Conformal Multilayer Perceptron-Based Probabilistic Net-Load Forecasting for Low-Voltage Distribution Systems with Photovoltaic Generation

This paper presents a probabilistic forecasting approach tailored for low voltage (LV) substations, offering short-term predictions for three crucial variables: voltage, reactive power, and active power. These parameters play a vital role in the resilience of distribution systems, especially in the presence of Distributed Energy Resources (DERs).

forecasting
probabilistic
machine learning
low voltage network
Author

Anthony Faustine and Pereira, Lucas

Published

September 11, 2024

Doi

10.1049/icp.2024.2555

Abstract

This paper presents a probabilistic forecasting approach tailored for low voltage (LV) substations, offering short-term predictions for three crucial variables: voltage, reactive power, and active power. These parameters play a vital role in the resilience of distribution systems, especially in the presence of Distributed Energy Resources (DERs).

Presented at the 2024 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), Oslo, Norway