{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T14:59:41Z","timestamp":1786460381346,"version":"build-2736575974"},"reference-count":0,"publisher":"European Alliance for Innovation n.o.","license":[{"start":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T00:00:00Z","timestamp":1786406400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["EAI Endorsed Trans Energy Web"],"abstract":"<jats:p>Data-driven forecasting has become increasingly important for describing the temporal interactions among heterogeneous variables in modern power systems. To capture the nonlinear coupling, heterogeneous fluctuations, and multi-scale temporal variations between renewable generation and load demand, this study develops an MT-Transformer framework for coordinated wind\u2013solar\u2013load forecasting. Meteorological variables, historical renewable output, historical load, and temporal labels are integrated as model inputs. A shared Transformer encoder is used to learn common temporal representations, and task-specific forecasting heads are designed to generate synchronized predictions for wind power, PV power, and load. The experimental results show that MT-Transformer achieves an MAE of 0.0848, an RMSE of 0.1254, and an R\u00b2 of 0.9302. Compared with the Persistence Model, the MAE and RMSE decrease by 36.05% and 30.49%, respectively. The predicted outputs are further converted into a net-load sequence, from which fluctuation indicators are derived. The peak\u2013valley difference reaches 0.462 p.u., and the maximum ramp rate reaches 0.087 p.u.\/h, indicating evident peak-shaving pressure and short-term regulation demand. These findings confirm that the proposed framework improves coordinated forecasting performance and provides quantitative evidence for coal-power peak regulation, reserve capacity allocation, and ancillary service demand identification.<\/jats:p>","DOI":"10.4108\/ew.13035","type":"journal-article","created":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T12:47:50Z","timestamp":1786452470000},"source":"Crossref","is-referenced-by-count":0,"title":["An MT-Transformer Framework for Coordinated Wind\u2013Solar\u2013Load Forecasting with Net-Load-Based Coal-Power Regulation Demand Identification"],"prefix":"10.4108","volume":"13","author":[{"given":"Meng","family":"Huang","sequence":"first","affiliation":[{"name":"\u5c71\u897f\u7701\u957f\u6cbb\u5e02"},{"id":[{"id":"https:\/\/ror.org\/01z6fgx85","id-type":"ROR","asserted-by":"publisher"}],"name":"CHN Energy (China)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Wang","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01z6fgx85","id-type":"ROR","asserted-by":"publisher"}],"name":"CHN Energy (China)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Teng","family":"Luo","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01z6fgx85","id-type":"ROR","asserted-by":"publisher"}],"name":"CHN Energy (China)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao","family":"Ju","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01z6fgx85","id-type":"ROR","asserted-by":"publisher"}],"name":"CHN Energy (China)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenchao","family":"Guo","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01z6fgx85","id-type":"ROR","asserted-by":"publisher"}],"name":"CHN Energy (China)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenghao","family":"Ning","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01z6fgx85","id-type":"ROR","asserted-by":"publisher"}],"name":"CHN Energy (China)"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2587","published-online":{"date-parts":[[2026,8,11]]},"container-title":["EAI Endorsed Transactions on Energy Web"],"original-title":[],"link":[{"URL":"https:\/\/publications.eai.eu\/index.php\/ew\/article\/download\/13035\/4238","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/publications.eai.eu\/index.php\/ew\/article\/download\/13035\/4238","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T12:47:51Z","timestamp":1786452471000},"score":1,"resource":{"primary":{"URL":"https:\/\/publications.eai.eu\/index.php\/ew\/article\/view\/13035"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,11]]},"references-count":0,"URL":"https:\/\/doi.org\/10.4108\/ew.13035","relation":{},"ISSN":["2032-944X"],"issn-type":[{"value":"2032-944X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,11]]}}}