Long-run power storage requirements for high shares of renewables: review and a new model
Introduction
An increasing use of renewable energy sources (RES) is foreseen in many countries around the world. This development is driven, among other factors, by tighter carbon constraints and growing concerns about security of supply. The power sector is often perceived as a particularly promising area for achieving high shares of renewables as compared to the heat and transportation sectors. Moreover, many other greenhouse gas mitigation options appear to be comparatively expensive. In countries where hydro, biomass or geothermal resources are limited, achieving high shares of RES in the electricity sector requires a massive deployment of variable wind and solar power generators. A cost-efficient power system that is largely based on such variable renewable energy sources not only requires an appropriate mix of different generation technologies, but also the utilization of dedicated flexibility options such as power storage or demand-side management (DSM).
In this paper, we first provide a comprehensive review of the academic literature analyzing the role of power storage and other flexibility measures to accommodate electricity generation from variable renewables deployed on large scale. For different types of models, we compare specific features, application details and central findings, and identify relevant aspects for comprehensively modeling the interplay between variable renewable energy sources and power storage. Based on this, we introduce a new open-source model, the Dispatch and Investment Evaluation Tool with Endogenous Renewables (DIETER).1 The model is designed to determine cost-minimizing combinations of generation, DSM, and power storage capacities as well as their optimal dispatch. In a companion paper [1], the model is applied to analyze the role of different power storage technologies in a long-term greenfield system with high shares of renewables between 60% and 100%.
We aim to contribute to the literature in several respects. First, we systematically review and compare relevant recent contributions from peer-reviewed energy economics and engineering journals that specifically deal with power storage in the context of variable renewable energy sources, such as wind and solar power. In doing so, we compare key characteristics of different models, provide an overview on the scope of respective applications, and summarize key findings on power storage requirements. We also evaluate which system values of storage are covered by respective model analyses. We discuss common findings and relevant modeling features concerning the role of storage. Based on the review, we propose a new model dedicated to exploring long-term storage requirements. This model not only focuses on the wholesale market, but also considers balancing reserves, the requirements of which are endogenously determined, depending on the deployment of variable renewables. We further include a novel representation of demand-side management, which may be considered one of the main competitors of power storage with respect to the provision of short-term flexibility. To do so, we build on a DSM model formulation recently introduced in the literature [2], which is applied in a large-scale model for the first time. Aside from DSM and different power storage technologies, which can be freely optimized with respect to their energy to power (E/P) ratio,2 the model comprises further flexibility options such as flexible thermal plants, dispatchable biomass generators, and oversizing as well as curtailment of variable renewables. Importantly, the model is able to reflect three distinctive system values of storage and other flexibility options: an arbitrage value, a balancing value, and a capacity value. At the same time, the model is set up as parsimonious as possible in order to remain traceable and to allow for extensive sensitivity analysis.
The remainder is structured as follows. We first review, compare, and discuss the relevant literature in Section 2. Subsequently, Section 3 introduces the analytical formulation of the new model. We briefly discuss the model's contribution and its limitations in Section 4. The final Section 5 concludes.
Section snippets
Literature review
The analysis of electricity or, more generally, energy systems with high shares of variable renewables spawned a broad literature featuring a variety of modeling approaches. Power storage and other flexibility options are important aspects of such exercises. Between the ends of traceability and the degree of technical, economic or spatial detail, there is always a trade-off depending on which features a particular focus is laid on—power system models are generally suited to their application.
A new model
We introduce a new open-source model, the Dispatch and Investment Evaluation Tool with Endogenous Renewables (DIETER), which addresses the domains distilled from the literature review: an hourly resolution for a full year, and the incorporation of balancing energy and demand-side management while being traceable to perform multiple sensitivity analyses on various parameters.
DIETER minimizes total system costs over 8760 h of a full year. System costs comprise annualized investment costs and fixed
Discussion of limitations
In the following, we briefly discuss important limitations of our model approach.
In its current setup, the model does not allow for investigating a transition from an existing power plant portfolio to a renewable-dominated one, but always assumes optimal long-run equilibria. This restricts the potential to draw policy conclusions on transformation processes. Still, the model can be used to provide, on the one hand, long-run benchmarks for the role of power storage in optimized future power
Conclusions
We carry out a detailed review of model-based analyses on the role of power storage in electricity systems dominated by variable renewable energy sources. These analyses and their underlying models can be differentiated with respect to a range of specific features, such as the coverage of balancing reserves and demand-side management, and with respect to the potential system values of storage covered by the analysis. This includes system values related to arbitrage, capacity, and reserves, as
Acknowledgments
The authors thank two anonymous reviewers for valuable comments. We also thank Jochen Diekmann, Clemens Gerbaulet, Friedrich Kunz, Moritz Niemeyer, Jan Stede, and Christian von Hirschhausen for their support and valuable comments on earlier drafts. We also thank the participants of session 30 at the 14th IAEE European Conference 2014 in Rome, the final StoRES workshop at DIW Berlin in December 2014, the DIW Berlin Sustainability Cluster Seminar, the 9th International Renewable Energy Storage
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