WP 2020-83 Variable time-step: a way to improve computational tractability for energy system models with long-term storage

ABSTRACT

Optimizing an energy system model featuring a large proportion of variable (nondispatchable) renewable energy requires a fine temporal resolution and a long period of weather data, to bring 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 are defined, during which we keep an hourly temporal resolution, because they may matter for dimensioning part of the electricity system. 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 ca.60. Results are milder for battery volume. We conclude that this variable time-step method is a research path worth following