The research topics presented in this dissertation focus on validation of customer-level voltage synchrophasor data for transmission system analysis, detection and categorization of power system events as measured by phasor measurement units (PMUs), and identification of the influence of power system conditions (wind power, daily and seasonal load variation) on low-frequency oscillations. Synchrophasor data can provide information across entire power systems but obtaining the data, handling the large dataset and developing tools to extract useful information from it is a challenge. To overcome the challenge of obtaining data, an independent synchrophasor network was created by taking synchrophasor measurements at customer-level voltage. The first objective is to determine if synchrophasor data taken at customer-level voltage is an accurate representation of power system behavior. The validation process was started by installing a transmission level (69 kV) PMU. The customer-level voltage measurements were validated by comparison of long term trends and low-frequency oscillations estimates. The techniques best suited for synchrophasor data analysis were identified after a detailed study and comparison. The same techniques were also applied to detect power system events resulting in the creation of novel categories for numerous events based on shared characteristics. The numerical characteristics for each category and the ranges of each numerical characteristic for each event category are identified. The final objective is to identify trends in power system behavior related to wind power and daily and seasonal variations by utilizing signal processing and statistical techniques. / text

<p>Today’s electrical transmission & distribution systems, are facing a number of challenges related to changing environmental, technical and business factors. Among these factors are, increased environmental restrictions leading to higher share of production from renewable and uncontrollable sources as well as local environmental concerns regarding construction of new transmission and distribution lines. The re-regulation of the electricity market has created a dynamic environment in which multiple organizations have to coordinate and cooperate in the operation and control of the power system. Finally, the high rate of devel-opment within the ICT field is creating many new opportunities for power system opera-tion and control, thanks to introduction of new technologies for measurement, communi-cation and automation.</p><p>As a result of these factors, Wide Area Monitoring and Control (WAMC) systems have been proposed. WAMC systems utilize new ICT based technologies to offer more accurate and timely data on the state of the power system. WAMC systems utilize Phasor Measure-ment Units (PMUs) that have higher data rates and are time synchronised using, GPS satel-lites. This allows synchronized observation of the dynamics of the power system, making it possible to manage the system at a more efficient and responsive level and apply wide area control and protection schemes. The success WAMC systems, on the other hand, are largely dependent on the performance of the Information and Communication Technology (ICT) infrastructure that would support them.</p><p>This thesis investigates the requirements on, and suitability of the ICT systems that support WAMC systems. This was done by identifying WAMC applications and the elicitation of their requirements. Furthermore, a set of simulation projects were carried out to determine the communication system characteristics such as delay and the impact of this delay on the WAMC system.</p><p>This thesis has several contributions. First, it provides summary and analysis of WAMC application priorities and requirements in the Nordic region. Secondly it provides simula-tion based comparison and evaluation of communication paradigms for WAMC systems. The research documented in this thesis addresses these paradigms by providing a compari-son and evaluation through simulation. Thirdly, the thesis provides insight to the possible sources of delay in WAMC architecture and the impact of these delays on data quality specifically data incompleteness. This provides insight on what applications are important to practitioners and what is the expected performance of these applications, as seen from the power system control and operation point of view.</p>

Big data has received a momentum from both academia and industry. The MapReduce model has emerged into a major computing model in support of big data analytics. Hadoop, which is an open source implementation of the MapReduce model, has been widely taken up by the community. Cloud service providers such as Amazon EC2 cloud have now supported Hadoop user applications. However, a key challenge is that the cloud service providers do not a have resource provisioning mechanism to satisfy user jobs with deadline requirements. Currently, it is solely the user responsibility to estimate the require amount of resources for their job running in a public cloud. This thesis presents a Hadoop performance model that accurately estimates the execution duration of a job and further provisions the required amount of resources for a job to be completed within a deadline. The proposed model employs Locally Weighted Linear Regression (LWLR) model to estimate execution time of a job and Lagrange Multiplier technique for resource provisioning to satisfy user job with a given deadline. The performance of the propose model is extensively evaluated in both in-house Hadoop cluster and Amazon EC2 Cloud. Experimental results show that the proposed model is highly accurate in job execution estimation and jobs are completed within the required deadlines following on the resource provisioning scheme of the proposed model. In addition, the Hadoop framework has over 190 configuration parameters and some of them have significant effects on the performance of a Hadoop job. Manually setting the optimum values for these parameters is a challenging task and also a time consuming process. This thesis presents optimization works that enhances the performance of Hadoop by automatically tuning its parameter values. It employs Gene Expression Programming (GEP) technique to build an objective function that represents the performance of a job and the correlation among the configuration parameters. For the purpose of optimization, Particle Swarm Optimization (PSO) is employed to find automatically an optimal or a near optimal configuration settings. The performance of the proposed work is intensively evaluated on a Hadoop cluster and the experimental results show that the proposed work enhances the performance of Hadoop significantly compared with the default settings.

