Open Access

ARTICLE

Koopman-WNN Based MPC for Hierarchical Optimal Voltage and Network Power Loss Control in ADNs

Wenfei Yi¹, Mingzhong Zheng¹, Jiayi Wang², Hao Yang^2,*, Zhenglong Sun²

1 Electric Power Research Institute, State Grid Jiangsu Electric Power Company, Nanjing, 211103, China
2 Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education, Northeast Electric Power University, Jilin, 132012, China

* Corresponding Author: Hao Yang. Email:

Energy Engineering 2026, 123(4), 4 https://doi.org/10.32604/ee.2025.072770

Received 03 September 2025; Accepted 03 November 2025; Issue published 27 March 2026

Abstract

With the growing integration of renewable energy sources (RESs) and smart interconnected devices, conventional distribution networks have turned to active distribution networks (ADNs) with complex system model and power flow dynamics. The rapid fluctuation of RES power may easily result in frequent voltage violation issues. Taking the flexible RES reactive power as control variables, this paper proposes a two-layer control scheme with Koopman wide neural network (WNN) based model predictive control (MPC) method for optimal voltage regulation and network loss reduction. Based on Koopman operator theory, a data-driven WNN method is presented to fit a high-dimensional linear model of power flow. With the model, voltage and network loss sensitivities are computed analytically, and utilized for ADN partition and control model formulation. In the lower level, a dual-mode adaptive switching MPC strategy is put forward for optimal voltage control and network loss optimization in each individual partition to decide the RES reactive power. The upper level is to calculate the adjustment coefficients of the RES reactive power given in the low level by taking the coupling effects of different partitions into account, and then the final reactive power dispatches of RESs are obtained to realize optimal control of voltage and network loss. Simulation results on two ADNs demonstrate that the proposed strategy can reliably maintain the voltage at each node within the secure range, reduce network power losses, and enhance the overall system security and economic efficiency.

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Keywords

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