Probabilistic game approaches for network cost allocation

Bhakar, Rohit; Sriram, V. S.; Padhy, Narayana Prasad; Gupta, Hari Om

doi:10.1109/pes.2010.5589819

Cited by 8 publications

(10 citation statements)

References 10 publications

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“…A power flow tracing method is used to evaluate characteristic value v ( S ) as well as stand-alone cost v ( i ) of player i of a system [15]. The work follows the ratio for cost allocation between generators and loads as 23:77% in pool market [21].…”

Section: Characteristic Functionmentioning

confidence: 99%

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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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Section: Characteristic Functionmentioning

confidence: 99%

“…In [23], particular loss allocation index (PLAI) method is utilized to evaluate characteristic value as well as stand-alone value, i.e., transmission loss of a system. In this method authors allocated 77% losses to loads and 23% losses to generators [21].…”

Section: Characteristic Functionmentioning

confidence: 99%

Game Theory Application in Smart Energy Logistics and Economy

Khan¹

2018

Game Theory - Applications in Logistics and Economy

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“…(16). It is assumed that a a ୣ୬ : a ୪୭ୟୢ (23:77) split in the transmission usage occurs between generators and demand [19].…”

Section: Model For Power Flow Tracingmentioning

confidence: 99%

“…From the equations (18) and (19) losses are allocated to generators and loads respectively. This method of loss allocation is said to be direct because all the calculation is already done for usage allocation.…”

Section: Model For Transmission Lossmentioning

confidence: 99%

A Multipurpose Matrices Methodology for Transmission Usage, Loss and Reliability Margin Allocation in Restructured Environment

2013

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In the era of power system restructuring there is a need of simplified method which provides a complete allocation of usage, transmission losses and transmission reliability margin. In this paper, authors presents a combined multipurpose matrices methodology for Transmission usage, transmission loss and transmission reliability margin allocation. Proposed methodology is simple and easy to implement on large power system. A modified Kirchhoff matrix is used for allocation purpose. A sample 6 bus system is used to demonstrate the feasibility of proposed methodology.

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“…A comprehensive comparative analysis of various game theoretic models in electricity markets was presented in [15]. In particular, the cooperative game theory provides tools to solve conflicts arising from the interaction, such as in allocation of transmission costs [16]. The solution mechanisms of this approach appreciate fairness, efficiency, and stability in distribution of payoffs among agents.…”

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confidence: 99%

Bidding and Cooperation Strategies for Electricity Buyers in Power Markets

Srinivasan

Trung

Singh

2016

IEEE Systems Journal

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Deregulation of electric power industries in recent years has opened many opportunities for electricity buyers. However, the strong influence of network physical constraints may result in economic decisions that adversely affect the interests of the consumers. Compared with the monopolistic economy of yesteryears, electricity buyers may actually be able to influence the market by cooperating with other buyers in the network. This paper presents a coevolutionary approach to investigate individual and cooperative strategies of buyers in a power market, taking fully into account the physical network constraints. First, the study focuses on deterministic cases, where buyers choose their bidding strategies to maximize the profits in different scenarios of playing individually or cooperatively. It is found that, by evolutionary learning, buyers can benefit from cooperation. After that, the uncertain nature of the market is modeled, where buyers find optimal cooperation strategies to hedge against the risk of low payoffs. The payoff distribution problem in cooperative game theory was linked with the optimal coalition generation problem by proving a theorem. The statistically consistent simulation results show that our approach is able to discover interesting cooperation strategies and can be easily extended to practical networks with a large number of buyers.

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Probabilistic game approaches for network cost allocation

Cited by 8 publications

References 10 publications

Game Theory Application in Smart Energy Logistics and Economy

Game Theory Application in Smart Energy Logistics and Economy

A Multipurpose Matrices Methodology for Transmission Usage, Loss and Reliability Margin Allocation in Restructured Environment

Bidding and Cooperation Strategies for Electricity Buyers in Power Markets

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