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An Online Feedback-Based Linearized Power Flow Model for Unbalanced Distribution Networks

Rui Cheng, Zhaoyu Wang, Yifei Guo

2021IEEE Transactions on Power Systems19 citationsDOI

Abstract

The nonlinear and nonconvex nature of ac power flow challenges the analysis and optimization of unbalanced distribution networks. To tackle this issue, this paper proposes an online feedback-based linearized power flow model for unbalanced distribution networks with both wye-connected and delta-connected loads. The online feedback-based linearized model is grounded on the first-order Taylor expansion of the branch flow model (BFM), and updates the model parameters via online feedback by leveraging the instantaneous measurements of voltages and load consumption. Exploiting the connection structure of unbalanced radial distribution networks, we also provide a unified matrix-vector compact form of the model. The numerical tests on the IEEE 123-bus test system validate its accuracy and superiority compared with other offline BFM methods. Additionally, we apply the proposed model to the optimal power flow for voltage regulation, which further demonstrates its effectiveness.

Topics & Concepts

Control theory (sociology)AC powerNonlinear systemPower flowFlow (mathematics)Power (physics)Mathematical optimizationVoltagePower-flow studyComputer scienceMatrix (chemical analysis)Electric power systemEngineeringMathematicsElectrical engineeringPhysicsComposite materialGeometryMaterials scienceControl (management)Artificial intelligenceQuantum mechanicsOptimal Power Flow DistributionMicrogrid Control and OptimizationPower System Optimization and Stability