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

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초록

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. © 2023 Elsevier Ltd

키워드

Distribution networkLoss minimizationModel predictive controlOptimizationReceding horizon controlSoft open pointSurface fittingACTIVE DISTRIBUTION NETWORKSCOORDINATED VOLTAGE/VAR CONTROLCONTROL STRATEGYREACTIVE POWEROPERATIONOPTIMIZATIONPENETRATIONGENERATIONDEVICESIMPACT
제목
Regression model-based adaptive receding horizon control of soft open points for loss minimization in distribution networks
저자
Han, ChangheeCho, SeokheonSong, Sung-GeunRao, Ramesh R.
DOI
10.1016/j.ijepes.2023.109130
발행일
2023-09
유형
정기학술지(Article(Perspective Article포함))
저널명
International Journal of Electrical Power and Energy Systems
151