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DC Field | Value | Language |
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dc.contributor.author | Qu, B | - |
dc.contributor.author | Wang, Z | - |
dc.contributor.author | Shen, B | - |
dc.contributor.author | Dong, H | - |
dc.date.accessioned | 2021-07-26T12:02:50Z | - |
dc.date.available | 2021-09-01 | - |
dc.date.available | 2021-07-26T12:02:50Z | - |
dc.date.issued | 2021-06-07 | - |
dc.identifier.citation | Qu, B., Wang, Z., Shen, B. and Dong, H. (2021) 'Distributed state estimation for renewable energy microgrids with sensor saturations', Automatica, 131, pp. 109730. doi: https://doi.org/10.1016/j.automatica.2021.109730. | en_US |
dc.identifier.issn | 0005-1098 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/22988 | - |
dc.description.abstract | In this paper, the distributed state estimation problem is studied for renewable energy microgrids with sensor saturations. A system model for the microgrids with sensor saturations is proposed. Attention is focused on the design of a distributed recursive estimation scheme such that, in the presence of the sensor saturations, an upper bound of the estimation error covariance is guaranteed. Subsequently, such an upper bound is minimized by appropriately designing the gain matrices of the corresponding state estimator. In particular, the sparsity of the gain matrices resulting from network topology is handled by using a matrix simplification method. Moreover, the performance evaluation of the designed distributed state estimator is conducted by analyzing the exponential boundedness of the estimation error in the mean square sense. Finally, simulation experiments under two cases are carried out on a renewable energy microgrid which contains two distributed generation units. The simulation results demonstrate that the developed state estimation scheme is effective. | en_US |
dc.description.sponsorship | This work was supported in part by the National Natural Science Foundation of China under Grants 61873148, 61922024, 61933007 and 61873058, the Program of Shanghai Academic/Technology Research Leader of China under Grant 20XD1420100, the Natural Science Foundation of Shanghai of China under Grant 18ZR1401500, the Natural Science Foundation of Heilongjiang Province of China under Grant ZD2019F001, the Fundamental Research Funds for the Central Universities, China and Graduate Student Innovation Fund of Donghua University of China under Grant CUSF-DH-D-2021046, and the Alexander von Humboldt Foundation of Germany . | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.subject | Microgrid | en_US |
dc.subject | Sensor saturations | en_US |
dc.subject | Power systems | en_US |
dc.subject | Distributed state estimation | en_US |
dc.subject | Recursive state estimation | en_US |
dc.title | Distributed state estimation for renewable energy microgrids with sensor saturations | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.1016/j.automatica.2021.109730 | - |
dc.relation.isPartOf | Automatica | - |
pubs.publication-status | Published | - |
pubs.volume | 131 | - |
Appears in Collections: | Dept of Computer Science Embargoed Research Papers |
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