Impact of the level of temporal and operational detail in energy-system planning models

By K. Poncelet, E. Delarue, D. Six, J. Duerinck, W. D’haeseleer. 2016

328 citations recorded by the source corpus.

To limit the computational cost, bottom-up long-term (LT) energy-system planning models typically have a stylized temporal representation and do not consider techno-economic operational constraints of power plants. Both these simplifications have been shown to have a significant impact on the results. However, increasing the level of temporal and techno-economic operational detail will result in an increased computational cost. In this regard, the first goal of this work is to quantify which of these simplifications has the highest impact on the results, and should therefore be prioritized for improving. To do so, the impact of both the low level of temporal and techno-economic operational detail are quantified for a varying penetration of intermittent renewable energy sources (IRES). For a high penetration of IRES, the gains obtained by improving the temporal representation are shown to outweigh the gains obtained by incorporating detailed techno-economic operational constraints. Therefore, improving the temporal representation is suggested to be prioritized. The second goal of this paper is to identify opportunities for model improvements. Different approaches to improve the temporal representation are proposed. While the focus in the literature lies primarily on the impact of the temporal resolution, this work more fundamentally considers and assesses different approaches of dealing with the temporal dimension. Using a different approach of defining the time slices to explicitly account for IRES variability is found to lead to a higher accuracy than can be obtained by simply increasing the temporal resolution, while requiring a lower number of time slices. Moreover, a temporal representation based on selecting a set of representative days can achieve an even higher accuracy, albeit requiring a higher number of time slices. An additional advantage of using representative days is that chronology is retained such that the impact of short-term dynamic fluctuations of IRES can be accounted for.

Subfields: Electrical and Electronic Engineering, Global and Planetary Change, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/cee31c749658850b7d4d53ed12c7aab07d2c2687

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In Electrical and Electronic Engineering

Citations in the corpus

Feasible path toward 40–100% renewable energy shares for power supply in France by 2050: A prospective analysis (2016, background): “For this purpose, we us a bottom-up, long-term investment planning model from the MARKAL-TIMES family [35], w ell suited for the dynamic evolution assessment on a long period of several de cades, that we have improved with: • TS resolution enabling us to capture, at least part ly, demand as well as ”
Classification and challenges of bottom-up energy system models - A review (2020, background): “[60], presents a large generation mix error compared to the hourly time resolution approach especially when facing high penetration of renewables.”
Carbon‐Neutral Pathways for the United States (2021, background): “A key concern is the temporal representation of electricity operations, which requires much greater fidelity when variable renewable generation is involved (Poncelet et al., 2016).”
The Pareto-optimal temporal aggregation of energy system models (2021, neutral): “…[67, 68] 2013/16  Simões et al. [69] 2013  Voll et al. [70] 2013  Fazlollahi et al. [9, 71] 2014  Green et al. [17] 2014  Poncelet et al. [72, 73] 2014/16  Stadler et al. [74] 2014  Wakui et al. [75-77] 2014/16  Agapoff et al. [20] 2015  Marquant et al. [25, 26] 2015  Munoz et al. [27]…”