A Compressive Sensing Based Method for Harmonic State Estimation

Power quality monitoring has become a vital need in modern power systems owing to the need for agile operation and troubleshooting scheme. On the other hand, the nature of load in modern power system is changing in many ways. Digital loads, which are mostly relied on power electronic equipment, may distort the quality of power flowing through the network. Moreover, one of the most critical objectives of smart grids is to improve quality of services delivered to customers, alongside with security, reliability and efficiency. To this end, a novel method based on compressive sensing is proposed in this paper to detect the source and the magnitude of the harmonics. The method takes advantages of compressive sensing theory in such a way that a real-time monitoring of harmonic distortion is obtained with a limited number of measurements. The efficacy of the method is checked by means of various simulations on IEEE 118 bus test system. The results show the capabilities of the method in both noisy and noise-free conditions

Gaussian mixture modeling for detecting integrity attacks in smart grids

The thematics focusing on inserting intelligence in cyber-physical critical infrastructures (CI) have been receiving a lot of attention in the recent years. This paper presents a methodology able to differentiate between the normal state of a system composed of interdependent infrastructures and states that appear to be normal but the system (or parts of it) has been compromised. The system under attack seems to operate properly since the associated measurements are simply a variation of the normal ones created by the attacker, and intended to mislead the operator while the consequences may be of catastrophic nature. Here, we propose a holistic modeling scheme based on Gaussian mixture models estimating the probability density function of the parameters coming from linear time invariant (LTI) models. LTI models are approximating the relationships between the datastreams coming from the CI. The experimental platform includes a power grid simulator of the IEEE 30 bus model controlled by a cyber network platform. Subsequently, we implemented a wide range of integrity attacks (replay, ramp, pulse, scaling, and random) with different intensity levels. An extensive experimental campaign was designed and we report satisfying detection results

Synchronized measurement data conditioning and real-time applications

Phasor measurement units (PMU), measuring voltage and current phasor with synchronized timestamps, is the fundamental component in wide-area monitoring systems (WAMS) and reveals complex dynamic behaviors of large power systems. The synchronized measurements collected from power grid may degrade due to many factors and impacts of the distorted synchronized measurement data are significant to WAMS. This dissertation focus on developing and improving applications with distorted synchronized measurements from power grid. The contributions of this dissertation are summarized below. In Chapter 2, synchronized frequency measurements of 13 power grids over the world, including both mainland and island systems, are retrieved from Frequency Monitoring Network (FNET/GridEye) and the statistical analysis of the typical power grids are presented. The probability functions of the power grid frequency based on the measurements are calculated and categorized. Developments of generation trip/load shedding and line outage events detection and localization based on high-density PMU measurements are investigated in Chapters 3 and 4 respectively. Four different types of abnormal synchronized measurements are identified from the PMU measurements of a power grid. The impacts of the abnormal synchronized measurements on generation trip/load shedding events detection and localization are evaluated. A line outage localization method based on power flow measurements is proposed to improve the accuracy of line outage events location estimation. A deep learning model is developed to detect abnormal synchronized measurements in Chapter 5. The performance of the model is evaluated with abnormal synchronized measurements from a power grid under normal operation status. Some types of abnormal synchronized measurements in the testing cases are recently observed and reported. An extensive study of hyper-parameters in the model is conducted and evaluation metrics of the model performance are presented. A non-contact synchronized measurements study using electric field strength is investigated in Chapter 6. The theoretical foundation and equation derivations are presented. The calculation process for a single circuit AC transmission line and a double circuit AC transmission line are derived. The derived method is implemented with Matlab and tested in simulation cases

Analysis of Line Outage Detection in Nigeria 330kV Transmission Lines using Phasor Measurement Units

In this work, an analysis of line outage detection in Nigeria 330kV transmission lines using Phasor Measurement Units was presented. This requires collection and analysis of the data obtained from Transmission Company of Nigeria with the aid of PSAT 2.10.1 / MATLAB SIMULINK using Newton-Raphson power flow algorithm and also to determine the effectiveness of PMU when introduced in our power system network. 12 buses and 3 Generators system were considered for the studied. This was achieved by collecting relevant transmission parameters for 330kV line and was simulated on PSAT 2.10.1 and MATLAB 2015a using Newton-Raphson power flow algorithm. The work involved an offline and online analysis. For the offline analysis the admittance / impedance matrix for Y-bus and bus voltage for pre-outage was obtained via the power flow analysis and change in impedance for the lines were calculated. These values were further normalised in order to reduce the value to a row echelon form. Then for the online analysis; the change in phase angle from the Phasor Measurement Unit (PMU) online simulation for pre-outage and also post-outage was calculated and a normalised column matrix was gotten. Finally, the effectiveness of the line outage detection was graphically represented using MATLAB software to plot the values of the normalised values of the offline and online analysis; i.e., by comparing the normalised form of the offline and online values. These results clearly show that PMUs gives an accurate monitoring and total observability when introduced in Nigeria power system