TY - GEN
T1 - A Taxonomy for Modeling Flexibility and a Computationally Efficient Algorithm for Dispatch in Smart Grids
AU - Petersen, Mette Højgaard
AU - Edlund, Kristian
AU - Hansen, Lars Henrik
AU - Bendtsen, Jan Dimon
AU - Stoustrup, Jakob
PY - 2013
Y1 - 2013
N2 - The word flexibility is central to Smart Grid literature, but still a formal definition of flexibility is pending. This paper present a taxonomy for flexibility modeling denoted Buckets, Batteries and Bakeries. We consider a direct control Virtual Power Plant (VPP), which is given the task of servicing a portfolio of flexible consumers by use of a fluctuating power supply. Based on the developed taxonomy we first prove that no causal optimal dispatch strategies exist for the considered problem. We then present two heuristic algorithms for solving the balancing task: Predictive Balancing and Agile Balancing. Predictive Balancing, is a traditional moving horizon algorithm, where power is dispatched based on perfect predictions of the power supply. Agile Balancing, on the other hand, is strictly non-predictive. It is, however, explicitly designed to exploit the heterogeneity of the flexible consumers. Simulation results show, that in spite of being non-predictive Agile Balancing can actually out-perform Predictive Balancing even when Predictive Balancing has perfect prediction over a relatively long horizon. This is due to the flexibility synergy effects, which Agile Balancing generates. As a further advantage it is demonstrated, that Agile Balancing is extremely computationally efficient since it is based on a sorting.
AB - The word flexibility is central to Smart Grid literature, but still a formal definition of flexibility is pending. This paper present a taxonomy for flexibility modeling denoted Buckets, Batteries and Bakeries. We consider a direct control Virtual Power Plant (VPP), which is given the task of servicing a portfolio of flexible consumers by use of a fluctuating power supply. Based on the developed taxonomy we first prove that no causal optimal dispatch strategies exist for the considered problem. We then present two heuristic algorithms for solving the balancing task: Predictive Balancing and Agile Balancing. Predictive Balancing, is a traditional moving horizon algorithm, where power is dispatched based on perfect predictions of the power supply. Agile Balancing, on the other hand, is strictly non-predictive. It is, however, explicitly designed to exploit the heterogeneity of the flexible consumers. Simulation results show, that in spite of being non-predictive Agile Balancing can actually out-perform Predictive Balancing even when Predictive Balancing has perfect prediction over a relatively long horizon. This is due to the flexibility synergy effects, which Agile Balancing generates. As a further advantage it is demonstrated, that Agile Balancing is extremely computationally efficient since it is based on a sorting.
U2 - 10.1109/ACC.2013.6579991
DO - 10.1109/ACC.2013.6579991
M3 - Article in proceeding
SN - 978-1-4799-0178-4
T3 - American Control Conference
SP - 1150
EP - 1156
BT - American Control Conference (ACC), 2013
PB - American Automatic Control Council
T2 - The 2013 American Control Conference
Y2 - 17 June 2013 through 19 June 2013
ER -