focusing on aspects such as landing point distribution, path characteristics, temporal patterns, wind speed attributes, and precipitation features. Subsequently, an analysis of typhoon disaster characteristics in the Zhejiang power system is conducted. This entails examining the distribution of fault points in the transmission system, the relationship between the substation system and typhoon landing points, and the distribution of power outage percentages in the distribution system. Finally, utilizing historical data from both Zhejiang's typhoon meteorology and power system, the paper creates a map outlining the risk zones for typhoon disasters. This includes a detailed delineation of high-risk areas for tower collapses, areas prone to wind deviations, and regions with high geological disaster risks. The analysis results aim to support risk assessment and response measures for typhoon disasters across various levels of the power grid.

关键词(KeyWords)： 台风灾害;浙江沿海地区;气象特征;电力系统;风险区域
typhoon disaster;Zhejiang coastal area;meteorological characteristics;power system;risk area

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金资助项目（61933005）;; 国网浙江省电力有限公司科技项目（2006CB200303）

作者(Author): 王振国,康丽莉,李特,姜凯华,刘超,侯慧
WANG Zhenguo,KANG Lili,LI Te,JIANG Kaihua,LIU Chao,HOU Hui

DOI: 10.19585/j.zjdl.202403004

参考文献(References)：

• [1]周象贤，刘黎，王少华，等.浙江电网自然灾害特征、趋势与预测技术概况[J].浙江电力，2021,40(5):20-29.ZHOU Xiangxian,LIU Li,WANG Shaohua,et al. An overview on characteristics,tendency and prediction technology of natural disasters in Zhejiang power grid[J].Zhejiang Electric Power,2021,40(5):20-29.
• [2]侯慧，刘超，陈希，等.台风灾害下配网两阶段应急抢修恢复优化策略[J].电力系统保护与控制，2022,50(23):169-179.HOU Hui,LIU Chao,CHEN Xi,et al.Optimization strategy for two-stage emergency repair and recovery of a distribution network after a typhoon disaster[J].Power System Protection and Control,2022,50(23):169-179.
• [3]周丹阳，黄晓燕.极端天气下基于RF-LSTM的配电网馈线薄弱环节识别方法[J].浙江电力，2022,41(12):71-78.ZHOU Danyang,HUANG Xiaoyan. An identification method for weak links in distribution network feeders based on RF-LSTM under extreme weather[J].Zhejiang Electric Power,2022,41(12):71-78.
• [4]侯慧，刘超，陈希，等.基于网格化多源异构数据的台风灾害下杆塔受损数量预测[J].高电压技术，2023,49(3):1205-1212.HOU Hui,LIU Chao,CHEN Xi,et al.Prediction on number of damaged towers under typhoon disasters based on gridded multi-source heterogeneous data[J].High Voltage Engineering,2023,49(3):1205-1212.
• [5] WMO.全球热带气旋预报指南[M].裘国庆，方维模，译.北京：气象出版社，1995.
• [6]向纯怡，许映龙，高拴柱，等.2021年西北太平洋台风活动特征和预报难点分析[J].气象，2022,48(9):1195-1208.XIANG Chunyi,XU Yinglong,GAO Shuanzhu,et al.Analysis of the characteristics and forecast difficulties of typhoon over the western North Pacific in 2021[J].Meteorological Monthly,2022,48(9):1195-1208.
• [7]杨奕杰.基于近20年历史数据的中国沿海城市台风灾害风险评估[D].上海：上海海洋大学，2022.YANG Yijie. Risk assessment of typhoon disasters in coastal cities in China based on historical data in the past20 years[D].Shanghai:Shanghai Ocean University,2022.
• [8]陆逸.浙江台风灾害风险评估与区划[D].南京：南京信息工程大学，2016.LU Yi.Risk assessment and regionalization of tropical cyclone disasters in Zhejiang[D]. Nanjing:Nanjing University of Information Science&Technology,2016.
• [9]田慧丽，张鼎茂，周荣生，等.台风灾害下配电系统受损评估研究[J].电网与清洁能源，2021,37(12):16-24.TIAN Huili,ZHANG Dingmao,ZHOU Rongsheng,et al.A study on damage evaluation of power distribution system under typhoon disaster[J].Power System and Clean Energy,2021,37(12):16-24.
