Start-Up and Shut-Down Capabilities in Unit Commitment Model with Fully Flexible Temporal Resolution
Effects of Including Start-Up and Shut-Down Ramping Constraints in the Tulipa Energy Model
K. Sperczyński (TU Delft - Electrical Engineering, Mathematics and Computer Science)
M.B. Elgersma – Mentor (TU Delft - Algorithmics)
G.A. Morales-España – Mentor (TU Delft - Algorithmics)
J.E.A.P. Decouchant – Graduation committee member (TU Delft - Data-Intensive Systems)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
The transition of the energy grid into a system with higher
shares of renewable energy production requires careful investment planning
while considering operational characteristics of generators. Generation
Expansion Planning (GEP) is used for finding optimal investments, while Unit
Commitment (UC) can be used to limit generator operational capabilities, such
as via ramping limits, for more accurate modelling. The system may be extended
to model custom thermal generator capabilities at the time of their start-up or
shut-down, where they may differ from traditional ramping, promoting more
precise modelling. However, the inclusion of such detail requires careful
managing of model complexity to keep solving time feasible, which can be done
with techniques such as Clustered Unit Commitment (CUC), and clustering time
blocks while allowing flexible resolution combinations. The latter is known as
Fully Flexible Temporal Resolution, and promises managing of model complexity
via temporal resolution reductions, while maintaining modelling versatility.
The paper targets the unexplored area of including Start-Up and Shut-Down
(SU/SD) capability ramping limits alongside a fully flexible temporal
resolution in a GEP & CUC model, and contributes by examining the effect of
the new capabilities on the run times, investment and operational solutions, and
the total system cost of a model with enabled Battery Energy Storage System (BESS)
investments. The resulting findings show that the inclusion of the SU/SD
capabilities has little effect on the investments and total cost of the model,
significantly increases computation time, yet has a noticeable effect on the
operational schedule of generators.