Transmission cost allocation by cooperative games and coalition formation

Zolezzi, Juan M.; Rudnick, H.

doi:10.1109/tpwrs.2002.804941

Cited by 158 publications

(40 citation statements)

References 15 publications

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“…The result of this game theoretical approach is determined by playing a cooperative game ( N , C ), where N represents the coalition with n collaborating players (partners), and C the characteristic function ( Zolezzi & Rudnick, 2002 ). This characteristic function is defined by the cost of all possible sub-coalitions S , with S ⊆N .…”

Section: Appendix a Algorithmic Implementation Of The Shapley Valuementioning

confidence: 99%

Multi-objective optimisation models for the travelling salesman problem with horizontal cooperation

Defryn

Sörensen

2018

European Journal of Operational Research

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People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

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Section: Appendix a Algorithmic Implementation Of The Shapley Valuementioning

confidence: 99%

Multi-objective optimisation models for the travelling salesman problem with horizontal cooperation

Defryn

Sörensen

2018

European Journal of Operational Research

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“…A payoff vector is { x represented in Eqs. (1)-(3), namely individual, group, and global rationalities, must be satisfied for fair and equitable allocation to all the players [11]:…”

Section: Terminology Used In Cooperative Game Theorymentioning

confidence: 99%

“…Further, players of a certain coalition are related to each other. But these players are not related to the participants of other coalitions[11].…”

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confidence: 99%

Game Theory Application in Smart Energy Logistics and Economy

Khan¹

2018

Game Theory - Applications in Logistics and Economy

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In many parts of the world, energy sectors are transformed from conventional to the smart deregulated market structures. In such smart deregulated market environment, cooperative game theory can play a vital role for analyzing various smart deregulated market problems. As an optimization tool, cooperative game theory is very useful in smart energy logistics and economy analysis problem. The economy associated with smart deregulated structure can be better optimized and allocated with the help of cooperative game theory. Initially, due to regulated structure, there is no cooperation between different entities of energy sector. But after new market structure, all the entities are free to take their own decisions as an independent entity. Transmission open access of energy logistics is also comes into the picture, as all the generators and demands have the same right to access the transmission system. In this market situation, multiple utilities are using the same energy logistic network. This situation can be formulated as a cooperative game in which generators and demands are represented by players. This chapter deals with energy logistic cost allocation problems for a smart deregulated energy market. It is cooperative in nature as all the agents are using the same energy logistic network.

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“…The main results of solving the DCOPF problem in the present power system x are the vectors Q Gx and d x , as well as l x , that is, the vector of LMPs at the system nodes. With these vectors used, the bulk revenue and payment assessment for various participant groups can be formulated as Equations (8)- (13). These values are suffixed with symbol x for representing their dependence with the vectors of transmission line capacities (Equation (5)) as well as the generation of lower and upper limits (Equation (4)) in the present power system x.…”

Section: Locational Marginal Price-based Revenue and Payment Assessmementioning

confidence: 99%

“…Hence, various approaches, reviewed in [3][4][5], have been presented to recover the remaining fixed part of the transmission costs and allocate it to the users. The postage stamp, contract pass, and megawatt-mile/megavolt ampere-mile derived methods [1,3,4,6,7], transmission capacity withholding [1,8], transmission lines' extent-of-use evaluation-based methods [4,6,[9][10][11][12][13][14][15][16][17], and the evaluation of the participants' profit/loss changes, due to the changes in the network topology or line capacities [5,18,19] are in such group. Additionally, several papers [20][21][22] have used the nodal prices or lines marginal capacity prices 1 modification to equalize the congestion surplus to the total required network revenue.…”

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confidence: 99%

A new market clearing mechanism, based on comprehensive welfare allocation, considering participants' optimality, efficiency, and extent of transmission use

Baghayipour

Foroud

2012

Int. Trans. Electr. Energ. Syst.

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SUMMARY This paper develops a new approach to fairly clear the market and assess the amount of each participant's revenue in a deregulated power system, through modifying the system nodal prices. This approach equalizes the economic profit of each participant group to its fair and rational value. Transco behavior is modeled as an independent entity without direct supervision of an independent system operator, causing the possibility of either making profit or incurring a loss for it. With this method applied, three main results for better system design and operation are produced: The rational and acceptable profit/loss values for all participant groups (producers, customers, and Transco) are determined through fair apportionment of total system profit among them based on their optimality and contribution of profitability to the whole system. The profit/loss value for each of producers and consumers in the system is allocated according to their proportional efficiency and extent of transmission use. Transmission revenue assessment is performed through defining a criterion for evaluating the transmission network optimality. So this approach can correct wrong and unfair economic signals in the previous electricity pricing and participants' revenue assessment methods, presenting such a fairer mechanism for it that each participant's action will be oriented in maximizing the system's total economic efficiency. Copyright © 2012 John Wiley & Sons, Ltd.

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Transmission cost allocation by cooperative games and coalition formation

Cited by 158 publications

References 15 publications

Multi-objective optimisation models for the travelling salesman problem with horizontal cooperation

Multi-objective optimisation models for the travelling salesman problem with horizontal cooperation

Game Theory Application in Smart Energy Logistics and Economy

A new market clearing mechanism, based on comprehensive welfare allocation, considering participants' optimality, efficiency, and extent of transmission use

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