Decentralized State Estimation and Bad Measurement Identification: An Efficient Lagrangian Relaxation Approach

Caro, Eduardo; Conejo, Antonio J.; Mı́nguez, Roberto

doi:10.1109/tpwrs.2011.2157367

Cited by 45 publications

(15 citation statements)

References 24 publications

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“…Thus, it is advantageous to relax the tolerances at the first iteration and to modify it by considering neighboring data as variables instead of fixed parameters [29]. In particular, the variable set of optimization problem (2) is extended from to just for the first iteration and the first area in the sequential algorithm.…”

Section: On Convergence Information Interchange and Implementationmentioning

confidence: 99%

Multi-Area Energy and Reserve Dispatch Under Wind Uncertainty and Equipment Failures

Ahmadi-Khatir

Conejo

Cherkaoui

2013

IEEE Trans. Power Syst.

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117

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Abstract-The cross-border trading among electricity markets in an interconnected multi-area system (e.g., in central Europe) and the integration of renewable resources (e.g., wind energy) have remarkably increased in recent years. To efficiently operate such system, a proper coordination among different areas is required. Within this context, a decentralized algorithm for market clearing is proposed in this paper to dispatch simultaneously energy and reserve under wind generation uncertainty and equipment failures. The proposed technique does not require a central operator but just a moderate interchange of information among neighboring areas. Additionally, the benefit of cross-border trading is studied.Index Terms-Decentralized dispatch, energy and reserve, equipment failure, interconnections, multi-area power system, renewable generation. NOTATIONSThe notation is provided below.

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Section: On Convergence Information Interchange and Implementationmentioning

confidence: 99%

Multi-Area Energy and Reserve Dispatch Under Wind Uncertainty and Equipment Failures

Ahmadi-Khatir

Conejo

Cherkaoui

2013

IEEE Trans. Power Syst.

Self Cite

117

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“…They are Diakoptics Theory [7], Dantzig-Wolfe Decomposition [8], and Auxiliary Problem Principle [9]. In the DSE model, optimization methods and distributed computing are applied [10]- [13]. In these papers, the coordination step is suppressed and a continuous boundary data flow is usually considered.…”

Section: Introductionmentioning

confidence: 99%

Improving State Estimation With Real-Time External Equivalents

Ângelos

Asada

2016

IEEE Trans. Power Syst.

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Reduced external networks supplied with real-time data are employed in this paper to solve the state estimation problem in interconnected systems. We propose a method to obtain a composed single system state of different monitored areas with local estimations and external equivalent models, which neither require the use of a coordination agent nor requires extensive data interchange. Phasor measurement unit (PMU) measurements taken from system boundaries are used to provide updated equivalent networks as well as an inter-area synchronism. The approach allows testing erroneous external models directly in the state estimation framework. The detectability of bad data in interconnection measurements are also preserved. Tests with the IEEE 118-bus and IEEE 300-bus systems show robustness and accuracy of the model under different area decomposition schemes with low computational requirements compared to similar conventional approaches.Index Terms-Extended Ward equivalent, external equivalents, phasor measurement units, state estimation.

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“…Besides, the estimation process of telemetering measurements is treated individually and forced them as an additional constraints to the WLS method [9]. Then the constrained minimization problem is solved by the Lagrange multiplier method [10]. In reference [11], the authors are proposed a decentralized SE method, where local estimator are estimated system states by each subregion considering that the border measurements are belonged to the specific local region.…”

Section: Introductionmentioning

confidence: 99%

Kalman Filter Based Microgrid State Estimation Using the Internet of Things Communication Network

Rana

2015

2015 12th International Conference on Information Technology - New Generations

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Recently, the smart grid is expected to modernize the current electricity grid by commencing a new set of technologies and services that make the electricity networks secure, automated controlled, cooperative and sustainable. Consequently, the smart control centre feels the requirement of a robust and scalable technique for state estimation (SE) that allows continuous and accurate wide-area real-time monitoring of power system operation and customer utilization of smart grid. This paper proposes a Kalman filter (KF) based microgrid SE using the internet of things (IoT) communication network under two different sensing scenarios. Particularly, the observation from the multiple distributed energy resources (DERs) information is obtained by a set of sensors, which is transmitted to a control center via the IoT communication network. In this control center, the information is fed to a state estimator program for estimating the states of the multiple DERs. Finally, the simulation results show that the proposed KF based microgrid SE is able to estimate the system states properly in all scenarios. Results indicate that it is better to use the same number of sensors as that of states for properly estimating the DERs states using the IoT communication network.

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Decentralized State Estimation and Bad Measurement Identification: An Efficient Lagrangian Relaxation Approach

Cited by 45 publications

References 24 publications

Multi-Area Energy and Reserve Dispatch Under Wind Uncertainty and Equipment Failures

Multi-Area Energy and Reserve Dispatch Under Wind Uncertainty and Equipment Failures

Improving State Estimation With Real-Time External Equivalents

Kalman Filter Based Microgrid State Estimation Using the Internet of Things Communication Network

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