TY - THES A1 - Hirth, Lion T1 - The Economics of Wind and Solar Variability – How the Variability of Wind and Solar Power affects their Marginal Value, Optimal Deployment, and Integration Costs T2 - Die Ökonomik von variabler Wind- und Solarenergie: ökonomischer Wert, optimaler Ausbau und Integrationskosten von Wind- und Solarstrom KW - Wind power KW - Solar power KW - Power system economics KW - Integration costs KW - Intermittency Y1 - 2014 U6 - https://doi.org/10.14279/depositonce-4291 PB - Technical University of Berlin CY - Berlin ER - TY - JOUR A1 - Hirth, Lion T1 - The Optimal Share of Variable Renewables: How the Variability of Wind and Solar Power affects their Welfare-optimal Deployment JF - The Energy Journal N2 - This paper estimates the welfare-optimal market share of wind and solar power, explicitly taking into account their output variability. We present a theoretical valuation framework that consistently accounts for the impact of fluctuations over time, forecast errors, and the location of generators in the power grid on the marginal value of electricity from renewables. Then the optimal share of wind and solar power in Northwestern Europe's generation mix is estimated from a calibrated numerical model. We find the optimal long-term wind share to be 20%, three times more than today; however, we also find significant parameter uncertainty. Variability significantly impacts results: if winds were constant, the optimal share would be 60%. In addition, the effect of technological change, price shocks, and policies on the optimal share is assessed. We present and explain several surprising findings, including a negative impact of CO2 prices on optimal wind deployment. KW - Wind power KW - Solar power KW - Variable renewables KW - Cost-benefit analysis KW - Numerical optimization KW - Competitiveness Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b1570-opus4-22832 SN - 1944-9089 VL - 36 IS - 1 SP - 127 EP - 162 ER - TY - JOUR A1 - Hirth, Lion A1 - Ziegenhagen, Inka T1 - Balancing power and variable renewables: Three links JF - Renewable and Sustainable Energy Reviews N2 - Balancing power is used to quickly restore the supply-demand balance in power systems. The need for this tends to be increased by the use of variable renewable energy sources (VRE) such as wind and solar power. This paper reviews three channels through which VRE and balancing systems interact: the impact of VRE forecast errors on balancing reserve requirements; the supply of balancing services by VRE generators; and the incentives to improve forecasting provided by imbalance charges. The paper reviews the literature, provides stylized facts from German market data, and suggests policy options. Surprisingly, while German wind and solar capacity has tripled since 2008, balancing reserves have been reduced by 15%, and costs by 50%. KW - Balancing power KW - Control power KW - Regulating power KW - Variable renewables KW - Wind power KW - Solar power KW - Market design Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b1570-opus4-22856 SN - 1364-0321 N1 - This is a post-peer-review, pre-copyedit version of an article published in Renewable and Sustainable Energy Reviews. The final authenticated version is available online at: DOI 10.1016/j.rser.2015.04.180 VL - 50 SP - 1035 EP - 1051 PB - Elsevier Ltd ER - TY - JOUR A1 - Hirth, Lion A1 - Ueckerdt, Falko A1 - Edenhofer, Ottmar T1 - Integration Costs Revisited – An economic framework for wind and solar variability JF - Renewable Energy N2 - The integration of wind and solar generators into power systems causes “integration costs” – for grids, balancing services, more flexible operation of thermal plants, and reduced utilization of the capital stock embodied in infrastructure, among other things. This paper proposes a framework to analyze and quantify these costs. We propose a definition of integration costs based on the marginal economic value of electricity, or market value – as such a definition can be more easily used in economic cost-benefit assessment than previous approaches. We suggest decomposing integration costs intro three components, according to the principal characteristics of wind and solar power: temporal variability, uncertainty, and location-constraints. Quantitative estimates of these components are extracted from a review of 100 + published studies. At high penetration rates, say a wind market share of 30–40%, integration costs are found to be 25–35 €/MWh, i.e. up to 50% of generation costs. While these estimates are system-specific and subject to significant uncertainty, integration costs are certainly too large to be ignored in high-penetration assessments (but might be ignored at low penetration). The largest single factor is reduced utilization of capital embodied in thermal plants, a cost component that has not been accounted for in most previous integration studies. KW - Wind power KW - Solar power KW - Integration cost KW - Variable renewables Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b1570-opus4-22878 SN - 0960-1481 VL - 74 SP - 925 EP - 939 PB - Elsevier Ltd ER - TY - JOUR A1 - Hirth, Lion A1 - Ueckerdt, Falko A1 - Edenhofer, Ottmar T1 - Why Wind is not Coal: On the Economics of Electricity Generation JF - The Energy Journal N2 - Electricity is a paradoxical economic good: it is highly homogeneous and heterogeneous at the same time. Electricity prices vary dramatically between moments in time, between location, and according to lead-time between contract and delivery. This three-dimensional heterogeneity has implication for the economic assessment of power generation technologies: different technologies, such as coal-fired plants and wind turbines, produce electricity that has, on average, a different economic value. Several tools that are used to evaluate generators in practice ignore these value differences, including "levelized electricity costs", "grid parity", and simple macroeconomic models. This paper provides a rigorous and general discussion of heterogeneity and its implications for the economic assessment of electricity generating technologies. It shows that these tools are biased, specifically, they tend to favor wind and solar power over dispatchable generators where these renewable generators have a high market share. A literature review shows that, at a wind market share of 30-40%, the value of a megawatt-hour of electricity from a wind turbine can be 20-50% lower than the value of one megawatt-hour as demanded by consumers. We introduce "System LCOE" as one way of comparing generation technologies economically. KW - Power generation KW - Electricity sector KW - Integrated assessment modeling KW - Wind power KW - Solar power KW - Variable renewables KW - Integration costs KW - Welfare economics KW - Power economics KW - Levelized electricity cost KW - LCOE KW - Grid parity Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b1570-opus4-22828 SN - 1944-9089 VL - 37 IS - 3 SP - 1 EP - 27 ER -