Master of Science / Department of Electrical and Computer Engineering / Noel N. Schulz / Wind energy is becoming one of the most widely implemented forms of renewable energy worldwide. Traditionally, wind has been considered a non-dispatchable source of energy due to the uncertainty of wind speed and hence the variable availability of wind power. Advances in technology allow the consideration of the impact of distributed wind turbines and farms on distribution systems. It is possible to combine the clean energy attributes of wind with the quickly dispatchable nature of a storage facility in order to provide the maximum amount of locally available power economically to the loads present on the distribution feeder. However, a monitoring and control system needs to be provided that is capable of detecting the changes associated with the distribution feeder load and also the variable generation output from the wind farms. This task can be accomplished using a Phasor Measurement Unit (PMU) which has very high sampling rates and hence can measure very rapid and dynamic changes in power levels associated with distribution feeder load and wind generation. The data which is obtained from these PMUs can be used to calculate the amount of distributed generation and storage that can be dispatched locally at the distribution feeder, thus resulting in a reduction in the peak load levels associated with the distribution feeder as seen by the substation monitoring system. Simulations will work to balance load requirements, wind generation output, and distributed storage providing a stable system utilizing maximum renewable resources. The standard IEEE 37-node distribution test feeder is used in the study. Probabilistic models are implemented for distribution feeder load, and the models are analyzed through simulations. Four different combinations of charging and discharging methods have been investigated. Two analytically different algorithms have been used for wind and battery dispatch, one based on forecasted load information and the other based on historical measurements obtained from PMUs. The strategies being investigated can also be used to implement other important applications such as distribution system state estimation, protection and instability prediction.

Fault location reveals the exact information needed for utility crews to timely and promptly perform maintenance and system restoration. Therefore, accurate fault location is a key function in reducing outage time and enhancing power system reliability. Modern power systems are witnessing a trend of integrating more distributed generations (DG) into the grid. DG power outputs may be intermittent and can no longer be treated as constants in fault location method development. DG modeling is also difficult for fault location purpose. Moreover, most existing fault location methods are not applicable to simultaneous faults. To solve the challenges, this dissertation proposes three impedance-based fault location algorithms to pinpoint simultaneous faults for power transmission systems and distribution systems with high penetration of DGs. The proposed fault location algorithms utilize the voltage and/or current phasors that are captured by phasor measurement units. Bus impedance matrix technique is harnessed to establish the relationship between the measurements and unknown simultaneous fault locations. The distinct features of the proposed algorithms are that no fault types and fault resistances are needed to determine the fault locations. In particular, Type I and Type III algorithms do not need the information of source impedances and prefault measurements to locate the faults. Moreover, the effects of shunt capacitance are fully considered to improve fault location accuracy. The proposed algorithms for distribution systems are validated by evaluation studies using Matlab and Simulink SimPowerSystems on a 21 bus distribution system and the modified IEEE 34 node test system. Type II fault location algorithm for transmission systems is applicable to untransposed lines and is validated by simulation studies using EMTP on a 27 bus transmission system. Fault area identification method is proposed to reduce the number of line segments to be examined for fault location. In addition, an optimal fault location method that can identify possible bad measurement is proposed for enhanced fault location estimate. Evaluation studies show that the optimal fault location method is accurate and effective. The proposed algorithms can be integrated into the existing energy management system for enhanced fault management capability for power systems.

