{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:06:24Z","timestamp":1760058384515,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T00:00:00Z","timestamp":1743120000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Jiangsu Industry Outlook and Key Technology Research Project","award":["BE2023093-2"],"award-info":[{"award-number":["BE2023093-2"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>This paper presents a moving horizon estimator-based cooperative model predictive control strategy for a low-voltage distribution area equipped with symmetric distributed generators (DGs). First, DGs have their symmetries in the control structures that can be utilized for the control design. Then, a simplified model using feedback linearization theory for the symmetric DGs with hierarchical control reduces the high-order detailed models to low-order ones. To supplement the loss of accuracy and reliability in the proposed model, the controller introduces a moving horizon estimator to observe the unmeasured state variables under the poor communication condition of a low-voltage distribution network. Compared to the conventional method, the moving horizon estimator has advantages in handling uncertain disturbances, communication delays, constraints, etc. Furthermore, with all measured and observed state information, a cooperative distributed model predictive controller can be executed, and the stability and feasibility of controller are given. Finally, the effectiveness of the proposed control technique is verified through simulation based on Matlab\/Simulink.<\/jats:p>","DOI":"10.3390\/sym17040513","type":"journal-article","created":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T06:06:35Z","timestamp":1743141995000},"page":"513","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Cooperative MHE-Based Distributed Model Predictive Control for Voltage Regulation of Low-Voltage Distribution Networks"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7321-1621","authenticated-orcid":false,"given":"Yongqing","family":"Lv","sequence":"first","affiliation":[{"name":"School of Electrical Engineering, Southeast University, Nanjing 210018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaobo","family":"Dou","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Southeast University, Nanjing 210018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kexin","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Southeast University, Nanjing 210018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Southeast University, Nanjing 210018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,28]]},"reference":[{"key":"ref_1","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. 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