{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T15:10:32Z","timestamp":1783523432758,"version":"3.55.0"},"reference-count":69,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,13]],"date-time":"2022-09-13T00:00:00Z","timestamp":1663027200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Deputyship for Research &amp; Innovation, Ministry of Education, Saudi Arabia","award":["QU-IF-04-02-28647"],"award-info":[{"award-number":["QU-IF-04-02-28647"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Multistep power consumption forecasting is smart grid electricity management\u2019s most decisive problem. Moreover, it is vital to develop operational strategies for electricity management systems in smart cities for commercial and residential users. However, an efficient electricity load forecasting model is required for accurate electric power management in an intelligent grid, leading to customer financial benefits. In this article, we develop an innovative framework for short-term electricity load forecasting, which includes two significant phases: data cleaning and a Residual Convolutional Neural Network (R-CNN) with multilayered Long Short-Term Memory (ML-LSTM) architecture. Data preprocessing strategies are applied in the first phase over raw data. A deep R-CNN architecture is developed in the second phase to extract essential features from the refined electricity consumption data. The output of R-CNN layers is fed into the ML-LSTM network to learn the sequence information, and finally, fully connected layers are used for the forecasting. The proposed model is evaluated over residential IHEPC and commercial PJM datasets and extensively decreases the error rates compared to baseline models.<\/jats:p>","DOI":"10.3390\/s22186913","type":"journal-article","created":{"date-parts":[[2022,9,13]],"date-time":"2022-09-13T22:37:28Z","timestamp":1663108648000},"page":"6913","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":62,"title":["Improving the Efficiency of Multistep Short-Term Electricity Load Forecasting via R-CNN with ML-LSTM"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9021-180X","authenticated-orcid":false,"given":"Mohammed F.","family":"Alsharekh","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Unaizah College of Engineering, Qassim University, Unaizah 56452, Saudi Arabia"},{"name":"System Control Processing Research Group, Qassim University, Buraydah 51452, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shabana","family":"Habib","sequence":"additional","affiliation":[{"name":"System Control Processing Research Group, Qassim University, Buraydah 51452, Saudi Arabia"},{"name":"Department of Information Technology, College of Computer, Qassim University, Buraydah 51452, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1488-7696","authenticated-orcid":false,"given":"Deshinta Arrova","family":"Dewi","sequence":"additional","affiliation":[{"name":"Faculty of Data Science and Information Technology, INTI International University, Nilai 71800, Negeri Sembilan, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0292-7304","authenticated-orcid":false,"given":"Waleed","family":"Albattah","sequence":"additional","affiliation":[{"name":"System Control Processing Research Group, Qassim University, Buraydah 51452, Saudi Arabia"},{"name":"Department of Information Technology, College of Computer, Qassim University, Buraydah 51452, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2379-4451","authenticated-orcid":false,"given":"Muhammad","family":"Islam","sequence":"additional","affiliation":[{"name":"System Control Processing Research Group, Qassim University, Buraydah 51452, Saudi Arabia"},{"name":"Department of Electrical Engineering, College of Engineering and Information Technology, Onaizah Colleges, Onaizah 56447, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6317-4313","authenticated-orcid":false,"given":"Saleh","family":"Albahli","sequence":"additional","affiliation":[{"name":"System Control Processing Research Group, Qassim University, Buraydah 51452, Saudi Arabia"},{"name":"Department of Information Technology, College of Computer, Qassim University, Buraydah 51452, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yar, H., Imran, A.S., Khan, Z.A., Sajjad, M., and Kastrati, Z. 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