Wattflex: AI in the energy transition

Steven Warmelink (Speaker)

System Integration in the Energy Transition

Activity: Talk or presentation › Oral presentation

Description

The generation of electrical power from renewable sources such as wind and solar power is on the rise. However, the nature of this power generation is characterized by a relatively high level of unpredictability, whereas the demand for electrical power continues to grow steadily.

These factors – among others – lead to increasing volatility in the energy markets, which in turn increases the reliance on (the flexibility of) the power grid. Given that supply and demand of electricity must always be balanced, this results in significant price fluctuations on the day ahead (EPEX) and imbalance energy markets.

In the Wattflex project, we investigated how the control / management of batteries can be used to reduce the imbalance on the electricity grid, while ensuring a valid business case for the battery owner / operator. We optimized for two scenarios: home batteries, typically combined with solar panels, and large scale batteries (1MW+) that are placed near solar parks.

By exploring different control mechanisms (algorithmic, linear programming and reinforcement learning), we get a better understanding of where and how AI can be applied in the domain, and what the limitations are.

Period	29 Nov 2024
Event title	aiGrunn: The AI tech event for software professionals
Event type	Conference
Location	Groningen, NetherlandsShow on map
Degree of Recognition	Regional

UN SDGs

This activity contributes to the following UN Sustainable Development Goals (SDGs)

SDG 07 Affordable and Clean Energy
SDG 09 Industry, Innovation, and Infrastructure

Keywords

energy transition
machine learning
battery energy storage
AI

Research Focus Areas Hanze University of Applied Sciences * (mandatory by Hanze)

Energy

Research Focus Areas Research Centre or Centre of Expertise * (mandatory by Hanze)

System Integration

Publinova themes

Technology

Documents & Links

aiGrunn
File: application/octet-stream, 54.5 MB
Type: Audiovisual

The generation of electrical power from renewable sources such as wind and solar power is on the rise. However, the nature of this power generation is characterized by a relatively high level of unpredictability, whereas the demand for electrical power continues to grow steadily. These factors – among others – lead to increasing volatility in the energy markets, which in turn increases the reliance on (the flexibility of) the power grid. Given that supply and demand of electricity must always be balanced, this results in significant price fluctuations on the day ahead (EPEX) and imbalance energy markets. In the Wattflex project, we investigated how the control / management of batteries can be used to reduce the imbalance on the electricity grid, while ensuring a valid business case for the battery owner / operator. We optimized for two scenarios: home batteries, typically combined with solar panels, and large scale batteries (1MW+) that are placed near solar parks. By exploring different control mechanisms (algorithmic, linear programming and reinforcement learning), we get a better understanding of where and how AI can be applied in the domain, and what the limitations are.