Robust model predictive control based voltage regulation method for a distribution system with renewable energy sources and energy storage systems
•A RMPC based voltage regulation scheme is proposed to coordinate RES, ESS and OLTC considering uncertainty of RES outputs.•The RMPC-based nonlinear model is transformed to a quadratic programming problem using the strong duality theory.•The efficiency of the RMPC-based voltage regulation model is v...
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Veröffentlicht in: | International journal of electrical power & energy systems 2020-06, Vol.118, p.105749, Article 105749 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •A RMPC based voltage regulation scheme is proposed to coordinate RES, ESS and OLTC considering uncertainty of RES outputs.•The RMPC-based nonlinear model is transformed to a quadratic programming problem using the strong duality theory.•The efficiency of the RMPC-based voltage regulation model is validated using a real Finnish distribution network.
With the integration of high penetration renewable energy sources (RESs) in distribution networks, the uncertainty of RES outputs brings a great challenge for the voltage regulation of distribution systems. This paper proposes a method based on robust model predictive control (RMPC) for voltage regulation by optimally coordinating the reactive power outputs of the RESs, energy storage systems and on-load tap changers (OLTCs). By considering the prediction error of the RES active outputs, the voltage regulation problem is formulated as a multitime period robust optimization model to obtain the optimal control actions in the prediction horizon. The control actions for the first time period are applied to the distribution network. Since the RMPC-based optimization model is nonlinear, it is linearized and transformed into a quadratic programming model that can be solved effectively by commercial software. The effectiveness of the proposed method is demonstrated in a real Finnish distribution network model. |
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ISSN: | 0142-0615 1879-3517 |
DOI: | 10.1016/j.ijepes.2019.105749 |