Risk Hedging Strategies Under Energy System and Climate Policy Uncertainties
Volker Krey () and
Keywan Riahi ()
Additional contact information
Volker Krey: IIASA
Keywan Riahi: IIASA
Chapter Chapter 17 in Handbook of Risk Management in Energy Production and Trading, 2013, pp 435-474 from Springer
Abstract:
Abstract The future development of the energy sector is rife with uncertainties. They concern virtually the entire energy chain, from resource extraction to conversion technologies, energy demand, and the stringency of future environmental policies. Investment decisions today need thus not only to be cost-effective from the present perspective, but have to take into account also the imputed future risks of above uncertainties. This chapter introduces a newly developed modeling decision framework with endogenous representation of above uncertainties. We employ modeling techniques from finance and in particular modern portfolio theory to a systems engineering model of the global energy system and implement several alternative representations of risk. We aim to identify salient characteristics of least-cost risk hedging strategies that are adapted to considerably reduce future risks and are hence robust against a wide range of future uncertainties. These lead to significant changes in response to energy system and carbon price uncertainties, in particular (i) higher short- to medium-term investments into advanced technologies, (ii) pronounced emissions reductions, and (iii) diversification of the technology portfolio. From a methodological perspective, we find that there are strong interactions and synergies between different types of uncertainties. Cost-effective risk hedging strategies thus need to take a holistic view and comprehensively account for all uncertainties jointly. With respect to costs, relatively modest risk premiums (or hedging investments) can significantly reduce the vulnerability of the energy system against the associated uncertainties. The extent of early investments, diversification, and emissions reductions, however, depends on the risk premium that decision makers are willing to pay to respond to prevailing uncertainties and remains thus one of the key policy variables.
Keywords: Risk Measure; Risk Premium; Carbon Price; Latin Hypercube Sampling; Total System Cost (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations: View citations in EconPapers (9)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-1-4614-9035-7_17
Ordering information: This item can be ordered from
http://www.springer.com/9781461490357
DOI: 10.1007/978-1-4614-9035-7_17
Access Statistics for this chapter
More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().