Finished Assignments

Combining TRIANA and PowerMatcher

Master's assignment

Student: Jorrit Nutma
Supervisors: Albert Molderink, Gerwin Hoogsteen
Programme: Embedded Systems - University of Twente    

In order to cope with the upcoming challenges in the electricity distribution net, which are mainly caused by the large-scale introduction of renewable energy sources and envisioned rise of electric vehicles, ICT can be used to make our distribution grid smarter. Smart methodologies to control flexible loads, such as heat pumps, smart washing machines, and electric vehicles, are being developed currently. In The Netherlands, pilot project are running in which The PowerMatcher methodology is used as a Demand Side Management (DSM) approach. The approach is effective and the pilots show promising result. However, the PowerMatcher approach does not always exploit flexibility at the right moments. The Triana approach uses, in contrast, predictions and a planning which gives more steering to the cluster. In this way, Triana gives better guidance about what an optimal operation of the cluster is.

As we see that The PowerMatcher and Triana both have strengths and weaknesses, it is interesting to study how a combined approach would perform. Therefore, this assignment is about combining the two approaches in the sense that the Triana planning, based on the Triana predictions, is used in the PowerMatcher real-time control approach.

There are globally two possibilities for the combination, which are being compared in the assignment. One is to use a global planning at auctioneer level only (the auctioneer is a PowerMatcher term, click here for more information). The other option is to use a planning at device level such that devices create their bidding functions on basis of a device-specific plan (again, the bidding function is a PowerMatcher term). For the second option, we created a novel bidding strategy.