Inter-Utilities Power-Exchange Coordination: A Market-Oriented Approach

Aguado, José A.; Quintana, V.H.

doi:10.1109/mper.2001.4311472

Cited by 34 publications

(28 citation statements)

References 21 publications

(21 reference statements)

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“…2) Decentralized scheme: To deal with the above dimensionality and confidentiality issues, decentralized algorithms have been proposed such as those reported in [13], [14], [15]. Simply stated, the interconnected system being decomposed into separate sub-systems, each controlled by a player, the aim is to process the information of each sub-system locally, while at the same time solving the system-wide problem (4).…”

Section: ) Centralized Schemementioning

confidence: 99%

A framework for the simultaneous clearing of multiple markets within a common transmission system

Marinakis

Rosehart

Cutsem

2009

2009 IEEE Bucharest PowerTech

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Abstract-The possibility for market participants to place their bids in all the markets of an interconnection irrespective of where they are physically connected is investigated in this paper. A mechanism is proposed for managing the resulting congestion. It consists in iteratively sharing the transmission line capacities between the different market operators based each time on their present schedules. The algorithm is applied on a small test system. The results are assessed in terms of their property of being Nash equilibria and of their distance of the set of Pareto optimal operating points.

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Section: ) Centralized Schemementioning

confidence: 99%

A framework for the simultaneous clearing of multiple markets within a common transmission system

Marinakis

Rosehart

Cutsem

2009

2009 IEEE Bucharest PowerTech

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“…Decentralized optimization includes Lagrangian relaxation, Benders decomposition and optimality condition decomposition (OCD). The main idea of Lagrangian relaxation is to add shared constraints to each subproblem and update multipliers [13]. Augmented Lagrangian based decomposition [14][15][16][17][18] is the extended method of Lagrangian relaxation and used widely in multi-area optimal power flow (OPF).…”

Section: Introductionmentioning

confidence: 99%

“…However, [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] are focused on coordinated optimization between TNs and subsystems are parallel to each other. So all sub optimization problems use the variables of same nature, which does not apply to coordinated scheduling problem between ADNs and TN.…”

Section: Introductionmentioning

confidence: 99%

Coordinated scheduling model of power system with active distribution networks based on multi-agent system

Hao

Jiang

2017

J. Mod. Power Syst. Clean Energy

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With the large-scale development of distributed generations (DGs) and the connection into the main grid of active distribution networks (ADNs), traditional centralized dispatch of power system has encountered enormous challenge. In a bilateral electricity market, introducing ADN resources in the day-ahead generation schedule will not only enrich the dispatch patterns to the power system, but also reflect the initiative of ADNs. This paper proposes a coordinated scheduling model of power system with a plurality of ADNs based on multi-agent system where ADN agents are brought in the day-ahead market clearing. The process of market clearing and the dispatch of DGs in ADNs are independent with each other but linked together through the market clearing price (MCP) and bid volume. The optimal operating point of the whole system is achieved through multiple information exchange. In comparison with the dispatch without interaction between ADNs and the market operator (MO), the coordinated scheduling model is applied in a system with four ADNs to verify that the proposed method can improve the overall interests of ADNs. Finally, the effects of storage device and tie-line power limit are analyzed.

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“…On the other hand, efforts have been made to create higher-level entities, which would be in charge of coordinating operation over very large geographical areas. By way of example, the potential benefits of a centralized control center (CCC) to make decisions for multi-TSO systems are emphasized in [7].…”

Section: Introductionmentioning

confidence: 99%

A fair method for centralized optimization of multi-TSO power systems

Phulpin

Begović

Petit

et al. 2009

International Journal of Electrical Power & Energy Systems

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Abstract-This paper addresses the problem of centralized optimization of an interconnected power system partitioned into several regions controlled by different transmission system operators (TSOs). It is assumed that those utilities have agreed to transferring some of their competencies to a centralized control center, which is in charge of setting the control variables in the entire system to satisfy every utility's individual objective. This paper proposes an objective method for centralized optimization of such multi-TSO power systems, which relies on the assumption that each TSO has a real-valued optimization function focusing on its control area only. This method is illustrated on the IEEE 118 bus system partitioned into three TSOs. It is applied to the optimal reactive power dispatch problem, where the control variables are the voltage settings for generators and compensators. After showing that the method has some properties of fairness, namely freedom from envy, efficiency, accountability, and altruism, we emphasize its robustness with respect to certain biased behavior of the different TSOs.

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Inter-Utilities Power-Exchange Coordination: A Market-Oriented Approach

Cited by 34 publications

References 21 publications

A framework for the simultaneous clearing of multiple markets within a common transmission system

A framework for the simultaneous clearing of multiple markets within a common transmission system

Coordinated scheduling model of power system with active distribution networks based on multi-agent system

A fair method for centralized optimization of multi-TSO power systems

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