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Abstract
To solve the problems caused by the intermittent
generation of Renewable Energy Sources, the concept of energy
flexibility is of utmost importance, and batteries are devices
with high potential in this regard. However, current exact
mathematical models specifying battery flexibility cannot scale
(exponentially growing runtime) with long time horizons and
many batteries. In this paper, we propose to use the FlexOffer
(FO) model for this purpose, because: 1) FO is a general model,
capturing all types of flexible assets in a unified format and 2)
being approximate, it scales very well in terms of number of
devices and time horizons. First, we describe the different types
of FOs: standard, total-energy constraint and dependency-based
(DFOs). Then, we present and discuss FO generation techniques,
and provide an analytic method for generating DFOs. Finally, we
perform simulations for measuring flexibility in economic terms
and time needed for optimization and aggregation. We show that
DFOs retain most of the flexibility, while vastly outperforming
exact models in optimization and aggregation speed.
generation of Renewable Energy Sources, the concept of energy
flexibility is of utmost importance, and batteries are devices
with high potential in this regard. However, current exact
mathematical models specifying battery flexibility cannot scale
(exponentially growing runtime) with long time horizons and
many batteries. In this paper, we propose to use the FlexOffer
(FO) model for this purpose, because: 1) FO is a general model,
capturing all types of flexible assets in a unified format and 2)
being approximate, it scales very well in terms of number of
devices and time horizons. First, we describe the different types
of FOs: standard, total-energy constraint and dependency-based
(DFOs). Then, we present and discuss FO generation techniques,
and provide an analytic method for generating DFOs. Finally, we
perform simulations for measuring flexibility in economic terms
and time needed for optimization and aggregation. We show that
DFOs retain most of the flexibility, while vastly outperforming
exact models in optimization and aggregation speed.
| Original language | English |
|---|---|
| Title of host publication | IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) 2021 |
| Number of pages | 7 |
| Place of Publication | Aachen, Germany |
| Publisher | IEEE |
| Publication date | 28 Oct 2021 |
| Pages | 64-70 |
| Article number | 9631999 |
| ISBN (Print) | 978-1-6654-3044-9 |
| ISBN (Electronic) | 978-1-6654-1502-6 |
| DOIs | |
| Publication status | Published - 28 Oct 2021 |
| Event | International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) - Aachen, Germany Duration: 25 Oct 2021 → 28 Oct 2021 |
Conference
| Conference | International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) |
|---|---|
| Country/Territory | Germany |
| City | Aachen |
| Period | 25/10/2021 → 28/10/2021 |
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- 2 Finished
-
domOS: Operating System for Smart Services in Buildings
Skou, A., Nielsen, B., Pedersen, T. B. & Thomsen, C.
01/09/2020 → 31/08/2023
Project: Research
-
FEVER: Flexible Energy Production, Demand and Storage-based Virtual Power Plants for Electricity Markets and Resilient DSO Operation
Skou, A., Pedersen, T. B., Skov, M. B., Chakraborty, N., Jensen, R. H. & Raptis, D.
01/02/2020 → 31/07/2023
Project: Research