Distributed Model Predictive Control for Voltage Coordination of Distributed Photovoltaic Distribution Networks with High Permeability

Jianfeng  Yang; Shikun  Zhu; Tao  Zhou

doi:10.6180/jase.202506_28(6).0016

Distributed Model Predictive Control for Voltage Coordination of Distributed Photovoltaic Distribution Networks with High Permeability

Jianfeng Yang, Shikun ZhuThis email address is being protected from spambots. You need JavaScript enabled to view it., and Tao Zhou

School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China

Received: May 21, 2024
Accepted: July 30, 2024
Publication Date: September 19, 2024

Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202506_28(6).0016

With large-scale distributed photovoltaic (DPV) access to the distribution network, the problems of node voltage overruns and increased network losses, as well as the traditional centralized control with low reliability, high computational and communication pressure, and poor scalability, can no longer meet the requirements of distribution network operation and control in the context of the increasing DPV penetration. To this end, a collaborative optimal control strategy for PV distribution networks based on distributed model predictive control (DMPC) is proposed for fast recovery of voltage overruns and reduction of network losses. Firstly, based on the analysis of voltage overruns in distribution networks containing distributed PV, a voltage control model of the PV system is established and a distributed model predictive controller is designed. The controller solves for the control quantities of each region through the state and prediction information in the system, while considering the coupling information of adjacent control regions to achieve the cooperative optimization of the control objectives. Secondly, the distributed PV active and reactive power output constraints as well as capacity limitations are considered, and the objective function is transformed into a quadratic constrained quadratic programming (QCQP) problem to solve the control commands to achieve the optimal control of the PV distribution network. Finally, the effectiveness and applicability of the proposed optimal control strategy are verified through the simplified topology of actual distribution lines in a region of Gansu Province as an example simulation.

Keywords: Distribution network; Distributed photovoltaic; Distributed model predictive control; Voltage overrun; Power loss

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