The purpose of this article is twofold. First, we review model-based analyses that explore the role of power storage in energy systems with high shares of variable renewables. Second, we introduce a new model that is specifically designed for exploring long-term storage requirements. The literature survey focuses on recent contributions in the peer-reviewed energy economics and engineering literature. We compare key characteristics of the different models, provide an overview of model applications, and summarize key findings on power storage requirements. We also evaluate which system values of storage are covered by respective model analyses. Based on the literature survey, we identify common findings and key model features required for a sound assessment of future storage requirements. In order to raise complementary insights, we introduce DIETER, a new dispatch and investment model. The model contributes to the literature by capturing multiple system values of power storage related to arbitrage, capacity, and reserve provision. Further, the model is designed as an open-source tool that can be freely used and modified. Results of a first application of the new model are presented in a companion paper.

Long-run power storage requirements for high shares of renewables: review and a new model

Comparison of spatially and temporally resolved energy system models with a focus on Germany's future power supply

Germany has an ambitious climate target for 2030 that cannot be achieved without reducing the high share of coal in power generation. In the face of this, the country has set up a commission to phase out coal. A UK-style carbon price floor is one of the options being considered. Yet implementing such a policy comes with important risks related to the following two aspects: (1) the price level necessary to reduce emissions to reach the 2030 climate target; and (2) the waterbed effect that arises from such a policy under the EU Emissions Trading Scheme (ETS) cap. In this paper, we quantify these risks using the numerical electricity market model LIMES-EU, and consider their implications as well as different options for dealing with them. Our results show that under baseline assumptions a carbon price floor of around 33 €/tCO2 would be sufficient to reach the 2030 target. Under unfavourable conditions, an appropriate price floor may be nearly twice as high (57 €/tCO2). The waterbed effect and related risks for the EU ETS could be reduced substantially in the mid-term (2030) through the recently introduced cancellation of allowances through the Market Stability Reserve (MSR), or through a larger coalition of countries. Germany could even fully alleviate the waterbed effect by cancelling 1.1 GtCO2 of certificates. In the long-term (until 2050), emission reductions leading up to 2030 would be almost completely (91%) offset at the EU level. Accordingly, it is essential that the national price initiates a policy sequence that leads to the EU level.

How to deal with the risks of phasing out coal in Germany through national carbon pricing

This paper presents the results of a multi-model comparison to determine outcome deviations resulting from differences in power system models. We apply eight temporally and spatially resolved models to 16 stylized test cases. These test cases differ in their renewable energy supply share, technology scope, and optimization scope. We focus on technologies for balancing the variability of power generation, such as controllable power plants, energy storage, power transmission, and flexibility related to sector coupling. We use harmonized input data in all models to separate model-related from data-related outcome deviations. We find that our approach allows for isolating and quantifying model-related outcome deviations and robust effects concerning system operation and investment decisions. Furthermore, we can attribute these deviations to the identified model differences. Our results show that trends in the use of individual flexibility options are robust across most models. Moreover, our analysis reveals that differences in the general modeling approach and the modeling of specific technologies lead to comparatively small deviations. In contrast, a heterogeneous model scope can cause substantially larger deviations. Due to a large number of models and scenarios, our analysis can provide important information on which investment and operation decisions are robust to the model choice, and which modeling approaches have an exceptionally high impact on results. Our findings may guide both modelers and decision-makers in properly evaluating the results of similarly designed power system models. 

Model-related outcome differences in power system models with sector coupling—Quantification and drivers

The European electricity industry, the dominant sector of the world's largest cap-and-trade scheme, is one of the most-studied examples of carbon pricing. In particular, numerical models are often used to study the uncertain future development of carbon prices and emissions. While parameter uncertainty is often addressed through sensitivity analyses, the potential uncertainty of the models themselves remains unclear from existing single-model studies. This study investigates such model-related uncertainty by running a structured model comparison experiment, which exposes five numerical power sector models to aligned input parameters—finding stark model differences. At a carbon price of 27 EUR/t in 2030, the models estimate that European power sector emissions will decrease by 36–57% when compared to 2016. Most of this variation can be explained by the extent to which models consider the market-driven decommissioning of coal- and lignite-fired power plants. Higher carbon prices of 57 and 87 EUR/t yield a stronger decrease in carbon emissions, by 45–75% and 52–80%, respectively. The lower end of these ranges can be attributed to the short-term fuel switch captured by dispatch-only models. The higher reductions correspond to models that additionally consider market-based investment in renewables. By further studying cross-model variation in the remaining emissions at high carbon prices, the representation of combined heat and power is identified as another crucial driver of differences across model results.

https://www.econstor.eu/bitstream/10419/234468/1/Ruhnau-et-al-2021-Why-electricity-market-models-EconStor.pdf

Why electricity market models yield different results: Carbon pricing in a model-comparison experiment