The thesis is devoted to the development of new algorithms for estimation of system frequency, power system phasors and transmission line fault location in the context of power system protection and control. A z-transform signal model combined with a nonlinear post-filtering scheme to estimate the operating frequency in a power system is first developed in the thesis. The signal model parameters are identified by an optimisation method in which the error between the model output and the actual signal that represents a voltage or current in the power system is minimised. The form and the structure of the signal model do not require iterations in the optimisation process for parameter identification. The system operating frequency is directly evaluated from the model parameters. Effects of noise and any frequency components other than the operating or supply-frequency on the accuracy are countered very effectively by applying a median post-filtering on the time series representing the frequency estimates derived from the model. Extensive simulation studies and comparisons with previously-published frequency estimation techniques confirm the high performance of the method developed in the thesis in terms of accuracy and time delay. With respect to power system phasor estimation, a method is developed based on waveform interpolation in the discrete time-domain to counter the spectral leakage errors arising in forming, by discrete Fourier transform (DFT), the supply frequency phasors representing power system voltages and currents when there are system frequency deviations from the nominal value. The interpolation scheme allows DFT evaluation to be performed with a time window length which is exactly equal to the fundamental period of the voltage or current waveform. Comparative studies presented in the thesis confirm the improvements achieved by the method proposed over other previouslypublished techniques in terms of accuracy and computing time. With the availability of accurate operating frequency and phasor estimates, an optimal fault location method based on multi-conductor distributedparameter line model is developed. The method is a general one which is applicable to any transmission line configurations, including multi-terminal lines. The fault location method is based on the minimisation of an objective function in which the fault distance is a variable. The objective function is formed from combining the phase-variable distributed-parameter equations of individual line sections from the fault point to the line terminals. The multivariable minimisation leads to high accuracy and robustness of the fault location algorithm in which any voltage/current measurement errors, including sampling time synchronisation errors, are represented in the estimation procedure as variables in addition to the fault distance. Extensive simulation studies are performed to verify that the method developed is highly accurate and robust. The thesis is supported by two international publications of which the candidate is a joint author.

The strain on modern electrical power systems has led to an ever-increasing utilization of new information and communication technologies (ICT) to improve their efficiency and reliability. Wide area monitoring and control (WAMC) systems offer many opportunities to improve the real-time situational awareness in the power system. These systems are essen-tially SCADA systems but with continuous streaming of measurement data from the power system. The quality of WAMC systems and the applications running on top of them are heavily, but not exclusively, dependent on the underlying non-functional quality of the ICT systems. From an ICT perspective, the real-time nature of WAMC systems makes them susceptible to variations in the quality of the supporting ICT systems. The non-functional qualities studied as part of this research are performance, interoperability and cyber security. To analyze the performance of WAMC ICT systems, WAMC applications were identified, and their requirements were elicited. Furthermore, simulation models capturing typical utility communication infrastructure architectures were implemented. The simulation studies were carried out to identify and characterize the latency in these systems and its impact on data quality in terms of the data loss. While performance is a major and desirable quality, other non-functional qualities such as interoperability and cyber security have a significant impact on the usefulness of the sys-tem. To analyze these non-functional qualities, an enterprise architecture (EA) based framework for the modeling and analysis of interoperability and cyber security, specialized for WAMC systems, is proposed. The framework also captures the impact of cyber security on the interoperability of WAMC systems. Finally, a prototype WAMC system was imple-mented to allow the validation of the proposed EA based framework. The prototype is based on existing and adopted open-source frameworks and libraries. The research described in this thesis makes several contributions. The work is a systematic approach for the analysis of the non-functional quality of WAMC ICT systems as a basis for establishing the suitability of ICT system architectures to support WAMC applications. This analysis is accomplished by first analyzing the impact of communication architectures for WAMC systems on the latency. Second, the impact of these latencies on the data quali-ty, specifically data currency (end to end delay of the phasor measurements) and data in-completeness (i.e., the percentage of phasor measurements lost in the communication), is analyzed. The research also provides a framework for interoperability and cyber security analysis based on a probabilistic Monte Carlo enterprise architecture method. Additionally, the framework captures the possible impact of cyber security on the interoperability of WAMC data flows. A final result of the research is a test bed where WAMC applications can be deployed and ICT architectures tested in a controlled but realistic environment. / <p>QC 20130218</p>

