{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T19:48:58Z","timestamp":1780084138163,"version":"3.54.0"},"reference-count":56,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,6,9]],"date-time":"2022-06-09T00:00:00Z","timestamp":1654732800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Universiti Teknologi PETRONAS (UTP) and Yayasan Universiti Teknologi Petronas","award":["YUTP 015LC0-360"],"award-info":[{"award-number":["YUTP 015LC0-360"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Smart Grid (S.G.) is a digitally enabled power grid with an automatic capability to control electricity and information between utility and consumer. S.G. data streams are heterogenous and possess a dynamic environment, whereas the existing machine learning methods are static and stand obsolete in such environments. Since these models cannot handle variations posed by S.G. and utilities with different generation modalities (D.G.M.), a model with adaptive features must comply with the requirements and fulfill the demand for new data, features, and modality. In this study, we considered two open sources and one real-world dataset and observed the behavior of ARIMA, ANN, and LSTM concerning changes in input parameters. It was found that no model observed the change in input parameters until it was manually introduced. It was observed that considered models experienced performance degradation and deterioration from 5 to 15% in terms of accuracy relating to parameter change. Therefore, to improve the model accuracy and adapt the parametric variations, which are dynamic in nature and evident in S.G. and D.G.M. environments. The study has proposed a novel adaptive framework to overcome the existing limitations in electrical load forecasting models.<\/jats:p>","DOI":"10.3390\/s22124363","type":"journal-article","created":{"date-parts":[[2022,6,13]],"date-time":"2022-06-13T02:01:44Z","timestamp":1655085704000},"page":"4363","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Deterioration of Electrical Load Forecasting Models in a Smart Grid Environment"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9595-6184","authenticated-orcid":false,"given":"Abdul","family":"Azeem","sequence":"first","affiliation":[{"name":"Electrical and Electronics Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Idris","family":"Ismail","sequence":"additional","affiliation":[{"name":"Electrical and Electronics Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7179-8206","authenticated-orcid":false,"given":"Syed Muslim","family":"Jameel","sequence":"additional","affiliation":[{"name":"Postdoc Scientist at Structure Lab, School of Engineering, National University of Ireland Galway (NUIG), Galway H91 TK33, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6405-4150","authenticated-orcid":false,"given":"Fakhizan","family":"Romlie","sequence":"additional","affiliation":[{"name":"Electrical and Electronics Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1022-4983","authenticated-orcid":false,"given":"Kamaluddeen Usman","family":"Danyaro","sequence":"additional","affiliation":[{"name":"Computer Science Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3335-373X","authenticated-orcid":false,"given":"Saurabh","family":"Shukla","sequence":"additional","affiliation":[{"name":"Data Science Institute (DSI), National University of Ireland Galway (NUIG), Galway H91 TK33, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1016\/j.energy.2018.10.119","article-title":"Short term load forecasting based on feature extraction and improved general regression neural network model","volume":"166","author":"Liang","year":"2019","journal-title":"Energy"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1016\/j.energy.2019.02.141","article-title":"A hybrid method based on neural network and improved environmental adaptation method using Controlled Gaussian Mutation with real parameter for short-term load forecasting","volume":"174","author":"Singh","year":"2019","journal-title":"Energy"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.ijepes.2014.11.003","article-title":"Optimal control strategy of a DC micro grid","volume":"7","author":"Bracale","year":"2015","journal-title":"Int. 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