By Topic

Optimal dispatch strategy for the Agile Virtual Power Plant

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Mette Petersen ; Department of Electronic Systems, Automation and Control, Aalborg University, Denmark ; Jan Bendtsen ; Jakob Stoustrup

The introduction of large ratios of renewable energy into the existing power system is complicated by the inherent variability of production technologies, which harvest energy from wind, sun and waves. Fluctuations of renewable power production can be predicted to some extent, but the assumption of perfect prediction is unrealistic. This paper therefore introduces the Agile Virtual Power Plant. The Agile Virtual Power Plant assumes that the base load production planning based on best available knowledge is already given, so imbalances cannot be predicted. Consequently the Agile Virtual Power Plant attempts to preserve maneuverability (stay agile) rather than optimize performance according to predictions. In this paper the imbalance compensation problem for an Agile Virtual Power Plant is formulated. It is proved formally, that when local units are power and energy constrained integrators a dispatch strategy exists, which is optimal regardless of future load/imbalances. The optimal dispatch is obtained at each sample by solving a quadratic program. Finally a simulation example illustrates the optimal dispatch strategy and compares the performance with a (non-optimal) MPC-strategy.

Published in:

2012 American Control Conference (ACC)

Date of Conference:

27-29 June 2012