Voltage Risk Assessment of Distribution Network with Photovoltaic Intergration Based on Parallel Computing

Abstract

Voltage fluctuations in distribution networks are usually caused by the stochastic volatility of photovoltaic generation system and load. The traditional deterministic power flow calculation method is difficult to assess the voltage risk. Moreover, traditional serial computing technologies cannot provide rapid voltage risk assessment of large-scale distribution networks. To address these problems, the probabilistic characteristics of PV generation and load fluctuations are first analyzed. Then, the corresponding probabilistic model is established based on the Newton-Raphson algorithm. Finally, an indicator to evaluate voltage risk is proposed by using the Monte-Carlo simulation. In order to meet the computing speed requirement imposed by large-scale distribution networks, a parallel computing platform based on Apache Spark is designed, and a parallel implementation of the Monte-Carlo simulation on Spark Resilience Distributed Datasets (RDD) is established. Simulation results based on real-world data illustrate the effectiveness of the proposed voltage risk assessment for large-scale distribution power networks and its computational efficiency.