Energy and climate policies to 2020: the impacts of the European “20/20/20” approach

Stankeviciute, Loreta; Criqui, Patrick

doi:10.1108/17506220810883243

Cited by 26 publications

(12 citation statements)

References 16 publications

(24 reference statements)

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“…A prominent illustration of some of the problems of policy interactions and risk is provided by the EU (European Commission, 2008) which includes provisions for strengthening the EU emissions trading scheme (EU-ETS), an ambitious target of 20% of final energy consumption to come from renewable sources by 2020, targets for improved energy efficiency, as well as a support package for carbon capture and storage. Because they all tackle emissions from the same key sources, there is significant scope for these wide-ranging and potentially transformative policies to interact in a way which reduces their individual efficacy (Stankeviciute and Criqui, 2008). The direction and magnitude of these interactions is taken into account for example in the EU's energy modelling exercises (EU Commission, 2008a), which shows a relatively modest depression in the carbon price resulting from the introduction of the 20% renewable energy target.…”

Section: Article In Pressmentioning

confidence: 99%

Policy interactions, risk and price formation in carbon markets

et al. 2009

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a b s t r a c tCarbon pricing is an important mechanism for providing companies with incentives to invest in carbon abatement. Price formation in carbon markets involves a complex interplay between policy targets, dynamic technology costs, and market rules. Carbon pricing may under-deliver investment due to R&D externalities, requiring additional policies which themselves affect market prices. Also, abatement costs depend on the extent of technology deployment due to learning-by-doing. This paper introduces an analytical framework based on marginal abatement cost (MAC) curves with the aim of providing an intuitive understanding of the key dynamics and risk factors in carbon markets. The framework extends the usual static MAC representation of the market to incorporate policy interactions and some technology cost dynamics. The analysis indicates that supporting large-scale deployment of mature abatement technologies suppresses the marginal cost of abatement, sometimes to zero, whilst increasing total abatement costs. However, support for early stage R&D may reduce both total abatement cost and carbon price risk. An important aspect of the analysis is in elevating risk management considerations into energy policy formation, as the results of the stochastic modelling indicate wide distributions for the emergence of carbon prices and public costs around the policy expectations.

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Section: Article In Pressmentioning

confidence: 99%

Policy interactions, risk and price formation in carbon markets

et al. 2009

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“…A similar conclusion is drawn by Klepper and Peterson (2006) in their global CGE analysis of the EU Emissions Trading Scheme and the use of flexible mechanisms. Stankeviciute and Criqui (2008) emphasize the role of additional policies in the area of energy savings and renewable energies. They show in a partial equilibrium framework for a scenario named "ETS only," which is based on the current ETS system and no additional policies in the areas of energy savings and renewable energies, that merely with the carbon price signal Europe would move away from the European Council objectives for 2020 and would increase the compliance costs for ETS participants.…”

Section: Results For Greenhouse Gas Emissionsmentioning

confidence: 99%

Economic comparison of greenhouse gas mitigation options in Germany

Sands

Schumacher

2008

Energy Efficiency

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Our objective is to provide a balanced analysis of greenhouse gas mitigation options, across a variety of climate policy scenarios, for Germany. At least four classes of greenhouse gas mitigation options are available: energy efficiency, fuel switching, CO 2 capture and storage (CCS), and reductions in emissions of non-CO 2 greenhouse gases. These options vary by cost, timing, and our ability to represent them in an economic analysis. We use the Second Generation Model, an economy-wide computable general equilibrium (CGE) model that embodies greenhouse gas mitigation possibilities from the energy system and CCS. Policy scenarios are represented as a response to varying levels of a price for greenhouse gas emissions, either applied economy-wide or targeted at energy-intensive sectors of the economy according to the EU emissions trading scheme. Energy efficiency options are represented in the standard CGE format where non-energy inputs substitute for energy inputs within economic production functions, or system of consumer demand equations, as the price of energy increases relative to other goods. The electric power sector provides substantial opportunities for fuel switching and the deployment of advanced electricity-generating technologies, with and without CO 2 capture and storage. Our methodology relies on engineering descriptions of electricity-generating technologies and how their competitive positions vary with a CO 2 price or change in fuel price. Further, we allow for reduction of emissions of non-CO 2 gases, which adds a set of mitigation opportunities not usually included in energy-economic modeling efforts. A formal decomposition methodology is used to isolate the contribution of each greenhouse gas mitigation option.

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“…index for the rival investor units running 1 to K i index for the existing generation units running 1…”

Section: Indices Imentioning

confidence: 99%

Bi‐level model for generation expansion planning with contract pricing of renewable energy in the presence of energy storage

Rafiei

Mohammadi‐Ivatloo

Asadi

et al. 2019

IET Renewable Power Generation

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This study presents a bi-level model for expansion planning of generation systems. The proposed model endogenously determines the incentive to invest (guaranteed purchase contract) for wind and storage units. In the upper level of the proposed model, wind turbines and compressed air storage systems focus on maximising their profits by presenting a strategic offering, while at the lower level, there is an independent system operator with the purpose of increasing social welfare run the market clearing equations. In solving the bi-level model, the Karush-Kuhn-Tucker conditions are used to develop the mathematical program with equilibrium constraints. The problem was first linearised and then solved by GAMS software. The outputs of this problem are the installation time and capacity of the wind and storage units and the price of the purchase contract. The obtained results were compared with other existing studies for verification purposes.

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Energy and climate policies to 2020: the impacts of the European “20/20/20” approach

Cited by 26 publications

References 16 publications

Policy interactions, risk and price formation in carbon markets

Policy interactions, risk and price formation in carbon markets

Economic comparison of greenhouse gas mitigation options in Germany

Bi‐level model for generation expansion planning with contract pricing of renewable energy in the presence of energy storage

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