Power Quality Governance Strategy of Active Distribution Network Based on Multi-phase Optimal Power Flow

In recent years, due to the large-scale integration of distributed energy sources in active distribution networks, severe over-voltage issues have emerged. A common solution is to install reactive power compensation devices, but the application scenarios of these devices are limited. With the widespread application of energy storage and electric vehicles in distribution networks, the active power output of energy storage systems and the V2G (Vehicle-to-Grid) interaction of electric vehicles not only address issues like peak shaving and valley filling, but also the reactive power and harmonic current output by their grid-connected inverters, when capacity permits, can be used to compensate the voltage quality of the distribution network. Therefore, this paper proposes a power quality management strategy for active distribution networks based on the collaborative optimization of energy storage systems and electric vehicles. This is achieved by establishing an Optimal Power Flow (OPF) model. Additionally, an Immune Comprehensive Learning Particle Swarm Optimization (ICLPSO) algorithm is used to optimize and determine the reactive power output of energy storage systems and electric vehicles. Finally, taking the voltage issues of the IEEE 162-node distribution network with distributed PV as an example, the effectiveness of the proposed management strategy is verified.