Multi-area coordinated decentralized DC optimal power flow

Conejo, Antonio J.; Aguado, José A.

doi:10.1109/59.736264

Cited by 268 publications

(123 citation statements)

References 12 publications

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“…In addition, Xa also contains information on the control variables for area a, such as real and reactive power generation, phase-shifter angles, voltage control settings and transformer taps settings, for example. Constraints (13) represent the power fiow equations and transmission capacity limits (9)- (11) for those lines and buses interconnecting different areas. Constraints (14) include the power fiow equations and transmission capacity limits (9)- (11), only for those lines and buses lying within a given area, and limits over dependent and control variables (5)- (8).…”

Section: Problem Formulationmentioning

confidence: 99%

“…Constraints (13) represent the power fiow equations and transmission capacity limits (9)- (11) for those lines and buses interconnecting different areas. Constraints (14) include the power fiow equations and transmission capacity limits (9)- (11), only for those lines and buses lying within a given area, and limits over dependent and control variables (5)- (8). It should be noted that the sets of constrains (13) and (14) represent both equality and inequality constraints.…”

Section: Problem Formulationmentioning

confidence: 99%

“…The power fiow equations are included in the model as constraints (2), (3); there are two equations for each bus of the global system, representing the active and reactive power balance in each node, (9) where a = 1, ... , A, and the superscripts a indicate the area for each constant and variable.…”

Section: Problem Formulationmentioning

confidence: 99%

“…Particularly remarkable is the theoretical decomposition framework based on the auxiliary problem principIe ana1yzed in [6][7][8]. An application ofLagrangian relaxation to solve a multi-area OPF is described in [1,9], while in [2,14] an augmented Lagrangian relaxation procedure is used to sol ve a distributed OPF. In sorne cases, Lagrangian procedures may present drawbacks, such as difficulties to converge to an optimal solution for the global system (in the absence of convexity assumptions), and convergence rates that depend on the correct choice of the values for several parameters which may be difficult to update, and require the intervention of a central agent to update this information.…”

Section: Introductionmentioning

confidence: 99%

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Nogales

Prieto

Conejo

2003

Annals of Operations Research

177

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Abstract. This paper describes a decomposition methodology applied to the multi-area optimal power fiow problem in the context of an electric energy system. The proposed procedure is simple and efficient, and presents sorne advantages with respect to other common decomposition techniques such as Lagrangian relaxation and augmented Lagrangian decomposition. The application to the multi-area optimal power fiow problem allows the computation of an optimal coordinated but decentralized solution. The proposed method is appropriate for an Independent System Operator in charge of the electric energy system technical operation. Convergence properties of the proposed decomposition algorithm are described and related to the physical coupling between the areas. Theoretical and numerical results show that the proposed decentralized methodology has a lower computational cost than other decomposition techniques, and in large large-scale cases even lower than a centralized approach.

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Section: Problem Formulationmentioning

confidence: 99%

Section: Problem Formulationmentioning

confidence: 99%

Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Untitled

Nogales

Prieto

Conejo

2003

Annals of Operations Research

177

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“…On one hand, ad-hoc decentralized control schemes have been proposed, as in [5], [6] for example. 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.…”

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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Some Optimization Models and Techniques for Electric Power System Short‐term Operations

Sun

Phan

2011

Wiley Encyclopedia of Operations Research and Management Science

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This article introduces modern optimization models and solution methods for two fundamental decision‐making problems in electric power system short‐term operations, namely the optimal power flow (OPF) problem and the unit commitment (UC) problem. This article reviews basic formulations and surveys some of the most recent advances, including global optimization techniques for exact solution of the OPF problem, adaptive robust optimization models for the UC problem under uncertainty of renewable generation and demand‐side response, contingency analysis for large‐scale power systems, and distributed optimization schemes for decentralized operation.

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Multi-area coordinated decentralized DC optimal power flow

Cited by 268 publications

References 12 publications

Untitled

Untitled

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

Some Optimization Models and Techniques for Electric Power System Short‐term Operations

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