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- Creators: Ayyanar, Raja
Description
In modern electric power systems, energy management systems (EMSs) are responsi-ble for monitoring and controlling the generation system and transmission networks. State estimation (SE) is a critical `must run successful' component within the EMS software. This is dictated by the high reliability requirements and need to represent the closest real time model for market operations and other critical analysis functions in the EMS. Tradi-tionally, SE is run with data obtained only from supervisory control and data acquisition (SCADA) devices and systems. However, more emphasis on improving the performance of SE drives the inclusion of phasor measurement units (PMUs) into SE input data. PMU measurements are claimed to be more accurate than conventional measurements and PMUs `time stamp' measurements accurately. These widely distributed devices meas-ure the voltage phasors directly. That is, phase information for measured voltages and currents are available. PMUs provide data time stamps to synchronize measurements. Con-sidering the relatively small number of PMUs installed in contemporary power systems in North America, performing SE with only phasor measurements is not feasible. Thus a hy-brid SE, including both SCADA and PMU measurements, is the reality for contemporary power system SE. The hybrid approach is the focus of a number of research papers. There are many practical challenges in incorporating PMUs into SE input data. The higher reporting rates of PMUs as compared with SCADA measurements is one of the salient problems. The disparity of reporting rates raises a question whether buffering the phasor measurements helps to give better estimates of the states. The research presented in this thesis addresses the design of data buffers for PMU data as used in SE applications in electric power systems. The system theoretic analysis is illustrated using an operating electric power system in the southwest part of the USA. Var-ious instances of state estimation data have been used for analysis purposes. The details of the research, results obtained and conclusions drawn are presented in this document.
ContributorsMurugesan, Veerakumar (Author) / Vittal, Vijay (Committee member) / Heydt, Gerald (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
Description
The Smart Grid initiative describes the collaborative effort to modernize the U.S. electric power infrastructure. Modernization efforts incorporate digital data and information technology to effectuate control, enhance reliability, encourage small customer sited distributed generation (DG), and better utilize assets. The Smart Grid environment is envisioned to include distributed generation, flexible and controllable loads, bidirectional communications using smart meters and other technologies. Sensory technology may be utilized as a tool that enhances operation including operation of the distribution system. Addressing this point, a distribution system state estimation algorithm is developed in this thesis. The state estimation algorithm developed here utilizes distribution system modeling techniques to calculate a vector of state variables for a given set of measurements. Measurements include active and reactive power flows, voltage and current magnitudes, phasor voltages with magnitude and angle information. The state estimator is envisioned as a tool embedded in distribution substation computers as part of distribution management systems (DMS); the estimator acts as a supervisory layer for a number of applications including automation (DA), energy management, control and switching. The distribution system state estimator is developed in full three-phase detail, and the effect of mutual coupling and single-phase laterals and loads on the solution is calculated. The network model comprises a full three-phase admittance matrix and a subset of equations that relates measurements to system states. Network equations and variables are represented in rectangular form. Thus a linear calculation procedure may be employed. When initialized to the vector of measured quantities and approximated non-metered load values, the calculation procedure is non-iterative. This dissertation presents background information used to develop the state estimation algorithm, considerations for distribution system modeling, and the formulation of the state estimator. Estimator performance for various power system test beds is investigated. Sample applications of the estimator to Smart Grid systems are presented. Applications include monitoring, enabling demand response (DR), voltage unbalance mitigation, and enhancing voltage control. Illustrations of these applications are shown. Also, examples of enhanced reliability and restoration using a sensory based automation infrastructure are shown.
ContributorsHaughton, Daniel Andrew (Author) / Heydt, Gerald T (Thesis advisor) / Vittal, Vijay (Committee member) / Ayyanar, Raja (Committee member) / Hedman, Kory W (Committee member) / Arizona State University (Publisher)
Created2012
Description
In electric power systems, phasor measurement units (PMUs) are capable of providing synchronized voltage and current phasor measurements which are superior to conventional measurements collected by the supervisory control and data acquisition (SCADA) system in terms of resolution and accuracy. These measurements are known as synchrophasor measurements. Considerable research work has been done on the applications of PMU measurements based on the as-sumption that a high level of accuracy is obtained in the field. The study in this dissertation is conducted to address the basic issue concerning the accuracy of actual PMU measurements in the field. Synchronization is one of the important features of PMU measurements. However, the study presented in this dissertation reveals that the problem of faulty synchronization between measurements with the same time stamps from different PMUs exists. A Kalman filter model is proposed to analyze and calcu-late the time skew error caused by faulty synchronization. In order to achieve a high level of accuracy of PMU measurements, inno-vative methods are proposed to detect and identify system state changes or bad data which are reflected by changes in the measurements. This procedure is ap-plied as a key step in adaptive Kalman filtering of PMU measurements to over-come the insensitivity of a conventional Kalman filter. Calibration of PMU measurements is implemented in specific PMU instal-lation scenarios using transmission line (TL) parameters from operation planning data. The voltage and current correction factors calculated from the calibration procedure indicate the possible errors in PMU measurements. Correction factors can be applied in on-line calibration of PMU measurements. A study is conducted to address an important issue when integrating PMU measurements into state estimation. The reporting rate of PMU measurements is much higher than that of the measurements collected by the SCADA. The ques-tion of how to buffer PMU measurements is raised. The impact of PMU meas-urement buffer length on state estimation is discussed. A method based on hy-pothesis testing is proposed to determine the optimal buffer length of PMU meas-urements considering the two conflicting features of PMU measurements, i. e. un-certainty and variability. Results are presented for actual PMU synchrophasor measurements.
ContributorsZhang, Qing (Author) / Heydt, Gerald (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Ayyanar, Raja (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2012