{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T20:19:02Z","timestamp":1783455542394,"version":"3.55.0"},"reference-count":32,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"State Grid Corporation of China Research Project","award":["52060025001S-052-ZN"],"award-info":[{"award-number":["52060025001S-052-ZN"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Ind. Inf."],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1109\/tii.2026.3674492","type":"journal-article","created":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T20:15:52Z","timestamp":1775074552000},"page":"6022-6033","source":"Crossref","is-referenced-by-count":0,"title":["Lightweight Edge-Deployable Voltage Prediction Method for Distribution Networks With High Photovoltaic Penetration"],"prefix":"10.1109","volume":"22","author":[{"given":"Zhijin","family":"Lyu","sequence":"first","affiliation":[{"name":"School of Automation, Nanjing University of Science and Technology, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9859-4892","authenticated-orcid":false,"given":"Wei","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Automation, Nanjing University of Science and Technology, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Du","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Technology and Equipment for Defense against Power System Operational Risks, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tian","family":"Gao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Technology and Equipment for Defense against Power System Operational Risks, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xibin","family":"Shan","sequence":"additional","affiliation":[{"name":"Weihai Power Supply Company, Weihai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaiyuan","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Automation, Nanjing University of Science and Technology, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"152","article-title":"Impact and improvement of distributed generation on distribution network voltage quality","volume-title":"Proc. Chin. Soc. Elect. Eng.","volume":"28","author":"Pei","year":"2008"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAS.1983.317769"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2011.2166794"},{"issue":"5","key":"ref4","first-page":"20","article-title":"Prediction of voltage RMS value based on ARMA model","volume-title":"Elect. Power Eng. Technol.","volume":"37","author":"Yin","year":"2018"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2016.2579198"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2019.01.055"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2014.05.055"},{"issue":"23","key":"ref8","first-page":"179","article-title":"Review and prospect of method study for distributed model predictive control in power system","volume":"44","author":"Le","year":"2020","journal-title":"Automat. Elect. Power Syst."},{"issue":"22","key":"ref9","first-page":"110","article-title":"Distributed generation system interconnection protection based on multi-class SVM","volume":"39","author":"Yang","year":"2015","journal-title":"Automat. Elect. Power Syst."},{"issue":"1","key":"ref10","first-page":"43","article-title":"Decision tree and its key techniques","volume":"17","author":"Yang","year":"2007","journal-title":"Comput. Technol. Develop."},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2020.115733"},{"issue":"4","key":"ref12","first-page":"180","article-title":"Analysis and prospect of deep learning application in smart grid","volume":"43","author":"Zhou","year":"2019","journal-title":"Automat. Elect. Power Syst."},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2013.2288675"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2022.125609"},{"issue":"2","key":"ref15","first-page":"614","article-title":"Ultra short-term power load forecasting based on combined LSTM-XGB model","volume":"44","author":"Chen","year":"2020","journal-title":"Power Syst. Technol."},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115895"},{"key":"ref17","article-title":"Mamba: Linear-time sequence modeling with selective state spaces","volume-title":"1rst Conf. Lang. Modeling","author":"Gu","year":"2024"},{"issue":"9","key":"ref18","first-page":"5879","article-title":"A survey on the applications of Big Data analytics in smart grids","volume":"16","author":"Wang","year":"2020","journal-title":"IEEE Trans. Ind. Informat."},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/S0169-2070(97)00044-7"},{"issue":"4","key":"ref20","first-page":"91","article-title":"Short-term load prediction based on combined model of LSTM and LightGBM","volume":"45","author":"Chen","year":"2021","journal-title":"Automat. Elect. Power Syst."},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2025.110644"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2025.139248"},{"issue":"9","key":"ref24","first-page":"3416","article-title":"Load forecasting method based on CNN-GRU hybrid neural network","volume":"44","author":"Yao","year":"2020","journal-title":"Power Syst. Technol."},{"issue":"5","key":"ref25","first-page":"53","article-title":"Short-term load forecasting method based on GRU-NN model","volume":"43","author":"Wang","year":"2019","journal-title":"Automat. Elect. Power Syst."},{"issue":"1","key":"ref26","first-page":"147","article-title":"Review of the short-term load forecasting methods of electric power system","volume":"39","author":"Liao","year":"2011","journal-title":"Power Syst. Protection Control"},{"issue":"3","key":"ref27","first-page":"527","article-title":"Big data analysis and parallel load forecasting of electric power user side","volume":"35","author":"Wang","year":"2015","journal-title":"J. Chin. Soc. Elect. Eng."},{"issue":"6","key":"ref28","first-page":"55","article-title":"Study of support vector machines for short-term load forecasting","volume-title":"Proc. CSEE","volume":"23","author":"Li","year":"2003"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3390\/su12177076"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2024.3449938"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TCSII.2020.2996161"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2022.3187557"}],"container-title":["IEEE Transactions on Industrial Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/9424\/11595910\/11466342.pdf?arnumber=11466342","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T19:48:27Z","timestamp":1783453707000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11466342\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":32,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/tii.2026.3674492","relation":{},"ISSN":["1551-3203","1941-0050"],"issn-type":[{"value":"1551-3203","type":"print"},{"value":"1941-0050","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7]]}}}