Effect of modelling choices in the unit commitment problem

Abstract

In power system studies the unit commitment problem (UC) is solved to support market decisions and assess system adequacy. Simplifications are made to solve the UC faster, but they are made without considering the consequences on solution quality. In this study we thoroughly investigated the impacts of simplifications on solution quality and computation time on a benchmark set consisting of almost all the available instances in the literature. We found that omitting the minimum up- and downtime and simplifying the startup cost resulted in a significant quality loss without reducing the computation time. Omitting reserve requirements, ramping limits and transmission limits reduced the computation time, but degraded the solution significantly. However, the linear relaxation resulted in less quality loss with a significant speed-up and resulted in no difference when unserved energy was minimized. Finally, we found that the average and maximum capacity factor difference is large for all model variants.

Linking Unserved Energy to Weather Regimes

“…Because specific modelling choices in the UCED have an effect on the decision variables and outcomes of the simulation (R. Wuijts et al, 2023), model choices matter. For instance, the fixed storage level at start and end of the year might limit the use of storage in times of need, although similar assumptions are made in the ENTSO-E (2021).…”

“…The UCED may incorporate many types of technical constraints, of which some can be omitted depending on the purpose of the study (R. Wuijts et al, 2023). We therefore can use a simplified model which includes fewer constraints regarding the flexibility of thermal power plants.…”

“…Model characteristics often included in the UCED problem such as ramping limits, minimum uptime, and binary commitment variables, are unnecessary when you are only interested in energy not served (R. Wuijts et al, 2023). This was validated by running multiple months with 4 different models of varying degree in detail and similar values of ENS where found (see Appendix E).…”

“…We assume that most model characteristics normally included in the unit commitment problem such as ramping limits, minimum uptime, and binary commitment variables, are unnecessary when you are only interested in energy not served (R. Wuijts et al, 2023). To validate this assumption, we ran four models with two different objective functions and two levels of detail to check whether this results in equivalent solutions.…”

The climatological renewable energy deviation index (credi)

“…Energy system models are vital to capture the impact of this variability [4]. However, their complexity results in high computational burdens that grows exponentially with the simulation period [1,[5][6][7][8]. Incorporating large climate datasets that capture energy-meteorological variability in operational hourly energy system models is thus, as of yet, unfeasible [1,7,9].…”