Research and Development in Digital Power Engineering

Our Research: Short-Term Electricity Demand Forecasting

Alina Igorevna Stepanova and Alexandra Ilmarovna Khalyasmaa of our Digital Twins in Electric Power Engineering Laboratory have developed a new method for short-term electricity demand forecasting at a gas industry enterprise.

The approach applies machine learning methods that account for meteorological, production-related, and other factors, as well as relationships between them.

The new forecasting method is intended to improve enterprises' energy efficiency and support the safe operation of critical gas industry infrastructure.

The research findings were published in the scientific journal Algorithms.