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To reduce the impact of renewable energy output prediction errors on the distribution network, this paper considers the charging and discharging behaviors of electric vehicles (EVs) and demand responses, and proposes a robust optimization model for the distribution network with a three-stage framework. In the day-ahead stage, a day-ahead optimization operation model is constructed by promoting load shifting through price-based demand response, minimizing daily operation costs while accounting for new energy uncertainty via penalty costs for supply-demand imbalances. In the intraday stage, an intraday rolling optimization model is developed by integrating EV charging\/discharging responses, refining the day-ahead plan with higher-resolution forecasts to enhance renewable energy absorption and load balancing. In the real-time stage, a real-time adjustment model utilizes incentive-based demand response to smooth short-term fluctuations in renewable output, ensuring voltage stability and operational flexibility. Experimental simulations on the IEEE 33-bus test system demonstrate that the proposed three-stage cooperative operation strategy significantly promotes renewable energy consumption, reduces operational costs, and improves the reliability of active distribution network (ADN) operation.<\/jats:p>","DOI":"10.1038\/s41598-025-25084-3","type":"journal-article","created":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T11:22:30Z","timestamp":1763724150000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Robust modeling and evidence-based evaluation method for a active distribution network with EVs and CHPs"],"prefix":"10.1038","volume":"15","author":[{"given":"Kuineng","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingheng","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zikang","family":"Fang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunshou","family":"Mao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,11,21]]},"reference":[{"key":"25084_CR1","doi-asserted-by":"publisher","first-page":"114808","DOI":"10.1016\/j.rser.2024.114808","volume":"205","author":"G Varathan","year":"2024","unstructured":"Varathan, G. & Belwin Edward, J. 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