{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T22:57:31Z","timestamp":1771023451293,"version":"3.50.1"},"reference-count":31,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2019,3,18]],"date-time":"2019-03-18T00:00:00Z","timestamp":1552867200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Basic Research Plan in Shaanxi Province of China","award":["2017 JM6033"],"award-info":[{"award-number":["2017 JM6033"]}]},{"name":"National Natural Science Foundation Shenzhen Joint Research Program","award":["U1613219"],"award-info":[{"award-number":["U1613219"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51877174"],"award-info":[{"award-number":["51877174"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the opening project of State Key Laboratory","award":["EIPE18201"],"award-info":[{"award-number":["EIPE18201"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Monitoring the current operation status of the power system plays an essential role in the enhancement of the power grid for future requirements. Therefore, the real-time state estimation (SE) of the power system has been of widely-held concern. The Kalman filter is an outstanding method for the SE, and the noise in the system is generally assumed to be Gaussian noise. In the actual power system however, these measurements are usually disturbed by non-Gaussian noises in practice. Furthermore, it is hard to get the statistics of the state noise and measurement noise. As a result, a novel adaptive extended Kalman filter with correntropy loss is proposed and applied for power system SE in this paper. Firstly, correntropy is used to improve the robustness of the EKF algorithm in the presence of non-Gaussian noises and outliers. In addition, an adaptive update mechanism of the covariance matrixes of the measurement and process noises is introduced into the EKF with correntropy loss to enhance the accuracy of the algorithm. Extensive simulations are carried out on IEEE 14-bus and IEEE 30-bus test systems to verify the feasibility and robustness of the proposed algorithm.<\/jats:p>","DOI":"10.3390\/e21030293","type":"journal-article","created":{"date-parts":[[2019,3,19]],"date-time":"2019-03-19T12:12:25Z","timestamp":1552997545000},"page":"293","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Adaptive Extended Kalman Filter with Correntropy Loss for Robust Power System State Estimation"],"prefix":"10.3390","volume":"21","author":[{"given":"Zhiyu","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Automation and Information Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7378-5836","authenticated-orcid":false,"given":"Jinzhe","family":"Qiu","sequence":"additional","affiliation":[{"name":"School of Automation and Information Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2781-1693","authenticated-orcid":false,"given":"Wentao","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Automation and Information Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1623","DOI":"10.1109\/PROC.1987.13931","article-title":"Security analysis and optimization","volume":"75","author":"Stott","year":"1987","journal-title":"Proc. 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