Abstract
AI-Empowered Reliable Forecasting for Energy Sectors
Recently, there has been a dramatic increase in the deployment of diverse types of intermittent renewable energy sources (RES), leading to significant energy supply variability. It should be emphasised that the characteristics of renewable energy sources can provide several obstacles to integrating large-scale renewables in transmission systems and a significant number of dispersed renewables in distribution networks. Besides, electricity demand also has considerable fluctuating nature, which is expected to be more challenging with the continued electrification of energy demand for heating and transport, besides the power to gas coupling. Accordingly, this is a global trend towards coupling energy sectors to provide more flexibility and regularity options.
In this context, reliable forecasting is an essential tool for system operators to ensure the safe and optimal operation of the energy sectors. This ambition target can be achieved by improving the dependability and precision of forecasting methodologies required while considering data uncertainty. In this regard, Artificial Intelligence (AI) and machine learning have shown powerful prediction capabilities. Accordingly, this Special Issue intends to cover the most recent advances in the forecasting task in energy sectors (generation, demand, energy prices, etc.) through the empowerment of AI.
Recently, there has been a dramatic increase in the deployment of diverse types of intermittent renewable energy sources (RES), leading to significant energy supply variability. It should be emphasised that the characteristics of renewable energy sources can provide several obstacles to integrating large-scale renewables in transmission systems and a significant number of dispersed renewables in distribution networks. Besides, electricity demand also has considerable fluctuating nature, which is expected to be more challenging with the continued electrification of energy demand for heating and transport, besides the power to gas coupling. Accordingly, this is a global trend towards coupling energy sectors to provide more flexibility and regularity options.
In this context, reliable forecasting is an essential tool for system operators to ensure the safe and optimal operation of the energy sectors. This ambition target can be achieved by improving the dependability and precision of forecasting methodologies required while considering data uncertainty. In this regard, Artificial Intelligence (AI) and machine learning have shown powerful prediction capabilities. Accordingly, this Special Issue intends to cover the most recent advances in the forecasting task in energy sectors (generation, demand, energy prices, etc.) through the empowerment of AI.
Original language | English |
---|---|
Journal | IET GENERATION TRANSMISSION AND DISTRIBUTION |
Publication status | Accepted/In press - 2022 |
MoE publication type | C2 Edited book, conference proceedings or special issue of a journal |