Data-driven Models to Anticipate Critical Voltage Events in Power Systems

This paper explores the effectiveness of data-driven models to predict voltage excursion events in power systems using simple categorical labels. By treating the prediction as a categorical classification task, the workflow is characterized by a low computational and data burden. A proof-of-concept case study on a real portion of the Italian 150 kV sub-transmission network, which hosts a significant amount of wind power generation, demonstrates the general validity of the proposal and offers insight into the strengths and weaknesses of several widely utilized prediction models for this application.Comment: In proceedings of the 11th Bulk Power Systems Dynamics and Control Symposium (IREP 2022), July 25-30, 2022, Banff, Canad

Delay analysis of two-way synchronization scheme for phasor measurement unit based digital smart grid applications

The power system has been experiencing adaptation of new problem solving technologies which have intelligent capabilities to arrive better solutions. Smart Grid is the best leading technology that presents better integration platforms of synchronous power generation system (Solar energy, hydro power plant, thermal plant, coal based power plant as well as fuel based power generation systems. Likewise, other power system components that require efficient techniques and methods for solving day-to-day problems have also being applied to the Smart Grid. Thus, the variables and the parameters of electrical and mechanical occurrences are needed to monitor, detect faults, measures the accuracies that actions timely to an interconnected grid system. In WAM-based smart grid system, the occurrences are monitored using frequency parameters, rotational speed as well as phasor angles of voltage. This parameter ensures the fault detection, monitoring, measurement and control of the interconnected digital smart grid applications. The recent development of IEEE C37.118 based frameworks in Phasor Measurement Unit (PMU) based Wide Area Measurement (WAM) systems of smart grid. However due to extensive level of delay and error the grid application became unstable in measuring, controlling and monitoring. Therefore, this paper has designed the two-way synchronization communication framework for smart grid application. The mat lab based simulation evaluation has made to measure the delay occurrences in smart grid applications. The designed scheme is a higher-level communication scheme is to be utilized, and validated to come up with the required solution of reconciling between input values and output values from the available synchronous applications

Current and voltage sensors for use in Smart Grid applications

Klasična mreža zastarjela je i nije dovoljno razvijena kako bi zadovoljila potrebe modernih potrošača. Cilj ovog rada je prikazati pregled i primjenu strujnih i naponskih senzora te koristi njihove implementacije. Suvremeni način distribucije donosi nove tehnologije u elektroenergetski sustav. Razvojem senzora i aplikacija, potrošačima i proizvođačima omogućuje se pametna distribucija resursa u svrhu pouzdanije i stabilnije mreže. Prikazane su prednosti pametne mreže, njene komponente i pregled senzora, te načini mjerenja parametara i komunikacija unutar mreže.Classic power grid is oudated and insufficiently developed in order to meet requirements of modern consumers. Purpose of this paper is to show a review and application of current and voltage sensors as well as the benefits of their implementations. Modern way of distribution brings new technologies into the power system. With development of sensors and applications, consumers and manufacturers have ability to wisely manipulate their resources in purpose of more reliable and stable grid. Here are shown benefits of smart grid, it's components and sensor overview as well as the ways of measuring the parameters and communication within the network

Protocolli Power Line Communications per applicazioni Smart Grid

In questa tesi verranno analizzati alcuni protocolli a banda larga progettati per offrire, mediante l'utilizzo di tecnologie Power Line Communications (PLC), servizi necessari per l'implementazione di una rete Smart Grid. Smart Grid si riferisce ad un progetto di sviluppo della rete elettrica odierna, che integri sistemi di raccolta dati, monitoraggio e controllo. Varie tecnologie sono state proposte per fornire il supporto informativo necessario a Smart Grid per operare, tecnologie che dovevano soddisfare principalmente al requisito di essere economicamente vantaggiose, oltrech\'e affidabili. Tra le varie tecnologie due si sono imposte come le maggiormente promettenti: la tecnologia wireless e PLC. Entrambe offrono l'infrastuttura richiesta da Smart Grid, ciascuna con i propri pregi e difetti. Questa tesi analizza la tecnologia PLC e in particolare il protocollo HomePlug Green PHY e la direttiva ITU-T G.h

