{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T04:07:38Z","timestamp":1782965258803,"version":"3.54.5"},"reference-count":17,"publisher":"European Society of Computational Methods in Sciences and Engineering","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2022,9,5]]},"abstract":"<jats:p>A risk assessment method for transmission line galloping in mountainous areas is proposed based on meteorological conditions, environmental factors and line parameters to timely and effectively assess the risk level of stable and reliable power supply of iced transmission lines in galloping and ensure its normal operation. The galloping amplitude is obtained through cluster algorithm by use of three factors, i.e., icing, line and wind, on the premise of entering the key meteorological factors by fuzzy algorithm to predict the ice thickness. Then the galloping amplitude is used as the risk evaluation standard, and the risk is graded accordingly. Taking the historical galloping monitoring data and meteorological record parameters collected by a certain power grid as samples, upon analysis, it shows that the proposed method can perform more accurate assessment on the risk of transmission lines, reveal the weak links of lines through the risk assessment results, ensure that the risk points or sections can be controlled, provide the decision-making basis and enhanced decision-making support ability for power grid dispatchers and line operators and maintainers, realize the shift from passive hazard prevention to active risk avoidance, effectively improve the ability of power grid to prevent, reduce and cope with severe meteorological hazards, reduce the impact of galloping on the safe operation of power grid, and decrease unnecessary hazards and losses.<\/jats:p>","DOI":"10.3233\/jcm-226170","type":"journal-article","created":{"date-parts":[[2022,6,7]],"date-time":"2022-06-07T12:38:34Z","timestamp":1654605514000},"page":"1413-1432","source":"Crossref","is-referenced-by-count":4,"title":["Risk assessment of the iced transmission line galloping based on fuzzy and cluster algorithms"],"prefix":"10.66113","volume":"22","author":[{"given":"Zhimeng","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Boyan","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"55691","reference":[{"key":"10.3233\/JCM-226170_ref1","first-page":"60","article-title":"Reliability assessment of large power systems considering climate factors","author":"Liu","journal-title":"Electric Power Automation Equipment"},{"issue":"13","key":"10.3233\/JCM-226170_ref2","first-page":"51","article-title":"Running state and its risk evaluation of transmission line based on markov chain model","volume":"39","author":"Jiang","year":"2015","journal-title":"Automation of Electric Power Systems"},{"issue":"04","key":"10.3233\/JCM-226170_ref3","first-page":"1289","article-title":"Condition assessment method for transmission line with multiple outputs based on variable weight principle and fuzzy comprehensive evaluation","volume":"43","author":"Zou","year":"2017","journal-title":"High Voltage Engineering"},{"key":"10.3233\/JCM-226170_ref4","unstructured":"Wang J, Xiong X, Liang Y, Li Z, Weng S. Geographical and meteorological factor related transmission line risk difference assessment: Method and indexes. Proceedings of the CSEE, 2016; 36(05): 1252-1259."},{"issue":"10","key":"10.3233\/JCM-226170_ref5","first-page":"84","article-title":"Reliability risk evaluation for the high voltage overhead transmission line under icing condition","volume":"44","author":"Wang","year":"2016","journal-title":"Power System Protection and Control"},{"issue":"09","key":"10.3233\/JCM-226170_ref6","first-page":"194","article-title":"Early warning method for transmission line icing galloping based on risk coefficient","volume":"55","author":"Wang","year":"2019","journal-title":"High Voltage Electrical Apparatus"},{"issue":"09","key":"10.3233\/JCM-226170_ref7","first-page":"86","article-title":"Short-term risk assessment of power grid considering galloping prediction of transmission lines","volume":"46","author":"Chu","year":"2018","journal-title":"Power System Protection and Control"},{"key":"10.3233\/JCM-226170_ref8","unstructured":"Sun Y, Wang X, Wang J, Wang X. Overhead transmission line icing flashover trip characteristic analysis and risk model. Proceedings of the CSEE, 2011; 31(31): 149-158."},{"issue":"21","key":"10.3233\/JCM-226170_ref9","first-page":"168","article-title":"Assessment method for power grid icing risk based on short-term icing forecasting","volume":"40","author":"Yan","year":"2016","journal-title":"Automation of Electric Power Systems"},{"issue":"21","key":"10.3233\/JCM-226170_ref10","first-page":"8601","article-title":"Evolutionary strategy-projection pursuit algorithms for risk assessment of transmission line icing disaster considering multi-factors","volume":"20","author":"Wu","year":"2020","journal-title":"Science Technology and Engineering"},{"issue":"03","key":"10.3233\/JCM-226170_ref11","first-page":"37","article-title":"Risk evaluation of ice disaster using fuzzy logic theory","volume":"35","author":"Lu","year":"2019","journal-title":"Electric Power Science and Engineering"},{"issue":"06","key":"10.3233\/JCM-226170_ref12","first-page":"672","article-title":"Fuzzy evaluation and risk matrix based on overhead lines risk assessment","volume":"35","author":"Li","year":"2014","journal-title":"Power & Energy"},{"issue":"11","key":"10.3233\/JCM-226170_ref13","doi-asserted-by":"crossref","first-page":"04014081","DOI":"10.1061\/(ASCE)EM.1943-7889.0000795","article-title":"Two-parameter bifurcation and stability analysis for nonlinear galloping of iced transmission lines","volume":"40","author":"Lou","year":"2014","journal-title":"J Eng Mech"},{"key":"10.3233\/JCM-226170_ref15","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1007\/s40565-013-0042-y","article-title":"Power transmission risk assessment considering component condition","volume":"2","author":"Lei","year":"2014","journal-title":"J. Mod. Power Syst. Clean Energy"},{"issue":"17","key":"10.3233\/JCM-226170_ref16","first-page":"45","article-title":"Graded warning scheme of transmission line galloping based on grey clustering analysis","volume":"57","author":"Li","year":"2020","journal-title":"Electrical Measurement & Instrumentation"},{"issue":"04","key":"10.3233\/JCM-226170_ref18","first-page":"11","article-title":"Application of improved spectral clustering algorithm in image segmentation","volume":"37","author":"Wang","year":"2018","journal-title":"Measurement & Control Technology"},{"issue":"07","key":"10.3233\/JCM-226170_ref19","first-page":"89","article-title":"Micro-meteorological feature extraction model for ice covering process of transmission line based on spectral clustering","volume":"38","author":"Liu","year":"2019","journal-title":"Measurement & Control Technology"}],"container-title":["Journal of Computational Methods in Sciences and Engineering"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JCM-226170","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:06:27Z","timestamp":1776809187000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JCM-226170"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,5]]},"references-count":17,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.3233\/jcm-226170","relation":{},"ISSN":["1472-7978","1875-8983"],"issn-type":[{"value":"1472-7978","type":"print"},{"value":"1875-8983","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,5]]}}}