In recent years, with the increasing penetration of renewable energy sources (RES), the generation of electricity has become more uncertain. As this integration is only expected to increase, the uncertainty in the power grid will become worse.

As electricity consumption has to equal electricity generation at all times, increasing uncertainty in electricity generation leads to electricity markets that display highly volatile prices with sudden and unexpected price peaks. In this context, accurate price forecasting is paramount to ensure further integration of RES into the electricity grid by guarantying their profitability and reducing the associated market risks.

In this talk, we will cover the main approaches and techniques when it comes to forecasting prices. We will start the talk with a brief introduction to the field of price forecasting. Then, we will talk about the three main types of forecasting methods: point forecasting, probability forecasting, and scenario forecasting. In particular, we will discuss the merits and disadvantages of these three classes, and we will provide some particular examples of methods belonging to these families.

At the end, we will also discuss the importance of market integration in forecasting electricity prices, and the role of deep learning techniques in the context of point forecasting.

We look forward to seeing you there! Lunch is free but registration mandatory via :