Phasor measurement unit (PMU) placement optimisation in power transmission network based on hybrid approach

The Phasor Measurement Unit (PMU) is a device that is employed to detect the voltage and current waveform that is synchronised with a clocking signal obtained continuously from the global positioning system (GPS). Integrating with the GPS receiver, the base station is able to receive the synchronous data from each PMU in real time. This thesis presents novel optimal placement approaches of PMU for applications such as state estimation and fault detection. In this thesis, the PMU placement is realised based on two hybrid algorithms namely Approximation Algorithm and Global Optimization Algorithm. The proposed algorithms will ensure optimum PMU placement with full network observability under different contingency conditions. The IEEE 14, 24, 30, 57 and the New England 39 standard test systems will be used to exam the proposed algorithm adequately and the result will be compared to existing methods. In this thesis, we demonstrated that the proposed methods are very effective in determining the minimum number of PMU and the results are comparable to the best methods presented in the past literature. In addition, the comparison between the proposed methods to the existing methods show that the proposed hybrid approaches achieve higher System Observability Redundancy Index (SORI) which will in turn improve the reliability and stability of power transmission

False data injection attack detection in smart grid

Smart grid is a distributed and autonomous energy delivery infrastructure that constantly monitors the operational state of its overall network using smart techniques and state estimation. State estimation is a powerful technique that is used to determine the overall operational state of the system based on a limited set of measurements collected through metering systems. Cyber-attacks pose serious risks to a smart grid state estimation that can cause disruptions and power outages resulting in huge economical losses and are therefore a big concern to a reliable national grid operation. False data injection attacks (FDIAs), engineered on the basis of the knowledge of the network configuration, are difficult to detect using the traditional data detection mechanisms. These detection schemes have been found vulnerable and failed to detect these FDIAs. FDIAs specifically target the state data and can manipulate the state measurements in such a way that these false measurements appear real to the main control systems. This research work explores the possibility of FDIA detection using state estimation in a distributed and partitioned smart grid. In order to detect FDIAs we use measurements for residual-based testing which creates an objective function; and the probability of erroneous data is determined from this residual test. In this test, a preset threshold is determined based on the prior history of the state data. FDIA cases are simulated within a smart grid considering that the Chi-square detection state estimator fails in identifying such attacks. We compute the objective function using the standard weighted least problem and then test the objective function against the value in the Chi-square table. The gain matrix and the Jacobian matrix are computed. The state variables are computed in the form of a voltage magnitude. The state variables are computed after the inception of an attack to assess these state magnitude results. Different sizes of partitioning are used to improve the overall sensitivity of the Chi-square results. Our additional estimator is based on a Kalman estimation that consists of the state prediction and state correction steps. In the first step, it obtains the state and matrix covariance prediction, and in the second step, it calculates the Kalman gain and the state and matrix covariance update steps. The set of points is created for the state vector x at a time instant t. The initial vector and covariance matrix are based on a priori knowledge of the historical estimates. A set of sigma points is estimated by the state update function. Sigma points refer to the minimal set of sampling points that are selected and transformed using nonlinear function, and the new mean and the covariance are formed out of these transformed points. The idea behind this is that it is easier to compute a Gaussian distribution than an arbitrary nonlinear function. The filter gain, the mean and the covariance are used to estimate the next state. Our simulation results show that the combination of Kalman estimation and distributed state estimation improves the overall stability index and vulnerability assessment score of the smart grid. We built a stability index table for a smart grid based on the state estimates value after the inception of an FDIA. The vulnerability assessment score of the smart grid is based on common vulnerability scoring system (CVSS) and state estimates under the influence of an FDIA. The simulations are conducted in the MATPOWER program and different electrical bus systems such as IEEE 14, 30, 39, 118 and 300 are tested. All the contributions have been published in reputable journals and conferences.Doctor of Philosoph