An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

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

Development and application of synchronized wide-area power grid measurement

Phasor measurement units (PMUs) provide an innovative technology for real-time monitoring of the operational state of entire power systems and significantly improve power grid dynamic observability. This dissertation focuses on development and application of synchronized power grid measurements. The contributions of this dissertation are as followed:First, a novel method for successive approximation register analog to digital converter control in PMUs is developed to compensate for the sampling time error caused by the division remainder between the desirable sampling rate and the oscillator frequency. A variable sampling interval control method is presented by interlacing two integers under a proposed criterion. The frequency of the onboard oscillator is monitored in using the PPS from GPS.Second, the prevalence of GPS signal loss (GSL) on PMUs is first investigated using real PMU data. The correlation between GSL and time, spatial location, solar activity are explored via comprehensive statistical analysis. Furthermore, the impact of GSL on phasor measurement accuracy has been studied via experiments. Several potential solutions to mitigate the impact of GSL on PMUs are discussed and compared.Third, PMU integrated the novel sensors are presented. First, two innovative designs for non-contact PMUs presented. Compared with conventional synchrophasors, non-contact PMUs are more flexible and have lower costs. Moreover, to address nonlinear issues in conventional CT and PT, an optical sensor is used for signal acquisition in PMU. This is the first time the utilization of an optical sensor in PMUs has ever been reported.Fourth, the development of power grid phasor measurement function on an Android based mobile device is developed. The proposed device has the advantages of flexibility, easy installation, lower cost, data visualization and built-in communication channels, compared with conventional PMUs.Fifth, an identification method combining a wavelet-based signature extraction and artificial neural network based machine learning, is presented to identify the location of unsourced measurements. Experiments at multiple geographic scales are performed to validate the effectiveness of the proposed method using ambient frequency measurements. Identification accuracy is presented and the factors that affect identification performance are discussed

Security Analysis of Phasor Measurement Units in Smart Grid Communication Infrastructures

Phasor Measurement Units (PMUs), or synchrophasors, are rapidly being deployed in the smart grid with the goal of measuring phasor quantities concurrently from wide area distribution substations. By utilizing GPS receivers, PMUs can take a wide area snapshot of power systems. Thus, the possibility of blackouts in the smart grid, the next generation power grid, will be reduced. As the main enabler of Wide Area Measurement Systems (WAMS), PMUs transmit measured values to Phasor Data Concentrators (PDCs) by the synchrophasor standard IEEE C37.118. IEC 61850 and IEC 62351 are the communication protocols for the substation automation system and the security standard for the communication protocol of IEC 61850, respectively. According to the aforementioned communication and security protocols, as well as the implementation constraints of different platforms, HMAC-SHA1 was suggested by the TC 57 WG group in October 2009. The hash-based Message Authentication Code (MAC) is an algorithm for verifying both message integrity and authentication by using an iterative hash function and a supplied secret key. There are a variety of security attacks on the PMU communications infrastructure. Timing Side Channel Attack (SCA) is one of these possible attacks. In this thesis, timing side channel vulnerability against execution time of the HMAC-SHA1 authentication algorithm is studied. Both linear and negative binomial regression are used to model some security features of the stored key, e.g., its length and Hamming weight. The goal is to reveal secret-related information based on leakage models. The results would mitigate the cryptanalysis process of an attacker. Adviser: Yi Qia

Wide-Area Synchrophasor Data Server System and Data Analytics Platform

As synchrophasor data start to play a significant role in power system operation and dynamic study, data processing and data analysis capability are critical to Wide-area measurement systems (WAMS). The Frequency Monitoring Network (FNET/GridEye) is a WAMS network that collects data from hundreds of Frequency Disturbance Recorders (FDRs) at the distribution level. The previous FNET/GridEye data center is limited by its data storage capability and computation power. Targeting scalability, extensibility, concurrency and robustness, a distributed data analytics platform is proposed to process large volume, high velocity dataset. A variety of real-time and non-real-time synchrophasor data analytics applications are hosted by this platform. The computation load is shared with balance by multiple nodes of the analytics cluster, and big data analytics tools such as Apache Spark are adopted to manage large volume data and to boost the data processing speed. Multiple power system disturbance detection and analysis applications are redesigned to take advantage of this platform. Data quality and data security are monitored in real-time. Future data analytics applications can be easily developed and plugged into the system with simple configuration

Phase Measurement Units based FACT’s Devices for the Improvement of Power Systems Networks Controllability

This paper describes the importance of FACTS devices; it presents the outcome of the study of its reflectance on the performance of power system networks. It seeks to increase and guarantee the fact and accuracy of response systems under disturbance conditions when the phase measurement units are introduced as Real-Time Measurement (RTM) stations. This paper also describes the importance of FACTS devices. The combination of FACTS devices and PMUs is presented to increase the controllability performance of power systems. This paper demonstrates how PMUs measure voltage, current and their angles. It provides, through a communication link, a Phase Angle Data Concentrator (PDC) to make an appropriate decision to correct the power system state using the FACTS device (TCSC). We utilized the Graph-Theoretic Algorithm to optimize the number and location of PMUs. The technique proposed was tested on the Iraqi National Super Grid’s 24bus network, Diyala City’s regional 10bus network and the 14bus IEEE standard test system. The MATLAB/PSAT package was utilized for the simulation of results. It is evident that our proposed algorithm and technique achieved the purpose of this paper as confirmed by the level of accuracy of the results obtained from most of the cases tested