Analysis of virtual power plant performance for voltage stability in distribution networks with high DER penetration using PowerFactory-Python co-simulation: An Aotearoa New Zealand case study
Abstract
The way power systems operate is being reshaped by the high penetration of distributed energy resources (DERs) such as rooftop solar, batteries and electric vehicles in low-voltage distribution networks. These technologies, although beneficial for decentralization and decarbonization, pose significant technical challenges-including voltage rise, frequency fluctuations and bidirectional power flow. Virtual Power Plants (VPPs) are emerging as a promising framework to aggregate, manage and optimize the operation of DERs through intelligent control and coordination. The objective of this research is to analyse the use of Virtual Power Plants (VPPs) to coordinate DERs and enhance voltage stability in low-voltage distribution networks. The study uses an IEEE 13-bus test feeder, modelled in DIgSILENT PowerFactory, incorporating photovoltaic generation, battery energy storage systems, and electric vehicle loads under varying penetration levels. A PowerFactory-Python co-simulation framework is developed using a supervisory iterative approach, where quasi-dynamic simulations are analysed and used to update the control setpoints across successive runs. The results demonstrate that coordinated control of DERs can significantly improve voltage profiles, with voltage levels reduced from peak values above 1.05 pu within limits of approximately 0.99–1.03 pu. Battery energy storage systems provide effective voltage support, while demand-response flexible loads and photovoltaic curtailment act as a secondary control measure. However, the approach is constrained by limited storage capacity and the lack of real-time control implementation. To address these limitations, a reinforcement learning-based control framework is proposed as a future enhancement for adaptive and scalable VPP operation in New Zealand’s evolving distribution networks.