The TC-PSI indicator for forecasting the potential for market power in wholesale electricity markets

Hesamzadeh, Mohammad Reza; Biggar, Darryl R.; Hosseinzadeh, Nasser

doi:10.1016/j.enpol.2011.06.061

Cited by 28 publications

(15 citation statements)

References 20 publications

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“…The underlined numbers in Table 3 indicate the located bus of each unit. These values demonstrate the proposed LMP_S i market power index for each unit as introduced in (7). The following results can be concluded from power index could be a good basis for the structural analysis of the potential of a collusion formation in the market.…”

Section: Fig 3 Lmps and Their Constructive Componentssupporting

confidence: 56%

“…The regulatory evaluates the market power using some indices. The market power indices may be quantity-based [7] such as Herfindahl-Hirschman index (HHI), pivotal supplier index (PSI) and residual supply index (RSI), and price-based such as output gap and Lerner index (LI) [8]. GenCos owning a great share of the market or locating at the strategic bus of the network are able to exercise market power through strategic behavior [9].…”

Section: Introductionmentioning

confidence: 99%

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Locational marginal price share: a new structural market power index

Hajiabadi

Samadi

2019

J. Mod. Power Syst. Clean Energy

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Market power is known as the ability of units and generation companies (GenCos) to change electricity price profitably. As cleared in the definition, locational marginal price (LMP) is the most important key in market power evaluation. Therefore, the main objective of the paper is to analyze market power of units and GenCos based on their abilities to change electricity price. At the first step, using Karush-Kuhn-Tucker (KKT) conditions of Lagrangian method, LMP is decomposed into four main components. These components indicate the share of each unit at the LMP of each bus. These values are calculated by the proposed analytical method, and cannot be obtained using simulation methods. At the second step, ''unit-based LMP_S'' index, which indicates the contribution factor of each unit at LMP of each bus, is proposed as a new structural market power index. This index is also used as an effective tool to determine the most profitable coalition between two units. Using that, the market operator can predict highly potential collusions. Moreover, ''GenCosbased LMP_S'' index is proposed. Using this effective tool, the contribution of each GenCo, which owns multiple units in various buses, at the LMP of each bus is discovered. The proposed market power indices are calculated on the IEEE 24-bus test system and compared with some conventional structural market power indices. Incremental profits of units due to change of unit's strategies verify the accuracy of proposed method.

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Section: Fig 3 Lmps and Their Constructive Componentssupporting

confidence: 56%

Section: Introductionmentioning

confidence: 99%

Locational marginal price share: a new structural market power index

Hajiabadi

Samadi

2019

J. Mod. Power Syst. Clean Energy

View full text Add to dashboard Cite

show abstract

“…3.3.1 Effect of demand variation on TCBAI: Demand variation can have influential effect on MP. Equation (8) demonstrates that if the amount of demand becomes equal or lower than the amount of supply from cheaper competitors, the generator's bid will not be accepted, and therefore, it cannot exercise MP. Moreover, the lower the amount of demand is, the more incentive the generator has to exercise MP.…”

Section: Blocks' Acceptability In a Transmission-constrained Systemmentioning

confidence: 99%

“…The bids of generator's competitors can also influence the generator's potential of MP. According to (8), the only competitors who can affect TCBAI of a generator are the competitors who offer lower prices in comparison with offered prices of the generator. In this paper, these competitors are called 'cheaper competitors'.…”

Section: Effect Of Competitors' Behaviour On Tcbaimentioning

confidence: 99%

“…The impacts of load variation, generator size, random failures and transmission constraints were considered in an expected nodal must-run share index suggested by [6]. The authors [7,8] generalised the conventional indices residual supply index and pivotal supplier index to transmission-constrained residual supply index (TCRSI) and transmission-constrained pivotal supplier index (TCPSI), respectively. TCRSI performs a firm-based analysis of MP, regarding transmission constraints.…”

Section: Introductionmentioning

confidence: 99%

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