Applications of AI-Based Forecasts in Renewable Based Electricity Balancing Markets

Rising environmental concerns are integrating more renewables in power systems. This increase introduces uncertainty in generation and makes it challenging to maintain a balance between demand and supply. To avoid balancing problems and consequent stability issues, better forecast models are needed as traditional techniques are not fully equipped to deal with these new challenges. Thus, artificial intelligence (AI) based forecast techniques are gaining potential recognition in the realm of electricity markets. This paper aims at investigating the state-of-art of AI applications for price forecasts in electricity balancing markets (EBMs). The focus of previous studies extended in this direction has been towards the dayahead markets, whereas studies targeting EBMs are rather scarce. This paper shows how AI-based forecasts support EBMs modeling, resulting in more secure grid integration of distributed technologies. The benefits driven from such forecasts by market participants like brokers and customers are also investigated.