Probabilistic Hosting Capacity and Operating Reserve Calculation in Renewable-rich Distribution Networks

Maximization of renewable energy penetration plays a vital role in boosting green energy integration and system operational safety. As the most popular renewable energy, the assessment of hosting capacity (HC) of photovoltaic (PV) generation and operating reserve (OR) can provide valuable information for network planning. In this paper, an artificial neural network (ANN) forecast method is developed for predicting load demand and PV generation. Monte Carlo (MC) simulation of power flow is calculated based on predictions of various load and PV generation combination to obtain the maximum HC and OR considering voltage, loading, and reverse power flow constraints. The simulation results show that the methodology can indicate the actual power flow of the next 24 hours to estimate the maximum capability of PV integration and OR in a distribution network. The probabilities analysis can help network operators maintain safe operation to avoid further degradation caused by the intermittent renewable generation.