Market power is a result of anti-competitive behaviors in oligopoly power markets. Ex-ante indices evaluate the potential of market power through the capacity analysis of participants. In this study, structural indices are modified, and new indices are proposed to overcome the shortcoming of market power assessment in electricity markets. In the proposed indices, two types of assessment are considered as deterministic and probabilistic terms. These indices evaluate the incentive of each participant (supplier) to exercise market power. The probabilistic term of these indices considers the stochastic and uncertain nature of renewable energy resources. The Monte Carlo method (MCM) is used for modeling the uncertainty of renewable resources. The impact of each participant's transmission constraints, size, generation cost, and geographical differences in market power assessment are considered. Examination of the results taken from an IEEE 30-bus test system confirms the proposed indices' effectiveness in assessing market power potential.
Halakou, E., & Akbari Foroud, A. (2021). New Ex-ante Indices of Market Power Considering the Impact of Renewable Energy Resources in Oligopoly Power Markets. Modeling and Simulation in Electrical and Electronics Engineering, 1(2), 21-35. doi: 10.22075/mseee.2021.21758.1049
MLA
Ehsan Halakou; Asghar Akbari Foroud. "New Ex-ante Indices of Market Power Considering the Impact of Renewable Energy Resources in Oligopoly Power Markets". Modeling and Simulation in Electrical and Electronics Engineering, 1, 2, 2021, 21-35. doi: 10.22075/mseee.2021.21758.1049
HARVARD
Halakou, E., Akbari Foroud, A. (2021). 'New Ex-ante Indices of Market Power Considering the Impact of Renewable Energy Resources in Oligopoly Power Markets', Modeling and Simulation in Electrical and Electronics Engineering, 1(2), pp. 21-35. doi: 10.22075/mseee.2021.21758.1049
VANCOUVER
Halakou, E., Akbari Foroud, A. New Ex-ante Indices of Market Power Considering the Impact of Renewable Energy Resources in Oligopoly Power Markets. Modeling and Simulation in Electrical and Electronics Engineering, 2021; 1(2): 21-35. doi: 10.22075/mseee.2021.21758.1049