In diesem Beitrag werden die Rolle des europaischen Netzverbundes und der Beitrag von nicht-netzseitigen Flexibilitatsoptionen fur die Systemintegration erneuerbarer Energien (EE) im deutschen Stromsystem im Rahmen einer Szenarienanalyse fur den Zeitraum 2020 bis 2050 modellgestutzt analysiert. Der Bedarf an Flexibilitat steigt dabei mit zunehmendem Anteil erneuerbarer Energien an. Dem europaischen Netzverbund kommt in allen Phasen der Systemtransformation eine entscheidende Rolle als Flexibilitatsoption beim Ausgleich von Erzeugung und Verbrauch zu. Wahrend in der Ubergangsphase die Nutzung von innerdeutschen EE-Uberschussen im Ausland im Vordergrund steht, profitiert Deutschland vor allem bei einem EE-Anteil groser 60 % sowohl von auslandischen konventionellen Kraftwerken als auch von dem Import von EE-Strom. Wichtig sind dafur eine bessere Nutzung der heute schon bestehenden Netzkapazitaten (z. B. mittels lastflussbasierter Marktkopplung), der Ausbau der Kuppelleitungen sowie die Starkung des europaischen Binnenmarktes. Daruber hinaus konnen Lastmanagement und Speicher als nicht-netzseitige Flexibilitatsoptionen einen relevanten Beitrag zur Bereitstellung von Erzeugungskapazitat leisten. Die Flexibilisierung von Kraftwerken mit Kraft-Warme-Kopplung (KWK) bzw. von Biogas-Blockheizkraftwerken (BHKW) fuhrt zudem zu einer verbesserten Nutzung von EE-Uberschussen in Deutschland. Ab dem Szenario-Jahr 2030 treten relevante EE-Uberschusse auf, die grostenteils von Power-to-Heat und Power-to-Gas in Warme oder Wasserstoff bzw. synthetisches Methan umgewandelt werden und somit fossile Brennstoffe im Warme- oder Gassektor ersetzen.

Modellgestützte Bewertung von Netzausbau im europäischen Netzverbund und Flexibilitätsoptionen im deutschen Stromsystem im Zeitraum 2020–2050

We present results of two model based scenario analysis focussing on the future German power sector which is characterized by a rising share of renewable energies and an associated higher demand for flexibility. Case study 1 is based on a general comparison between a decentrally and a centrally orientated electricity system. The research question of case study 2 is whether flexibility should be centrally balanced by a national market-based dispatch or dispatched in a decentralized manner within regional balancing areas. The combined results of these two case studies offer the possibility to show the differences between a decentralized and a centralized electricity system regarding the dispatch of generation, storage and flexibility options as well as resulting effects on variable costs, CO2 emissions, grid usage and RE integration. Decentralization as control strategy leads to higher variable generation costs due to more expensive generation and less efficient flexibility options that come into the market, while the majority of demand and supply still needs a transmission grid for balancing.

Dispatch of Flexibility Options, Grid Infrastructure and Integration of Renewable Energies Within a Decentralized Electricity System

Entwicklungspfade aus dem ENSURE-Projekt - Transformation des Energiesystems bis zum Jahr 2030

The European electricity industry, the dominant sector of the world’s largest cap-and-trade scheme, is one of the most-studied examples of carbon pricing. In particular, numerical models are often used to study the uncertain future development of carbon prices and emissions. While parameter uncertainty is often addressed through sensitivity analyses, the potential uncertainty of the models themselves remains unclear from existing single-model studies. Here, we investigate such model-related uncertainty by running a structured model comparison experiment, in which we exposed five numerical power sector models to aligned input parameters—finding stark model differences. At a carbon price of 27 EUR/t in 2030, the models estimate that European power sector emissions will decrease by 36–57% when compared to 2016. Most of this variation can be explained by the extent to which models consider the market-driven decommissioning of coal- and lignite-fired power plants. Higher carbon prices of 57 and 87 EUR/t yield a stronger decrease in carbon emissions, by 45–75% and 52–80%, respectively. The lower end of these ranges can be attributed to the short-term fuel switch captured by dispatch-only models. The higher reductions correspond to models that additionally consider market-based investment in renewables. By further studying cross-model variation in the remaining emissions at high carbon prices, we identify the representation of combined heat and power as another crucial driver of differences across model results.

Matthias Koch

Papers

Why electricity market models yield different results: Carbon pricing in a model-comparison experiment

Modellgestützte Bewertung von Netzausbau im europäischen Netzverbund und Flexibilitätsoptionen im deutschen Stromsystem im Zeitraum 2020–2050

Dispatch of Flexibility Options, Grid Infrastructure and Integration of Renewable Energies Within a Decentralized Electricity System

Entwicklungspfade aus dem ENSURE-Projekt - Transformation des Energiesystems bis zum Jahr 2030

Why electricity market models yield different results: Carbon pricing in a model-comparison experiment