{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T02:18:25Z","timestamp":1775787505746,"version":"3.50.1"},"reference-count":24,"publisher":"Tech Science Press","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2025.063979","type":"journal-article","created":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T02:40:46Z","timestamp":1745289646000},"page":"861-886","source":"Crossref","is-referenced-by-count":3,"title":["Intelligent Scheduling of Virtual Power Plants Based on Deep Reinforcement Learning"],"prefix":"10.32604","volume":"84","author":[{"given":"Shaowei","family":"He","sequence":"first","affiliation":[]},{"given":"Wenchao","family":"Cui","sequence":"additional","affiliation":[]},{"given":"Gang","family":"Li","sequence":"additional","affiliation":[]},{"given":"Hairun","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Xiang","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Yu","family":"Tai","sequence":"additional","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"2277","DOI":"10.1007\/s10311-022-01435-8","article-title":"Strategies to achieve a carbon neutral society: a review","volume":"20","author":"Chen","year":"2022","journal-title":"Environ Chem Lett"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"108191","DOI":"10.1016\/j.epsr.2022.108191","article-title":"Frequency control studies: a review of power system, conventional and renewable generation unit modeling","volume":"211","author":"Fern\u00e1ndez-Guillam\u00f3n","year":"2022","journal-title":"Electric Power Syst Res"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"2071","DOI":"10.3390\/electronics13112071","article-title":"SolarFlux predictor: a novel deep learning approach for photovoltaic power forecasting in South Korea","volume":"13","author":"Min","year":"2071 2024","journal-title":"Electronics"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.rser.2018.02.007","article-title":"Intermittent and stochastic character of renewable energy sources: consequences, cost of intermittence and benefit of forecasting","volume":"87","author":"Notton","year":"2018","journal-title":"Renew Sustain Energy Rev"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"20347","DOI":"10.1016\/j.ijhydene.2022.04.142","article-title":"A review on distributed generation impacts on electric power system","volume":"47","author":"Ufa","year":"2022","journal-title":"Int J Hydrogen Energy"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"4328","DOI":"10.1109\/ISGT-Asia.2019.8881433","author":"Wang","year":"2019","journal-title":"2019 IEEE innovative smart grid technologies-Asia (ISGT Asia)"},{"key":"ref7","series-title":"IEEE International Conference on Power System Technology (POWERCON)","first-page":"1","article-title":"A review on the virtual power plant: components and operation systems","author":"Ghavidel","year":"2016"},{"key":"ref8","first-page":"679","article-title":"A Markovian decision process","volume":"6","author":"Bellman","year":"1957","journal-title":"J Math Mech"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.ijepes.2012.11.001","article-title":"A new model for optimal generation scheduling of power system considering generation units availability","volume":"47","author":"Gjorgiev","year":"2013","journal-title":"Int J Electr Power Energy Syst"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.enconman.2015.01.071","article-title":"A fast method for the unit scheduling problem with significant renewable power generation","volume":"94","author":"Os\u00f3rio","year":"2015","journal-title":"Energy Convers Manag"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"106658","DOI":"10.1016\/j.ijepes.2020.106658","article-title":"Optimal stochastic scheduling of electrical and thermal renewable and non-renewable resources in virtual power plant","volume":"127","author":"Rahimi","year":"2021","journal-title":"Int J Electr Power Energy Syst"},{"key":"ref12","first-page":"74","article-title":"Study on hybrid generator scheduling based on multi-agent","volume":"42","author":"Cui","year":"2014","journal-title":"Shaanxi Electr Power"},{"key":"ref13","doi-asserted-by":"crossref","unstructured":"Xiao T, Chen Y, Diao H, Huang S, Shen C. On fast-converged deep reinforcement learning for optimal dispatch of large-scale power systems under transient security constraints. arXiv:2304.08320. 2024.","DOI":"10.2139\/ssrn.4703658"},{"key":"ref14","series-title":"IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","first-page":"1","article-title":"Performance comparison of deep RL algorithms for energy systems optimal scheduling","author":"Shengren","year":"2022"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"6792","DOI":"10.1109\/TSMC.2023.3289322","article-title":"Dynamic parallel machine scheduling with deep Q-network","volume":"53","author":"Liu","year":"2023","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"ref16","volume":"771","author":"Workneh","year":"2023","journal-title":"Artificial intelligence and industrial applications. A2IA 2023. Lecture notes in networks and systems"},{"key":"ref17","series-title":"12th IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)","first-page":"1","article-title":"Deep-Q-network-based intelligent reschedule for power system operational planning","author":"Liu","year":"2020"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"108225","DOI":"10.1016\/j.ijepes.2022.108225","article-title":"Flexibility-based generation maintenance scheduling in presence of uncertain wind power plants forecasted by deep learning considering demand response programs portfolio","volume":"141","author":"Sharifi","year":"2022","journal-title":"Int J Electr Power Energy Syst"},{"key":"ref19","first-page":"734","article-title":"Intelligent traffic light via policy-based deep reinforcement learning","volume":"20","author":"Zhu","year":"2022","journal-title":"Int J Intell Transp Syst Res"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1109\/MSP.2017.2743240","article-title":"Deep reinforcement learning: a brief survey","volume":"34","author":"Arulkumaran","year":"2017","journal-title":"IEEE Signal Process Mag"},{"key":"ref21","first-page":"181","article-title":"Heuristic mean-variance optimization in Markov decision processes using state-dependent risk aversion","volume":"33","author":"Schlosser","year":"2022","journal-title":"IMA J Manag Math"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.rser.2016.01.016","article-title":"A review of residential demand response of smart grid","volume":"59","author":"Tarish","year":"2016","journal-title":"Renew Sustain Energy Rev"},{"key":"ref23","first-page":"57","article-title":"Daily load curve based power consumption mode extraction and clustering analysis","volume":"42","author":"Liu","year":"2023","journal-title":"Diangong Dianen Xinjishu"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"22281","DOI":"10.1007\/s00521-023-08877-3","article-title":"Double deep Q-network-based self-adaptive scheduling approach for smart shop floor","volume":"35","author":"Ma","year":"2023","journal-title":"Neural Comput Applic"}],"container-title":["Computers, Materials & Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-84-1\/TSP_CMC_63979\/TSP_CMC_63979.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T01:34:49Z","timestamp":1763343289000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v84n1\/61754"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":24,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.063979","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}