Suchergebnisse

This open access book analyzes and seeks to consolidate the use of robust quantitative tools and qualitative methods for the design and assessment of energy and climate policies. In particular, it examines energy and climate policy performance and associated risks, as well as public acceptance and portfolio analysis in climate policy, and presents methods for evaluating the costs and benefits of flexible policy implementation as well as new framings for business and market actors. In turn, it discusses the development of alternative policy pathways and the identification of optimal switching points, drawing on concrete examples to do so. Lastly, it discusses climate change mitigation policies' implications for the agricultural, food, building, transportation, service and manufacturing sectors. ; Open Access Presents a comprehensive tool set of methods for devising energy and climate policies Focuses on methods that are robust and adaptive enough to mitigate risks Investigates implications of climate change mitigation policies to various sectors

Given the international efforts in tackling climate change as well as the potential dependence on conventional energy imports and the adverse economic environment, countries in the European Union face significant challenges in the critical task of enhancing energy efficiency. Approaches exclusively oriented on detailed quantitative modelling tools like energy system and climate-economy models, however, tend to exclude certain policy instruments and risks, and be too formalised or complex for policymakers to participate, understand and trust. Several decision support frameworks have been proposed for bridging the policy-model gap and helping policymakers confidently select among a number of alternative strategies. This paper employs the expert-driven method of fuzzy cognitive mapping, a semi-quantitative modelling technique in which system dynamics are captured and simulated against different scenarios. To this end, an innovative decision support tool for building and simulating complex fuzzy cognitive maps for assessing policy strategies with the help of experts, ESQAPE, is introduced and presented. An application in Greece shows that long-term energy efficiency measures focusing mainly on behavioural change in the residential sector – as opposed to services in the private and public sectors – are perceived to be more sustainable in a socio-economically optimistic future; this is not the case when challenges across the mitigation and adaptation axes are expected to be higher.

Ambitious emission reduction targets are challenging the status quo on designing effective strategies for electricity generation portfolios. In this chapter, we consider the role of low-carbon technologies and determine the cost-benefits of policy strategies to mitigate greenhouse gas emissions in the EU. In particular, we look into how long-term scenarios for transmission expansion and decarbonisation policies influence the evolution of the EU power system infrastructure. We use an EU electricity investment model to determine the optimal portfolio of electricity generation technologies and compute their respective costs and emissions achieved towards 2050. Based on the investment model's results (strategies and suggested portfolios), we investigate how these portfolios perform under divergent policy or geopolitical developments. For this purpose, we apply a robust optimisation tool based on the min-max and the min-max regret criteria, which selects ideal portfolios by stress testing a particular scenario or policy choice under uncertainty of input parameters. Results show that pursuing a strong transmission expansion strategy under the EU PRIMES reference case leads to the maximum regret, while relying on EU scenarios with strong prospects for decarbonisation, either with possibilities or with limitation on transmission expansion, leads to portfolios that exhibit the least variance. However, applying regret analysis on investment costs and total emissions indicates a limited transmission investment case as the more robust one, also noting that a high carbon price will accelerate the energy transition. ; publishedVersion ; © The Author(s) 2019 Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

The European Union has set specific targets for reducing energy consumption, shifting the main focus of European energy policytowards a firm commitment to enhancing energy efficiency. In light of the limited progress reported in Greece's energy efficiency action plan, the objective of this paper is to help redesign the near-term national policy framework. In this respect, a risk-oriented optimisation model is developed to support the optimal budget allocation to energy efficiency measures, with a view to achieving the 2020 national targets. The transdisciplinary methodological framework initially builds on the Energy Efficiency Action Plans for Greece and involves stakeholder engagement, multiple-criteria decision making and portfolio analysis. The evaluation of the policy instruments is based on two criteria, namely energy savings and implementation risk, under a set of technical and financial constraints. Finally, the robustness of both the optimal policy portfolios and the individual policies composing these portfolios is assessed. The results indicate that, given the financial and technical constraints, the 2020 target cannot be achieved. By stochastically analysing the impact of external uncertainty, three policies emerge as the most robust, while portfolios achieving savings of more than 1000 kTOE until 2020 are found highly vulnerable to underlying uncertainties.