Regression model-based adaptive receding horizon control of soft open points for loss minimization in distribution networks

•A new decentralized operation of SOP using the polynomial regression model.•Adaptive MPC framework of SOP by modeling the plant as a linear time-variant system.•Superior performance in minimizing network losses and improving voltage profile. This study proposes a method of using a soft open point (...

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Veröffentlicht in:International journal of electrical power & energy systems 2023-09, Vol.151, p.109130, Article 109130
Hauptverfasser: Han, Changhee, Cho, Seokheon, Song, Sung-Geun, Rao, Ramesh R.
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Sprache:eng
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Zusammenfassung:•A new decentralized operation of SOP using the polynomial regression model.•Adaptive MPC framework of SOP by modeling the plant as a linear time-variant system.•Superior performance in minimizing network losses and improving voltage profile. This study proposes a method of using a soft open point (SOP) to flexibly connect different distribution networks. A novel operation strategy of SOP using a model predictive control (MPC) framework that adheres to the adaptive receding horizon control rule is developed to effectively respond to volatile renewable energy resources. Notably, the proposed method models the plant corresponding to voltage and network losses as a linear time-variant system, which provides better performance than the conventional MPC method in reducing network losses and improving voltage profile. To minimize the need for network observation of distribution system operators, we propose a process of deriving voltage-to-power and network loss-to-power sensitivity using a polynomial regression model. The effectiveness of the proposed strategy is verified on the modified IEEE 33-bus test systems, and its superiority is demonstrated through performance comparison with the existing general MPC method.
ISSN:0142-0615
1879-3517
DOI:10.1016/j.ijepes.2023.109130