Variable time-step: A method for improving computational tractability for energy system models with long-term storage

Abstract

Optimizing an energy system model featuring a large proportion of variable (non-dispatchable) renewable energy requires a fine temporal resolution and a long period of weather data to provide robust results. Many models are optimized over a limited set of 'representative' periods (e.g. weeks) but this precludes a realistic representation of long-term energy storage.To tackle this issue, we introduce a new method based on a variable time-step. Critical periods that may be important for dimensioning part of the electricity system are defined, during which we use an hourly temporal resolution. For the other periods, the temporal resolution is coarser. This method brings very accurate results in terms of system cost, curtailment, storage losses and installed capacity, even though the optimization time is reduced by a factor of around 60. Results are less accurate for battery volume. We conclude that further research into this 'variable time-step' method would be worthwhile.

Do multi-sector energy system optimization models need hourly temporal resolution? A case study with an investment and dispatch model applied to France

“…Similarly, the coarser-than-hourly time-slices are based on simple division of 24 hours of a day to two-hour, four-hour and eight-hour long time-steps with no particular consideration of variable time-step choice for a day as we did previously for an electricity-only model (De Guibert et al, 2020). The performance of the resolution variation methods could be improved by smarter sub-sampling of daily time-steps.…”

“…This choice is justified by the literature: on the one hand, if the size of the modeled area is that of a large European State, hourly resolution suffices since for both wind and solar generation, sub-hourly fluctuations, which are significant at the local scale, cancel each other out (Brown et al, 2018b, and references therein). On the other hand, with a temporal resolution coarser than one hour, demand peaks and wind or solar generation troughs are smoothed, resulting in an underestimation of the generation and storage capacities necessary to satisfy electricity demand (Pfenninger, 2017, De Guibert et al, 2020.…”

“…**Methanation is the combination of hydrogen production from electrolysis and the Sabatier reaction of green CO2 as a by-product from methanization with the hydrogen produced, therefore the economic parameters of each production are presented as electrolysis/Sabatier. ***As in Shirizadeh et al (2020). Table 5 shows the economic parameters for the two types of vehicle engine technologies considered, internal combustion engines fueled with compressed gas and electric vehicles.…”

Reducing climate risk in energy system planning: a posteriori time series aggregation for models with storage

“…Constraints linking periods, such as storage, complicate time series aggregation since they require chronology of representative periods to be preserved. A number of solutions have been proposed; they include merging only periods that are adjacent chronologically (Pineda & Morales, 2018;Tso et al, 2020;De Guibert et al, 2020), aggregating periods from different parts of the year separately (Welsch et al, 2012;Samsatli & Samsatli, 2015;Timmerman et al, 2017), and linking storage levels between representative periods (Gabrielli et al, 2018;Tejada-Arango et al, 2018;Kotzur et al, 2018b;van der Heijde et al, 2019;Novo et al, 2022).…”

Long-term optimization of the hydrogen-electricity nexus in France: Green, blue, or pink hydrogen?

“…Therefore, we develop a model to analyse simultaneously the optimal hydrogen and electricity production mixes. The model, labelled EOLES_elec_H 2 , belongs to the EOLES (Energy Optimisation for Low-emission Energy Systems) family (De Guibert et al, 2020;Shirizadeh et al 2020;Quirion, 2021, 2022). It optimises investment in, and dispatch of, production and storage options, minimising the annualised cost while satisfying electricity demand every hour for one year, subject to a zero net CO 2 emissions constraint.…”