A Smart Distribution Grid Laboratory

Yamane, Amine; Li, Wei; Bélanger, Jean; Ise, Toshifumi; Iyoda, Isao; Aizono, T.; Dufour, Christian

doi:10.1109/iecon.2011.6119912

Cited by 17 publications

(9 citation statements)

References 5 publications

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“…To guaran tee stability the inductances of the permanent synchronous machine where partially simulated in software and partially implemented on the hardware side. In addition, the stability of the whole PHIL setup can also be improved by using filters in the feedback branch (either in hardware and/or in software) as it is discussed in the literature (e. g. , by Lauss et al [5] and Yamane et al [6] ).…”

Section: Digital Simulation Systemmentioning

confidence: 97%

Implementation of a multi-rating interface for Power-Hardware-in-the-Loop simulations

Lehfuß

Lauss

Strasser

2012

IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society

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The Power-Hardware-in-the-Loop simulation ap proach constitutes a complicated integration of a classical, physical system/device test (hardware) in combination with a pure computer simulation (software). This paper presents a new interface topology that takes advantage of modern real-time system capabilities in order to increase stability and accuracy.Basic requirements are stated in a powerful real-time computing system, in a suitable power amplification stage, as well as in an adequate measurement system. In general, the performance of the used devices in the simulation setup is of crucial importance for the quality of simulation results and conclusions based on the executed tests. Furthermore, a first implementation of the proposed new interface topology is discussed. Actual areas of applications for this work can be found in the industrial research and development area as well as for the research of electric energy systems and electric drives and in modern power electronics.

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Section: Digital Simulation Systemmentioning

confidence: 97%

Implementation of a multi-rating interface for Power-Hardware-in-the-Loop simulations

Lehfuß

Lauss

Strasser

2012

IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society

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“…The proposed supervisory controllers read the DG output voltages and currents in order to generate the DG no-load voltages that are utilized by the DG primary controllers. For more details about RT-LAB and HIL applications, readers can refer to [40]- [42].…”

Section: Real-time Simulationsmentioning

confidence: 99%

Multiagent Supervisory Control for Power Management in DC Microgrids

Hamad

Azzouz

El-Saadany

2015

IEEE Trans. Smart Grid

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This paper proposes multiagent supervisory control for precise power management in isolated dc microgrids. Two power management aspects are considered: 1) equal power sharing, which is realized via a proposed distributed equal power sharing algorithm; and 2) optimal power dispatch, which is achieved through a proposed distributed equal incremental cost (DEIC) algorithm. Both algorithms offer the additional advantage of the ability to restore the average system voltage to its nominal value. The proposed algorithms are based on the application of the average consensus theory along with voltage sensitivity analysis. Each distributed generation (DG) unit exchanges information with its neighbors, thus locally updating its no-load voltage setting to achieve the supervisory control objectives. The incorporation of DG droop-based control renders the proposed algorithms fully distributed with a reduced number of agents. The stability of the proposed algorithms is addressed, as well as the convergence of the proposed DEIC algorithm. Real-time OPAL-RT simulations demonstrate the effectiveness of the proposed algorithms in a hardware-in-the-loop application.

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“…For instance, studies [7,9,[14][15][16][19][20][21][22][23][24][26][27][28]30] show that the information obtained from this approach is compelling evidence for design and corroboration in many applications. In summary, the following are growing uses of time-sequential simulations in smart grid studies: It is possible to classify several time-sequential simulation approaches in terms of the ratio of computation time over simulated time.…”

Section: Time-sequential Simulationmentioning

confidence: 99%

“…The number of validation developments based on real-time simulation has been increasing as a result of the potential capability in many research topics of power systems. Some research centers have successfully deployed this method [9,19,[21][22][23]26,28,30], and powerful power systems laboratories are obtaining a growing role as the next generation of validation for smart grids. The increasing development of powerful computational platforms increases the potential application of studies with large distribution systems, where the solving process has challenging scales.…”

Section: Real-time Simulationmentioning

confidence: 99%

Statistical Inference for Visualization of Large Utility Power Distribution Systems

et al. 2017

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Electrical variable visualization has been widely applied to report the performance and effectiveness of novel devices and strategies in utility power distribution systems. Many graphical alternatives are useful to demonstrate critical characteristics of distribution systems such as voltage regulation or power flow. This visualization of electrical variables can also be an effective approach to analyze, compare and evaluate large-scale systems. However, there is a lack of generalized visualization strategies oriented to perform electrical validations of smart grid strategies in large distribution systems. In this paper, we show that the proposed probabilistic density evolution is a powerful resource for long-term time-sequential simulations. Examinations with an IEEE 8500 node test feeder shows that the proposed approach increases the circuit situational awareness and reduces the validation time. To illustrate this methodology, the dynamic voltage condition was simulated and analyzed to recognize the global effect of voltage regulating equipment. The results show an accurate and convenient support that can be interpreted at first glance. The proper use of long-term field measurements and short time-step simulations is a robust method for future grid research, such as designing an optimum operation of intelligent devices or diagnosing electrical interoperability issues in complex grids.

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A Smart Distribution Grid Laboratory

Cited by 17 publications

References 5 publications

Implementation of a multi-rating interface for Power-Hardware-in-the-Loop simulations

Implementation of a multi-rating interface for Power-Hardware-in-the-Loop simulations

Multiagent Supervisory Control for Power Management in DC Microgrids

Statistical Inference for Visualization of Large Utility Power Distribution Systems

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