Zhang, J, Zhang, B, Li, Q et al. (4 more authors) (2022) Fast Frequency Regulation Method for Power System with Two-Stage Photovoltaic Plants. IEEE Transactions on Sustainable Energy, 13 (3). pp. 1779-1789. ISSN 1949-3029
Abstract
The full utilization of solar energy is of great significance in reducing carbon emissions and alleviating environmental problems. Fast frequency regulation plays an important role in the power system with grid-connected two-stage photovoltaic (PV) plants. The presented fast frequency regulation method is composed of droop control, virtual inertia control and de-loading control. This work focuses on improving droop control and virtual inertia control for PV plants connected to grid. Due to non-Gaussian disturbance induced by solar irradiance, an adaptive control strategy is proposed by minimizing an improved performance index which combines the mean square error (MSE) and the minimum error entropy (MEE) criteria. Based on the collected frequency deviation series data, the entropy of the frequency deviation is estimated with the aid of a quantizer. The droop control coefficient and inertia gain are then solved by an improved gravitational search algorithm (IGSA). Finally, the effectiveness of the proposed strategy is testified by an illustrative power system with a two-stage grid-connected PV plant.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Frequency regulation, gravitational search algorithm, particle swarm optimization, photovoltaic |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 13 May 2022 13:19 |
Last Modified: | 17 Feb 2023 15:31 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/TSTE.2022.3175662 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:186735 |