Power systems are protected by numerical relays that detect and isolate faults that may occur on power systems. The correct operation of the relay is very important to maintain the security of the power system. <p>Numerical relays that use voltage measurements from the power system provided by coupling capacitor voltage transformers (CCVT) have sometimes difficulty in correctly identifying a fault in the protected area. The fundamental frequency voltage phasor resulting from these CCVT measurements may result in a deviation from the true value and therefore may locate this phasor temporarily in the incorrect operating region. This phasor deviation is due to the CCVT behavior and the CCVT introduces spurious decaying and oscillating transient signal components on top of the original voltage received from the power system in response to sudden voltage changes produced during faults. Most of the existing methods for estimating the voltage phasor do not take advantage of the knowledge of the CCVT behavior that can be obtained from its design parameters.<p>A new least squares error method for phasor estimation is presented in this thesis, which improves the accuracy and speed of convergence of the phasors obtained, using the knowledge of the CCVT behavior. The characteristics of the transient signal components introduced by the CCVT, such as frequencies and time constants of decay, are included in the description of the curve to be fitted, which is required in a least squares fitting technique. Parameters such as window size and sampling rate for optimum results are discussed.<p>The method proposed is evaluated using typical power systems, with results that can be compared to the response if an ideal potential transformer (PT) were used instead of a CCVT. The limitations of this method are found in some specific power system scenarios, where the natural frequencies of the power system are close to that of the CCVT, but with longer time constants. The accuracy with which the CCVT parameters are known is also assessed, with results that show little impact compared to the improvements achievable.

Power systems are protected by numerical relays that detect and isolate faults that may occur on power systems. The correct operation of the relay is very important to maintain the security of the power system. <p>Numerical relays that use voltage measurements from the power system provided by coupling capacitor voltage transformers (CCVT) have sometimes difficulty in correctly identifying a fault in the protected area. The fundamental frequency voltage phasor resulting from these CCVT measurements may result in a deviation from the true value and therefore may locate this phasor temporarily in the incorrect operating region. This phasor deviation is due to the CCVT behavior and the CCVT introduces spurious decaying and oscillating transient signal components on top of the original voltage received from the power system in response to sudden voltage changes produced during faults. Most of the existing methods for estimating the voltage phasor do not take advantage of the knowledge of the CCVT behavior that can be obtained from its design parameters.<p>A new least squares error method for phasor estimation is presented in this thesis, which improves the accuracy and speed of convergence of the phasors obtained, using the knowledge of the CCVT behavior. The characteristics of the transient signal components introduced by the CCVT, such as frequencies and time constants of decay, are included in the description of the curve to be fitted, which is required in a least squares fitting technique. Parameters such as window size and sampling rate for optimum results are discussed.<p>The method proposed is evaluated using typical power systems, with results that can be compared to the response if an ideal potential transformer (PT) were used instead of a CCVT. The limitations of this method are found in some specific power system scenarios, where the natural frequencies of the power system are close to that of the CCVT, but with longer time constants. The accuracy with which the CCVT parameters are known is also assessed, with results that show little impact compared to the improvements achievable.

Taipower Company has already completed the installation of the Outage Management System (OMS) in all service districts. The attributes of all distribution equipments and customers have been included in the computerized mapping system. However, the phasing attributes of distribution transformers are not very accurate in the database because they are very difficult to be identified for the distribution systems. The phase information of transformers in the OMS database is often inconsistent with the actual service phase, which deteriorates the performance of distribution system analysis, planning, and operation of Taipower distribution systems. The objective of this thesis is to develop an innovative Phasor Measurement Unit (PMU) to support the phasing identification of distribution transformers in a very effective way. The proposed PMU is used to measure the low voltage signal at the secondary side of transformers to prevent the survey personnel from safety problem. With the measured phases information of distribution transformers stored in the embedded system, the attributes of transformer phases in OMS can be updated to improve the accuracy of database. For the underground distribution systems, it is very difficult to receive the 1PPS signal of GPS system for timing synchronous to support the proposed transformer phasing measurement because all transformers are located at the building basement. This thesis proposes a timing synchronous module by using the Temperature Compensated Crystal Oscillator, TCXO to maintain the timing accuracy with high precision. Before executing the phasing measurement, this module is calibrated using the GPS 1PPS signal with fuzzy control calibration algorithm. It is found that the proposed PMU module can maintain the timing synchronous with 6˚, during two hours time period which will support the transformer phasing measurement by providing the reference timing synchronous even without the GPS 1PPS signal.