GenCo's optimal power portfolio selection under emission price risk


Mathuria, P., Bhakar, R. and Li, F., 2015. GenCo's optimal power portfolio selection under emission price risk. Electric Power Systems Research, 121, pp. 279-286.

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    Carbon markets are a world-wide accepted market mechanism to promote emission reduction. Increasing stress on emission reduction from the power industry has led to a shift in the market mechanism, from free allocation to full auction. Consequent increase in volatility of emission market and its interdependency with electricity market is predominantly affecting the fossil-fuel generation companies (GenCos). For accurate realization of their optimal electricity trading portfolio selection, GenCos need to incorporate cost side uncertainties arising from fuel and emission market volatilities. This paper proposes a novel framework for electricity trading portfolio optimization of a GenCo, considering uncertainties of electricity, fuel and emission markets, to secure its future trading position. This optimization problem is modeled using mean variance portfolio theory, considering spot market, bilateral contracts as electricity trading options. Results show that considering correlation effects of electricity market with emission markets, the proposed framework is capable of improving profit risk trade-off for the portfolio. Positively correlated electricity, emission market prices lead to an increased trading in spot market. In such a situation, the model reflects that spot selling could offer higher risk protection vis-à-vis bilateral contracts, and can prominently help high emission GenCos to minimize their market risks.


    Item Type Articles
    CreatorsMathuria, P., Bhakar, R. and Li, F.
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    Uncontrolled Keywordselectricity price uncertainty,emission price uncertainty,fossil fuel gencos,fuel price uncertainty,mean variance portfolio theory,risk management
    DepartmentsFaculty of Engineering & Design > Electronic & Electrical Engineering
    Research CentresCentre for Sustainable Power Distribution
    EPSRC Centre for Doctoral Training in Statistical Mathematics (SAMBa)
    Publisher StatementAccepted_Version.pdf: The Published version is available via:
    ID Code44187


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