dispatch

Uncertainty Reduction in Smart Energy Systems (URSES)
Contact: Dr. Phuong Nguyen
[email protected]
DISPATCH
Prof. Martha Roggenkamp
Distributed Intelligence for Smart Power routing and mATCHing
Prof. Gerard Smit
[email protected]
[email protected]
OBJECTIVE
ABOUT
The DISPATCH project aims to develop a decentralised
implicit interaction framework for market and network
control mechanisms to overcome the uncertainty
challenges introduced by the upcoming energy transition.
 Project period: 4 years
 Total budget: 1 M€ (750 k€ funding for 3 PhDs, 1 Postdoc)
 How to improve market efficiency considering network
constraints in SES?
 How to improve network reliability considering market impacts in
SES?
 What are the possible organizational and legal arrangements to
enable the transition to SES?
CONCEPT & RESEARCH PLAN
Volume
EM/DSM
Scheduling
Fast actions
Planning
Slow actions
EMS/PFC
[real-time]
[seconds – minutes]
[minutes – hours]
[day ahead]
CURRENT PROGRESS
Energy market – demand/supply matching
(EM/DSM)
Interaction framework
Challenges:
o Mapping USEF to DISPATCH
o Flexibility to compensate uncertainty
o Forecasting/planning with uncertainty, coarse in time (15
min. intervals)
o Not taking geographical situation into account
Proposed solutions:
o Establishment of a finer grained schedule during
execution of the coarse grained schedule
o Integration of geographical and network constraints
Organisational and legal arrangements
Energy Management System – Power Flow
Control (EMS/PFC)
Challenges:
Challenges:
o Analysis of current legislation and possible
organizational changes for SES
o Limited monitoring capability in the distribution networks
o Centralized control strategies not suitable with
distributed energy resources
Proposed solutions:
o Design of standards for new and different
actors/entities in the energy sector
/ Electrical Energy System (EES) group / Department of Electrical Engineering
Proposed solutions:
o Simulation framework for performance assessment of
new monitoring and control applications
o Interaction with energy markets for better prediction of
system states and more optimal network operation