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    <link>http://hdl.handle.net/1880/47843</link>
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    <pubDate>Thu, 23 May 2013 09:54:13 GMT</pubDate>
    <dc:date>2013-05-23T09:54:13Z</dc:date>
    <item>
      <title>Optimization of Electricity Retailer’s Contract Portfolio Subject to Risk Preferences</title>
      <link>http://hdl.handle.net/1880/47850</link>
      <description>Title: Optimization of Electricity Retailer’s Contract Portfolio Subject to Risk Preferences
Authors: Kettunen, Janne; Salo, Ahti; Bunn, Derek  W
Abstract: When an electricity retailer faces volume risk in&#xD;
meeting load and spot price risk in purchasing from the wholesale&#xD;
market, conventional risk management optimization methods can&#xD;
be quite inefficient. For the management of an electricity contract&#xD;
portfolio in this context, we develop a multistage stochastic optimization&#xD;
approach which accounts for the uncertainties of both&#xD;
electricity prices and loads, and which permits the specification of&#xD;
conditional-value-at-risk requirements to optimize hedging across&#xD;
intermediate stages in the planning horizons. Our experimental&#xD;
results, based on real data from Nordpool, suggest that the modeling&#xD;
of price and load correlations is particularly important. The&#xD;
sensitivity analysis is extended to characterize the behavior of&#xD;
retailers with different risk attitudes. Thus, we observe that a risk&#xD;
neutral retailer is more susceptible to price-related than load-related&#xD;
uncertainties in terms of the expected cost of satisfying the&#xD;
load, and that a risk averse retailer is especially sensitive to the&#xD;
drivers of the forward risk premium.
Description: "(c) 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works."</description>
      <pubDate>Fri, 01 Jan 2010 00:00:00 GMT</pubDate>
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      <dc:date>2010-01-01T00:00:00Z</dc:date>
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      <title>Policy interactions, risk and price formation in carbon markets</title>
      <link>http://hdl.handle.net/1880/47845</link>
      <description>Title: Policy interactions, risk and price formation in carbon markets
Authors: Kettunen, Janne; Blyth, William; Bunn, Derek; Wilson, Tom
Abstract: Carbon pricing is an important mechanism for signalling to individuals and companies societal&#xD;
concerns about climate change, and for providing an incentive to invest in carbon abatement. Price&#xD;
formation in carbon markets involves a complex interplay between policy targets, dynamic&#xD;
technology costs, and market rules. Carbon pricing may under-deliver investment due to R&amp;D&#xD;
externalities and so additional policies may be needed which themselves affect carbon price&#xD;
formation. Also, future abatement costs depend on the extent of technology deployment due to&#xD;
learning-by-doing, leading to some circularity in the analysis of investment, learning, costs and&#xD;
prices. This paper introduces an analytical framework based on marginal abatement cost (MAC)&#xD;
curves with the aim of providing an intuitive (rather than complete) understanding of the key&#xD;
dynamics and risk factors in carbon markets. The framework extends the usual static MAC&#xD;
representation of the market to incorporate policy interactions and some technology cost dynamics.&#xD;
The analysis indicates that supporting large-scale deployment of mature abatement technologies&#xD;
suppresses the marginal cost of abatement, sometimes to zero, whilst increasing total abatement&#xD;
costs. However, support for early stage R&amp;D may reduce both total abatement cost and carbon&#xD;
price risk. It is anticipated that the intuitive framework introduced here may help in policy design&#xD;
issues around cost containment measures and other market design options such as banking and&#xD;
borrowing (factors that are not currently incorporated into the model).</description>
      <pubDate>Thu, 01 Jan 2009 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/1880/47845</guid>
      <dc:date>2009-01-01T00:00:00Z</dc:date>
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