MODELING, CHARACTERISATION AND DATA EXCHANGE SECURITY OF PMU

Abstract

The reliability and security of operational data sets are crucial considerations when evaluating a Phasor Measurement Unit (PMU). It is an intelligent device that provides real-time monitoring and measurements of electrical parameters in power systems and is an essential part of managing and operating SCADA systems and smart grids. Additionally, it can be used to detect micro-grid islanding, islanding, and isolation. In a broad area power system network, it is necessary to gather online real-time data referencing a synchronous frame without interruption. This requires PMU to be reliable and required accurate values of the parameters. As a result, the reliability and sensitivity of PMUs have been evaluated and calculated. Additionally, based on the uncertainties in each of its many modules, fuzzy logic analysis is performed to assess the dependability of the phasor measurement unit (PMU). This is constructed with a logic gate representation, and the Markov reliability model is implemented. The theory and configuration of PMU for synchronization detection are also examined with regard to compilation and operation. PMU is an intelligent, integrated system made up five modules and two sub modules such as module-1(Data Acquisition module), module-2(Global Positioning System), module-3(phasor processor) module-4(communication module), and module-5(Power Supply). Further Module-1 comprises of sub-modules viz. transducers, anti- alias filter, and analog to digital converter (ADC), Module-2 comprises of sub-modules GPS receiver, crystal Oscillator/ switch, Module-3 comprises of sub- modules hardware and software of Central Processing Unit (CPU), Module-4 has MODEM for communication and Module-5 is power supply. Each unit has a certain function, and depending on how frequently they fail and need repairs, they are available. The PMU is rendered useless and ineffective due to fault in any unit. Five PMU modules can, therefore be referred to as "series modules." Data is collected and transferred from the power system (the Data Acquisition module or system) to the CPU through the transducer, filter, and ADC. The ADC's start and stop functions are controlled by a GPS. The transducers gather information from the CT and PT as well as about the status of the circuit breaker, location of isolator, and other variables. The CPU analyzes the output of the ADC and timestamps it with the current time prior to transmission, while alias filters reduce data- and information-introduced noise. The time stamping of data is controlled by the GPS signal. If the GPS receiver malfunctions, the crystal oscillator will continue to run until the 50 Hz error does not increase by vii more than 31 microseconds per hour. For the working of all modules power supply unit is needed. A mathematical model of the PMU and its modules is constructed using Markov probability theory. The failure and repair rate of all sub-modules are calculated and the resulted rate is taken as the failure and repair rate of their respective modules. This is done in order to streamline the calculations. From the analysis of the result it has been observed that GPS module is the most critical module. Digital data is time-stamped and synchronized by the satellite-based Global Positioning System (GPS). In this study using time diagram of the failure rate and repair rate is also provided, along with the encountering frequency of each module. Through the use of a random number generator, the stipulated failure and repair rates, and simulation studies, the dependability of the PMU was evaluated. The proposed model is simulated in Mat lab version 7. This study suggests a novel and creative method of assessing the PMU performance indicator. An interval type-2 fuzzy logic system (IT2FS) with several cut sets is used to determine RAM. With this, uncertainty is transformed into a set of prospective data points. When assessing the PMU's overall performance, it also takes into account the GPS receiver's failure and a subpar switch. Performance graphs are made to give a visual picture of the risk and possibility for design improvement associated with the PMU. In order to improve the quality of PMU modules, it is crucial to detect design defects. The failure rate of the PMU module has not been sufficiently described by the manufacturers. There is a lack of clarity regarding the percentage of PMU modules that fail during operation. The ever-changing external factors contribute to the dynamic nature of the information processing. Firstly the fault tree model of PMU, which is a representation of system failure, is developed. To take into account the redundancy factor Petri Net is implemented using AND/OR transformation rules. The reachability graph is also developed. Fuzzy Petri Net (FPN) is developed which is an extension of Petri Net that permits the modeling of system with uncertain or imperfect data. FPN provide dynamic as well as redundant feature to the model. This FPN has been utilized to assess the dynamic reliability of a PMU when repair or failure rate are uncertain. With FPN developed the sprouting tree algorithm (STA) can be used to analysis it. This generates a Petri Net’s state space representation. FPN based STA is a hybrid method that viii incorporates the benefits of FPN and STA to solve optimisation problems involving uncertain or imprecise data. Data from PMUs must be used for monitoring and controlling is widely used power systems. A PMU is a smart device that keeps track of information about the power system, including the flow of energy between utilities and grids. The communication protocol used for the Data Acquisition module, IEEEC37.118 is centralized and unencrypted. In order to address the power exchange disparity, the role of Blockchain technology in the PMU is identified . With the help of a variety of MYSQL database management systems located in the AWS cloud, the thesis presents a novel approach for creating a distributed and scalable data model based on Blockchains. The method manages the heterogeneity within the database of different nodes contributing to the information flow using PMU data translated into a JSON data representation. The model's use of password and Blockchain as encryption techniques makes it cyber-secure. The coding language used is python. The research work presented in the thesis is expected to provide good exposure to modeling, characterization and data security of PMU.