Balancing uncertainties in future electricity markets

Just how fast quickly the transition to energy consumption will be in the future, cannot be predicted. What is clear, however, is it will need to rely on smart networks. These networks are designed to deal with a varying supply of (and demand for) renewable energy. This contrasts with the current energy market, which still heavily relies on the more or less constant supply of energy from fossil sources. Certainly as more and more consumers become energy suppliers themselves, these fluctuations can have major consequences for the way in which we have to organise our electricity networks.

Novel electricity tariff
CWI researcher Georgios Methenitis designed various approaches to balance out uncertainties. Using tools from game theory and mechanism design, he studied interactions between strategic users and derived optimal strategies under the presence of uncertainty.

One of the mechanisms designed by Methenitis to balance uncertainties, is a novel electricity tariff. Such a tariff could reduce the uncertainty of customers’ demand and thus high costs and CO₂ emissions related to last-minute balancing between supply and demand in electricity systems.

Service level agreement
Another mechanism aims to encourage flexible electricity users to reduce their demand as a last-minute balancing strategy when demand exceeds the planned supply. Finally, Methenitis proposes a design of a service-level agreement (SLA) framework that enables trading of uncertain electricity quantities (e.g., from wind generation). This framework also considers the criticality of the demand of each electricity user.

Efficient outcomes for all users
“My research provides building blocks for future electricity markets that guarantee efficient outcomes for all users”, says Methenitis. “The results can be used as components of future electricity systems, which are characterized by the increasing uncertainty on both demand and supply and actively participating users. In addition, they provide insights that transfer to the design and analysis of general systems with similar characteristics of uncertainty in resource allocation.”

Methenitis performed his research at CWI’s Intelligent and Autonomous Systems group. His research was supervised by Han La Poutré and Michael Kaisers.