Specification, implementation, and hardware-in-the-loop real-time simulation of an active distribution grid

Hooshyar, Hossein; Mahmood, Farhan; Vanfretti, Luigi; Baudette, Maxime

doi:10.1016/j.segan.2015.06.002

Cited by 38 publications

(35 citation statements)

References 17 publications

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“…As shown in Figure 5, two measurement locations have been specified on a grid model [19] that is simulated using the OPAL-RT Technologies real-time simulator [20]. The measured voltages and currents are fed to PMUs through the analogue output ports of the OPAL-RT simulator.…”

Section: Methodsmentioning

confidence: 99%

Extracting Steady State Components from Synchrophasor Data Using Kalman Filters

2016

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Data from phasor measurement units (PMUs) may be exploited to provide steady state information to the applications which require it. As PMU measurements may contain errors and missing data, the paper presents the application of a Kalman Filter technique for real-time data processing. PMU data captures the power system's response at different time-scales, which are generated by different types of power system events; the presented Kalman Filter methods have been applied to extract the steady state components of PMU measurements that can be fed to steady state applications. Two KF-based methods have been proposed, i.e., a windowing-based KF method and "the modified KF". Both methods are capable of reducing noise, compensating for missing data and filtering outliers from input PMU signals. A comparison of proposed methods has been carried out using the PMU data generated from a hardware-in-the-loop (HIL) experimental setup. In addition, a performance analysis of the proposed methods is performed using an evaluation metric.

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Section: Methodsmentioning

confidence: 99%

Extracting Steady State Components from Synchrophasor Data Using Kalman Filters

2016

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“…The sample network has been adopted from an active distribution network model, presented in [17]. Fig.…”

Section: Example 3: Model Synthesis Of a Sample Active Distributiomentioning

confidence: 99%

Real-Time Reduced Steady-State Model Synthesis of Active Distribution Networks Using PMU Measurements

Mahmood

Hooshyar

Lavenius

et al. 2017

IEEE Trans. Power Delivery

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Real-time reduced steady state model synthesis of active distribution networks using PMU measurements. IEEE Transactions on Power DeliveryAccess to the published version may require subscription. N.B. When citing this work, cite the original published paper. Permanent link to this version:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-192943 1  Abstract--Due to the increase of generation sources in distribution networks, it is becoming more and more complex to develop and maintain models of these networks. Network operators need to determine reduced models of distribution networks to be used in grid management functions. This paper presents a novel method that synthesizes steady state models of unbalanced active distribution networks by the use of dynamic measurements (time series) from PMUs. As PMU measurements may contain errors and bad data, the paper presents the application of a Kalman Filter technique for real-time data processing. In addition, PMU data captures the power system's response at different time-scales, which are generated by different types of power system events; the presented Kalman Filter has been improved to extract the steady state component of the PMU measurements to be fed to the steady state model synthesis application. Performance of the proposed methods has been assessed by real-time hardware-in-the-loop simulations on a sample distribution network.Index Terms-active distribution network, Kalman Filter (KF), model synthesis, PMU.

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“…More information about the grid can be found in [7] and [8]. As shown in Figure 1, four different measurement locations at the HV, MV and lowvoltage (LV) levels were equipped with PMUs to acquire synchrophasor data.…”

Section: Test Systemmentioning

confidence: 99%

Testing and analysis of centralized and decentralized mode estimation architectures for active distribution network monitoring

Singh

Hooshyar

Vanfretti

2017

2017 IEEE Manchester PowerTech

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Abstract-This paper presents the results of testing a Phasor Measurement Unit (PMU) data-based mode estimation application deployed within a decentralized architecture using a realtime test platform. By extending the author's previous work in [1], this paper shows that a decentralized architecture is effective in detecting local modes which are less observable in presence of other dominant modes when estimated in a centralized architecture. The tests in this paper were carried out that was coupled with actual PMUs, a Phasor Data Concentrator (PDC) and two types of mode estimation architectures. The is network comprised of a high voltage network connected to an Active Distribution Network (ADN) with Renewable Energy Resources (RES). In the decentralized architecture where each PMU was associated with its own processing unit running to compute mode estimates from the acquired time-series data. The results of the decentralized mode estimation architecture are analyzed and compared with centralized architecture.

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Specification, implementation, and hardware-in-the-loop real-time simulation of an active distribution grid

Cited by 38 publications

References 17 publications

Extracting Steady State Components from Synchrophasor Data Using Kalman Filters

Extracting Steady State Components from Synchrophasor Data Using Kalman Filters

Real-Time Reduced Steady-State Model Synthesis of Active Distribution Networks Using PMU Measurements

Testing and analysis of centralized and decentralized mode estimation architectures for active distribution network monitoring

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