An AMI based measurement and control system in smart distribution grid

Sui, Huibin; Lee, Wei-Jen

doi:10.1109/icps.2011.5890876

Cited by 15 publications

(7 citation statements)

References 3 publications

(3 reference statements)

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“…This approach is aimed at determining the influence of measured signal on an undisturbed RTV signal reception. However, in the case of typical communication standards, applied in industrial control systems [21], [22], [6], [20], [3], [26], [1], [4], [7], [8], [10], [15], [19], [27], instantaneous values of time domain signals are crucial parameters rather than the level of signal spectrum. An analysis of reasons for interference appearance in systems consisting power electronic interfaces indicates that in this case random modulations should not have any advantage over deterministic modulations.…”

Section: Emc Linked Hazard In Smart Gridsmentioning

confidence: 99%

Aggregated conducted interferences generated by group of asynchronous drives with deterministic and random modulation

Smoleński

Bojarşki

Kempski

et al. 2012

2012 Asia-Pacific Symposium on Electromagnetic Compatibility

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Section: Emc Linked Hazard In Smart Gridsmentioning

confidence: 99%

Aggregated conducted interferences generated by group of asynchronous drives with deterministic and random modulation

Smoleński

Bojarşki

Kempski

et al. 2012

2012 Asia-Pacific Symposium on Electromagnetic Compatibility

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“…This may lead to a single point failure or massive blackout. For instance, more than 95% of power outages [19] is owing to distribution system faults (excluding the reason of generation deficiency). In the distributed state estimation, every local estimator computes the state information based on its own measurements and sends it to the global estimator for obtaining a reliable estimation.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive-Then-Combine Dynamic State Estimation Considering Renewable Generations in Smart Grids

Rana

2016

IEEE J. Select. Areas Commun.

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The penetration of renewable distributed energy resources such as wind turbine has been dramatically increased in distribution networks. Due to the intermittent property, the wind power generation patterns vary, which may risk distribution network operations. So, it is intrinsically necessary to monitor wind turbines in a distributed way. This paper presents an adaptivethen-combine distributed dynamic approach for monitoring the grid under lossy communication links between the wind turbines and energy management system. Firstly, the wind turbine is represented by a state-space linear model, with sensors deployed to the obtain the system state information. Based on the mean squared error principle, an adaptive approach is proposed to estimate the local state information. The global estimation is designed by combining estimation results with weighting factors which are calculated by minimizing the estimation error covariance based on semidefinite programming. Finally, the convergence analysis indicates that the estimation error is gradually decreased, so the estimated state converges to the actual state. The efficacy of the developed approach is verified using the wind turbine and IEEE 6-bus distribution system.

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“…29 Box-and-whisker plots of average detector measurements for various drive configurations with deterministic and random modulations and filter IF BW = 9 kHz…”

mentioning

confidence: 99%

Conducted EMI Issues in Smart Grids

Smoleński

2012

Conducted Electromagnetic Interference (EMI) in Smart Grids

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The relatively high level of the generated interference, especially in CISPR A frequency band, and observed malfunctions of electronic equipment caused by converters in relatively distant circuits made it necessary to carry out research of the interference penetration depth into the local grid. The commercially available 25 kW four-quadrant frequency converter (FC2 , Table A.6) with 10 kW asynchronous machine (IM3, Table A.4) has been used in the research on interference flow. Preliminary measurements have been taken in a normalized system comprising the EMI receiver and Line Impedance Stabilization Network (LISN). Figure 3.1 shows the results of measurements using peak and average detectors and typical intermediate frequency bandwidth (IF BW) equal to 200 Hz and 9 kHz for CISPR A and CISPR B frequency range, respectively [14,16,[26][27][28].In order to asses interference penetration depth into the electric grid CM interference currents have been measured in the PE wire of the converter supplied directly from local grid without LISN. The result of the performed measurement in CISPR A frequency band is presented in Fig. 3.2. The conformity of the shapes of the CM current and conducted EMI measured using LISN indicates that CM mode noises are mainly responsible for the high level of the emission introduced by the investigated converter.As has been stated in Chap. 2 the origin of CM interference is the CM voltage source, which inevitably exists in a system as a result of temporary electrical asymmetry at its neutral point. This asymmetry is caused by a pulse-width modulation strategy using a three-phase two-level converter bridge. The common mode voltage in 3-phase circuits is defined as one third of the sum of phase voltages. CM currents emerge as a result of transistor switching in the active rectifier and the inverter, due to a high du/dt value of the CM voltage. The experimental results presented in Figs. 1.12, 1.13 and 1.14 have shown the minor influence of the load state and quadrant of operation on both the level and the shape of the CM current, therefore in all of the cases reported the drive was operated in the forward motoring quadrant R. Smolenski, Conducted Electromagnetic Interference (EMI) in Smart Grids, 3 7 Power Systems,

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An AMI based measurement and control system in smart distribution grid

Cited by 15 publications

References 3 publications

Aggregated conducted interferences generated by group of asynchronous drives with deterministic and random modulation

Aggregated conducted interferences generated by group of asynchronous drives with deterministic and random modulation

An Adaptive-Then-Combine Dynamic State Estimation Considering Renewable Generations in Smart Grids

Conducted EMI Issues in Smart Grids

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