GenCo's optimal power portfolio selection under emission price risk

Mathuria, Parul; Bhakar, Rohit; Li, Furong

doi:10.1016/j.epsr.2014.11.006

Cited by 19 publications

(6 citation statements)

References 26 publications

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“…A first-order secondmoment method has been used in [22] to maximize the profit of a hydropower generation company under the uncertainty of inflow. Mean-variance portfolio theory has been used in [23] to maximize the profit of GenCo considering the uncertainties of the emission and electricity markets, and fuel costs. A three-level model of a GenCo has been studied in [24] to maximize the social welfare under the electric demand uncertainty.…”

Section: A Literature Reviewmentioning

confidence: 99%

Offering Decision of Risk-Based Wind-Photovoltaic-Thermal GenCo Using Downside Risk Constraints Approach

et al. 2020

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Section: A Literature Reviewmentioning

confidence: 99%

Offering Decision of Risk-Based Wind-Photovoltaic-Thermal GenCo Using Downside Risk Constraints Approach

et al. 2020

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“…where c i represents the generation cost of producer i, which is calculated by the average coal consumption of the producer [28]. p C i indicates the settlement price for governmentauthorized energy and p M is the MCP in the CM.…”

Section: Decision Framework Of Power Producer's Biddings Under Mpbm I...mentioning

confidence: 99%

Optimal Bidding Strategy for a Power Producer Under Monthly Pre-Listing Balancing Mechanism in Actual Sequential Energy Dual-Market in China

et al. 2019

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At present, electricity transaction in China is mainly conducted by medium-and long-term market contracts, while the spot electricity market has not yet been implemented. An appropriate energy imbalance processing mechanism for medium-and long-term power transactions is highly demanded for maintaining the stability of market operation, since it is supposed to guide market participants to reduce system imbalances and actively provide balancing services. Given this background, a bi-level optimization model for developing optimal bidding strategies of power producer in the monthly sequential contract and balancing markets is proposed based on the currently implemented monthly pre-listing balancing mechanism in China. In the upper level of the model, the monthly utility which makes a tradeoff between revenues and risks produced by the bidding strategy of the producer in the monthly sequential energy dual-market is maximized, considering the uncertainties of the monthly energy imbalances in the power system and the bidding strategies of rivals. In the lower level, the dispatch cost is minimized by simulating the three-stage process of sequential system operation, which includes contract market clearing by power exchange (PX), energy decomposition and modification by the system operator (SO) and balancing market clearing by PX. The simulation results of an eastern provincial electricity market in China show that the presented model can assist power producers in adjusting their monthly bidding strategies with relevant factors, such as the minimum output level of each producer, risk preference, and forecast information including system energy imbalance status and bidding strategies of rivals. In addition, the proposed method is also helpful for market designers in setting market parameters, such as government-authorized contract energy proportion and settlement thresholds in the balancing market.INDEX TERMS Bidding strategy, medium-and long-term market, imbalance processing mechanism, balancing market, monthly pre-listing balancing mechanism.

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“…To meet its electricity production requirements, it procures fuel and carbon permits from their respective markets at competitive price. Long term contracts for fuel and carbon markets are ignored in this work [28].…”

Section: Problem Description and Formulationmentioning

confidence: 99%

Carbon price risk influence on GenCo's portfolio optimization

Mathuria

Bhakar

2014

2014 Eighteenth National Power Systems Conference (NPSC)

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Worldwide stress on low carbon economy and reducing aggregate CO 2 emission levels exposed fossil fuel GenCos to carbon risk associated with prices of carbon permits needed to be environmentally compliant. This risk is substantial for fossil fuel GenCos aiming to maximize profit. This paper addresses a power portfolio optimization approach for a fossil fuel GenCo to maximize profit and minimize risk of volatile input costs and output revenue. Carbon price risk along with fuel and electricity price risk with correlation between all revenue and cost side markets has been considered for portfolio selection using Markowitz mean variance theory. A realistic case study on Nordpool market illustrate that carbon price uncertainty considerations alter trading decision of GenCo in electricity market for efficient risk management. Correlated revenue and cost side markets provides better tradeoff in terms of profit and risk for same risk averse level for GenCo. Under strong correlation of electricity and carbon market a higher allocation in spot market provides risk protection. The carbon price risk impact is prominent for high emission GenCos.Index Terms--Electricity price risk; carbon price risk; fuel price risk; mean variance portfolio theory.

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GenCo's optimal power portfolio selection under emission price risk

Cited by 19 publications

References 26 publications

Offering Decision of Risk-Based Wind-Photovoltaic-Thermal GenCo Using Downside Risk Constraints Approach

Offering Decision of Risk-Based Wind-Photovoltaic-Thermal GenCo Using Downside Risk Constraints Approach

Optimal Bidding Strategy for a Power Producer Under Monthly Pre-Listing Balancing Mechanism in Actual Sequential Energy Dual-Market in China

Carbon price risk influence on GenCo's portfolio optimization

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