DocumentCode
574310
Title
Optimal dispatch strategy for the Agile Virtual Power Plant
Author
Petersen, Mark ; Bendtsen, Jan ; Stoustrup, Jakob
Author_Institution
Dept. of Electron. Syst., Aalborg Univ., Aalborg, Denmark
fYear
2012
fDate
27-29 June 2012
Firstpage
288
Lastpage
294
Abstract
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.
Keywords
power generation dispatch; power plants; production planning; quadratic programming; renewable energy sources; MPC-strategy; agile virtual power plant; base load production planning; maneuverability; optimal dispatch; optimal dispatch strategy; power system; production technologies; quadratic program; renewable energy; renewable power production; Dispatching; Optimization; Portfolios; Power generation; Power systems; Production; Schedules;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2012
Conference_Location
Montreal, QC
ISSN
0743-1619
Print_ISBN
978-1-4577-1095-7
Electronic_ISBN
0743-1619
Type
conf
DOI
10.1109/ACC.2012.6314895
Filename
6314895
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