Three-phase linear state estimation using Phasor Measurements

Jones, Kevin D.; Thorp, James S.; Gardner, R. Matthew

doi:10.1109/pesmg.2013.6672516

Cited by 93 publications

(40 citation statements)

References 6 publications

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“…C37.118 [19,20]. Examples of time latencies and accuracy of real-time state estimation processes fully based on PMU data are discussed in [21,22]. Typical time latencies of less than 200 ms can be achieved in order to determine the system state with relevant refresh rates of some tens of milliseconds.…”

Section: Agents and The Interaction Between Themmentioning

confidence: 99%

A composable method for real-time control of active distribution networks with explicit power setpoints. Part I: Framework

Bernstein

Reyes-Chamorro

Boudec

et al. 2015

Electric Power Systems Research

134

168

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a b s t r a c tThe conventional approach for the control of distribution networks, in the presence of active generation and/or controllable loads and storage, involves a combination of both frequency and voltage regulation at different time scales. With the increased penetration of stochastic resources, distributed generation and demand response, this approach shows severe limitations in both the optimal and feasible operation of these networks, as well as in the aggregation of the network resources for upper-layer power systems. An alternative approach is to directly control the targeted grid by defining explicit and real-time setpoints for active/reactive power absorptions/injections defined by a solution of a specific optimization problem; but this quickly becomes intractable when systems get large or diverse. In this paper, we address this problem and propose a method for the explicit control of the grid status, based on a common abstract model characterized by the main property of being composable. That is to say, subsystems can be aggregated into virtual devices that hide their internal complexity. Thus the proposed method can easily cope with systems of any size or complexity. The framework is presented in this Part I, whilst in Part II we illustrate its application to a CIGRÉ low voltage benchmark microgrid. In particular, we provide implementation examples with respect to typical devices connected to distribution networks and evaluate of the performance and benefits of the proposed control framework.

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Section: Agents and The Interaction Between Themmentioning

confidence: 99%

A composable method for real-time control of active distribution networks with explicit power setpoints. Part I: Framework

Bernstein

Reyes-Chamorro

Boudec

et al. 2015

Electric Power Systems Research

134

168

View full text Add to dashboard Cite

show abstract

“…In this paper it is supposed that measurements consist of phasors of bus voltages and nodal-injected current sent by a certain number of PMUs deployed in the network to guarantee its observability (e.g. [3]). The availability of bus voltage and nodal-injected current phasors allow the use of linear SEs.…”

Section: The Adopted Discrete Kalman Filtermentioning

confidence: 99%

“…The time frames for these functionalities vary between few hundreds of ms (fault detection and location) to few tens/hundreds of seconds (fast and slow voltage control and line congestions), so they might require the knowledge of the network state with relatively high refresh rates. This is driving the development of the so-called "RealTime State Estimators" (RTSEs) for which a drastic reduction of the computational burden can be achieved using Phasor Measurement Units (PMUs) (e.g., [3], [4]). …”

Section: Introductionmentioning

confidence: 99%

“…A large number of papers have been published using post-estimation analysis (e.g., [9], [10]) and this method has been recognized as providing good performances. On the other hand, when dealing with realtime monitoring of power systems, where speed and time determinism are key aspects (e.g., [3], [4]), one can take advantage of a predicted system state in order to obtain a consistent set of measurements to be compared with the real ones.…”

Section: Introductionmentioning

confidence: 99%

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A pre-estimation filtering process of bad data for linear power systems state estimators using PMUs

Pignati

Zanni

Sarri

et al. 2014

2014 Power Systems Computation Conference

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Abstract-The paper proposes a specific algorithm for the pre-estimation filtering of bad data (BD) in PMU-based power systems linear State Estimators (SEs). The approach is framed in the context of the so-called real-time SEs that take advantage of the high measurement frame rate made available by PMUs (i.e., 50 -60 frames per second). In particular, the proposed algorithm examines PMU measurement innovations for each new received set of data in order to locate anomalies and apply countermeasures. The detection and identification scheme is based on: (i) the forecasted state of the network obtained by means of a linear Kalman filter, (ii) the current network topology, (iii) the accuracy of the measurement devices and (iv) their location. The incoming measurement from each PMU is considered reliable, or not, according to a dynamic threshold defined as a function of the confidence of the predicted state estimated by using an AutoRegressive Integrated Moving Average (ARIMA) process. The performances of the proposed algorithm are validated with respect to single and multiple bad data of different nature and magnitudes. Furthermore, the algorithm is also tested against faults occurring in the power system to show its robustness during these unexpected operating conditions.

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“…The implementation, testing and performance assessment of a phasor-assisted state estimation for transmission networks is provided in [11]. A 3-phase linear-state estimation using phasor measurements only is presented in [12]. This is the first real implementation able to provide the 3-phase system's state with a refresh rate up to 30 times per second.…”

Section: State Of the Artmentioning

confidence: 99%

Real-time state estimation of the EPFL-campus medium-voltage grid by using PMUs

Pignati

Popović

Barreto

et al. 2015

2015 IEEE Power &Amp; Energy Society Innovative Smart Grid Technologies Conference (ISGT)

115

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Abstract-We describe the real-time monitoring infrastructure of the smart-grid pilot on the EPFL campus. We experimentally validate the concept of a real-time state-estimation for a 20 kV active distribution network. We designed and put into operation the whole infrastructure composed by the following main elements: (1) dedicated PMUs connected on the medium-voltage side of the network secondary substations by means of specific current/voltage transducers; (2) a dedicated communication network engineered to support stringent time limits and (3) an innovative state estimation process for real-time monitoring that incorporates phasor-data concentration and state estimation processes. Special care was taken to make the whole chain resilient to cyber-attacks, equipment failures and power outages. The achieved latency is within 65ms. The refresh rate of the estimated state is 20ms. The real-time visualization of the state estimator output is made publicly available, as well as the historical data (PMU measurements and estimated states). To the best of our knowledge, the work presented here is the first operational system that provides low-latency real-time stateestimation by using PMU measurements of a real active distribution network.

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Three-phase linear state estimation using Phasor Measurements

Cited by 93 publications

References 6 publications

A composable method for real-time control of active distribution networks with explicit power setpoints. Part I: Framework

A composable method for real-time control of active distribution networks with explicit power setpoints. Part I: Framework

A pre-estimation filtering process of bad data for linear power systems state estimators using PMUs

Real-time state estimation of the EPFL-campus medium-voltage grid by using PMUs

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