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In this paper, a deep renewable scenario generation model combining Multi\u2010Scale Decomposition mixer and Wasserstein Generative Adversarial Network with Gradient Penalty is proposed to achieve novel decision\u2010oriented forecasting, thus realizing effective characterization of renewable temporal dynamics and economic performance. From the perspective of wind and solar generation, the validity of the proposed method is demonstrated on a real\u2010world dataset with power station at regional level. Experimental results confirm the superiority of model performance through statistical indicators and power system scheduling test, compared with a number of scenario generation and time series forecasting benchmarks.<\/jats:p>","DOI":"10.1111\/exsy.70241","type":"journal-article","created":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T08:48:48Z","timestamp":1774342128000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Decision\u2010Oriented Renewable Scenario Generation Based on Multi\u2010Scale Decomposition and\n                    <scp>WGAN<\/scp>\n                    \u2010\n                    <scp>GP<\/scp>"],"prefix":"10.1111","volume":"43","author":[{"given":"Hao","family":"Hong","sequence":"first","affiliation":[{"name":"School of Management and Engineering Nanjing University  Nanjing China"}]},{"given":"Bo","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Management and Engineering Nanjing University  Nanjing China"}]},{"given":"Zhihang","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Management and Engineering Nanjing University  Nanjing China"}]},{"given":"Jingshi","family":"Cui","sequence":"additional","affiliation":[{"name":"School of Management and Engineering Nanjing University  Nanjing China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3322-2086","authenticated-orcid":false,"given":"Junzo","family":"Watada","sequence":"additional","affiliation":[{"name":"Graduate School of Information, Production and Systems Waseda University  Kitakyyushu Japan"}]}],"member":"311","published-online":{"date-parts":[[2026,3,24]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/exsy.13830"},{"key":"e_1_2_11_3_1","volume-title":"Neural Information Processing Systems","author":"Agrawal A.","year":"2019"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2021.3128485"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.23919\/PSCC.2018.8442500"},{"key":"e_1_2_11_6_1","doi-asserted-by":"crossref","unstructured":"Chen Y. 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