• [10]李家钰，秦文萍，景祥，等.台风灾害下考虑连锁故障的电力系统弹性评估[J].电力系统及其自动化学报，2023,35(1):14-22.LI Jiayu,QIN Wenping,JING Xiang,et al.Power system resilience assessment considering cascading failure under typhoon disaster[J]. Proceedings of the CSU-EPSA,2023,35(1):14-22.
• [11]沈菲菲，唐超，许冬梅，等.基于不同背景场条件的雷达资料同化在登陆台风“桑美”中的应用研究[J].海洋学报，2021,43(1):69-81.SHEN Feifei,TANG Chao,XU Dongmei,et al.Experiment of assimilating Doppler radar data in Typhoon Saomai based on the different initial conditions[J]. Haiyang Xuebao,2021,43(1):69-81.
• [12]栗倩倩，王伟，黄亮，等.台风暴雨型滑坡滞后效应分析：以浙江青田县“利奇马”台风为例[J].中国地质灾害与防治学报，2022,33(6):10-19.LI Qianqian,WANG Wei,HUANG Liang,et al.Analysis on lag effect of typhoon-induced landslide:a case study of typhoon “Lekima” in Qingtian County,Zhejiang Province[J].The Chinese Journal of Geological Hazard and Control,2022,33(6):10-19.
• [13]胡鑫蓉.“黑格比”台风局地特大暴雨过程分析及地形影响研究[D].北京：中国气象科学研究院，2022.HU Xinrong. Analysis of the local extreme rainstorm brought by typhoon hagupit and the study of topographic influence[D]. Beijing:Chinese Academy of Meteorological Sciences,2022.
• [14]张恩铭.220 kV全复合材料输电杆塔结构优化设计[J].浙江电力，2020,39(10):63-68.ZHANG Enming. Optimal design of structure of 220 kV composite transmission towers[J]. Zhejiang Electric Power,2020,39(10):63-68.
• [15] QIN W T,TANG J,LAO S Y.DeepFR:a trajectory prediction model based on deep feature representation[J].Information Sciences,2022,604:226-248.
• [16] TONG B,WANG X,FU J Y,et al.Short-term prediction of the intensity and track of tropical cyclone via ConvLSTM model[J].Journal of Wind Engineering and Industrial Aerodynamics,2022,226:105026.
• [17]牟笛，陈安.中国区域自然灾害综合风险评估[J].安全，2020,41(12):23-26.MU Di,CHEN An.Natura disaster universal risk evaluation of China[J].Safety&Security,2020,41(12):23-26.
• [18]高娇娇，王威，苏经宇，等.区域自然灾害综合风险模糊随机评价方法[J].中国安全生产科学技术，2014,10(5):103-109.GAO Jiaojiao,WANG Wei,SU Jingyu,et al.Fuzzy stochastic simulation method for comprehensive risk assessment of regional natural disaster[J].Journal of Safety Science and Technology,2014,10(5):103-109.
• [19]刘庭杰，施能，顾骏强.浙江省台风灾害的统计分析[J].灾害学，2002,17(4):64-71.LIU Tingjie,SHI Neng,GU Junqiang.A statistical analysis of typhoon disasters in Zhejiang Province[J].Journal of Catastrophology,2002,17(4):64-71.
• [20]朱恒槺，李虎星，袁灿.基于区域灾害系统和ArcGIS的山洪灾害风险评价[J].人民黄河，2019,41(6):21-25.ZHU Hengkang,LI Huxing,YUAN Can. Study on the risk assessment of torrent flood disaster based on regional disaster system and ArcGIS[J]. Yellow River,2019,41(6):21-25.
• [21]王野.葫芦岛市强降雨洪涝灾害风险区域划分研究[J].黑龙江水利科技，2023,51(2):166-170.WANG Ye.Study on risk region division of heavy rainfall and flood in Huludao city[J].Heilongjiang Hydraulic Science and Technology,2023,51(2):166-170.
• [22]周小梅，杜清运，彭瑞.浙江省台风灾害风险区划研究[J].地理空间信息，2018,16(8):12-14.ZHOU Xiaomei,DU Qingyun,PENG Rui. Research on risk zoning of typhoon disaster in Zhejiang Province[J].Geospatial Information,2018,16(8):12-14.
• [23]余瀚，郭浩，王静爱.区域自然灾害风险综合区划：以广东台风灾害人口与经济风险区划为例[J].灾害学，2022,37(2):131-137.YU Han,GUO Hao,WANG Jing'ai. Comprehensive regionalization of natural disaster risk—a case study of population and economic risk caused by typhoon in Guangdong Province[J]. Journal of Catastrophology,2022,37(2):131-137.
• [24]姜露露，马仁锋，袁海红.台风灾害经济损失评估研究进展[J].生态科学，2022,41(3):252-263.JIANG Lulu,MA Renfeng,YUAN Haihong. Review on economic loss assessment of typhoon disasters[J].Ecological Science,2022,41(3):252-263.
• [25]董加斌，黄新晴.登陆浙江的台风路径分类和暴雨落区分析[J].浙江气象，2019,40(3):13-19.DONG Jiabin,HUANG Xinqing.Typhoon path classification and rainstorm area analysis of landing in Zhejiang Province[J]. Journal of Zhejiang Meteorology,2019,40(3):13-19.