{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T16:08:41Z","timestamp":1768838921984,"version":"3.49.0"},"reference-count":31,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2025,2,18]],"date-time":"2025-02-18T00:00:00Z","timestamp":1739836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52371334"],"award-info":[{"award-number":["52371334"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Circuit Theory &amp;amp; Apps"],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Introducing new energy sources to create green ports holds great importance in the context of global energy conservation. As an important source of new energy power generation, the optimal operation of photovoltaic (PV) power generation has always been the focus of research. Port PV systems are prone to partial shading due to variable weather conditions and building occlusion. This phenomenon results in PV arrays with multipeaked power curves, thereby increasing the difficulty of maximum power point tracking (MPPT). Moreover, traditional reinforcement learning (RL) is incapable of addressing this problem effectively. Therefore, this paper proposes an improved RL\u2010MPPT algorithm. To enhance the convergence speed of this method, a Q\u2010table matching mechanism based on a back propagation neural network (BPNN) is introduced. Additionally, to mitigate the problem of the PV panel aging and the lack of updates in the Q\u2010table knowledge base, a Q\u2010table knowledge base time window update mechanism is implemented. Finally, MPPT method is verified by a comprehensive set of simulation experiments. The experimental results indicate that the Q\u2010table matching mechanism based on BPNN can effectively improve the convergence speed of the RL algorithm, and can effectively overcome the multi\u2010peak power characteristics in the MPPT control process of the port PV system in complex environmental scenarios, with good control accuracy, dynamic characteristics and robustness.<\/jats:p>","DOI":"10.1002\/cta.4479","type":"journal-article","created":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T00:09:01Z","timestamp":1739923741000},"page":"7181-7199","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Optimal Operation of Port PV Systems Based on Improved Reinforcement Learning"],"prefix":"10.1002","volume":"53","author":[{"given":"Ruoli","family":"Tang","sequence":"first","affiliation":[{"name":"School of Naval Architecture, Ocean and Energy Power Engineering Wuhan University of Technology  Wuhan Hubei China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5260-4332","authenticated-orcid":false,"given":"Chenchen","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Naval Architecture, Ocean and Energy Power Engineering Wuhan University of Technology  Wuhan Hubei China"}]},{"given":"Xin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Naval Architecture, Ocean and Energy Power Engineering Wuhan University of Technology  Wuhan Hubei China"}]},{"given":"Zhengcheng","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Automation Wuhan University of Technology  Wuhan Hubei China"}]},{"given":"Jingang","family":"Lai","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Automation Huazhong University of Science and Technology  Wuhan Hubei China"}]},{"given":"Yan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Transportation and Logistics Engineering Wuhan University of 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