Equilibria in the competitive retail electricity market considering uncertainty and risk management

Kharrati, Saeed; Kazemi, Mostafa; Ehsan, Mehdi

doi:10.1016/j.energy.2016.03.069

Cited by 36 publications

(13 citation statements)

References 30 publications

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“…Similarly, Deng and Oren (2006) review the applications of various financial derivatives in the electricity market, i.e., electricity derivatives, and analyze the effects of these derivatives in reducing market risks and optimizing hedging strategies. Taking CVaR as the risk measure, Kharrati et al (2016) construct a model for the decision-making problem of the retailers in the competitive retail power market. The numerical results show that the decisions of rivals will affect the strategies selected by the retailers.…”

Section: Introductionmentioning

confidence: 99%

How to Promote Compliance Management in the Electricity Market? An Analysis Based on the Evolutionary Game Model

Jin¹,

Chen²,

Li³

et al. 2021

Front. Environ. Sci.

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In this paper, we aim to analyze how to effectively promote compliance management in the electricity market. We construct an evolutionary game model under the two different scenarios, i.e., the scenario without governmental supervision and the scenario with governmental supervision, and explicitly describes the strategic behaviors and dynamic evolution process of power enterprises and regulators in the power market. According to the results of the evolutionary stable strategy, we find that, in the absence of governmental supervision, the long-term stable equilibrium of power enterprises' choice of strategy “Compliance” and regulatory agencies' choice of strategy “Not bribery” is hard to be realized. Only if the government effectively supervises the compliance management of the electricity market can the ideal compliance behavior of the two stakeholders be achieved. Furthermore, we conduct a simulation study to analyze the impacts of the various model parameters on the dynamic evolution process. The specific results show that the lower compliance cost, the higher psychological cost, and the larger profit loss of the power enterprises, as well as the lower inspection cost, the higher psychological cost, and the larger rewards of the regulatory agencies, can promote the formation of compliance management. Besides, the larger penalty charged by the government is also conducive to the compliance management of the electricity market.

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Section: Introductionmentioning

confidence: 99%

How to Promote Compliance Management in the Electricity Market? An Analysis Based on the Evolutionary Game Model

Jin¹,

Chen²,

Li³

et al. 2021

Front. Environ. Sci.

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show abstract

“…Zare et al proposed a risk-based electricity procurement model for large consumers, which considers the risk preference of large consumers and uncertainties related to pool price and expected procurement cost by using information gap decision theory, and the electricity procurement decision was evaluated by two criteria including the robustness of decision against experiencing high procurement costs and the opportunity of taking advantage of low procurement costs [15]. Kharrati et al proposed an equilibrium model for electricity retailer's medium-term decision making, which modelled consumer's retail choice behavior with an econometric model and employed Conditional Value at Risk (CVaR) to tackle retailer's risk caused by rivals' strategy, and the Lagrangian relaxation method and Nash equilibrium point of the competitive retailers were used to solve this model [16]. Deng et al proposed a real-time pricing model for industrial, residential, and commercial consumers by electricity retailers with the consideration of uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Business Risk Evaluation of Electricity Retail Company in China Using a Hybrid MCDM Method

2020

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Electricity retail marketization reform is in progress in China, and many electricity retail companies (ERC) have been founded. The comprehensive evaluation of business risk for ERC can help effectively manage business risk and reduce risk loss, which is vital for its healthy and sustainable development. In this paper, a new hybrid multi-criteria decision making (MCDM) method integrating the Bayesian best-worst method (BBWM) and improved matter-element extension model (IMEEM) is proposed for business risk evaluation for an ERC. The latest group MCDM method, namely the BBWM is employed to determine risk criteria weights, and the IMEEM is used to rank the business risk of ERC. The evaluation index system is built including three aspects of economic operation risk, marketable risk and political risk. The business risk of ERC in China is evaluated by using the proposed MCDM method, and the result shows the current business risk belongs to ‘High’ grade and closer to ‘Very High’ grade more. The proposed MCDM method for business risk evaluation of ERC is effective and practical, which can provide references for risk management and sustainable development of ERC.

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“…objective Nash-Cournot model was adopted in [29] to simulate the demand response under load uncertainty. A game based linear approach for retailer's scheduling under uncertain pool prices and load demands was presented in [30]. The scenario generation method and conditional value at risk (CVaR) are used for risk measurement.…”

Section: Introductionmentioning

confidence: 99%

Analyzing and validating the economic efficiency of managing a cluster of energy hubs in multi-carrier energy systems

et al. 2018

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Equilibria in the competitive retail electricity market considering uncertainty and risk management

Cited by 36 publications

References 30 publications

How to Promote Compliance Management in the Electricity Market? An Analysis Based on the Evolutionary Game Model

How to Promote Compliance Management in the Electricity Market? An Analysis Based on the Evolutionary Game Model

Business Risk Evaluation of Electricity Retail Company in China Using a Hybrid MCDM Method

Analyzing and validating the economic efficiency of managing a cluster of energy hubs in multi-carrier energy systems

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