Impact of Geomagnetically Induced Currents on Power Transformers

This thesis deals with the impact of Geomagnetically Induced Current (GIC) on power transformers in electrical power systems. A simulator to calculate the flows of GIC in an electrical power network, based on an assumed or measured induced geoelectric potential is proposed. This simulator includes all needed mapping techniques to handle a system that cover a large geographical area. A correlation between GIC and the reactive power absorbed in the core of the saturated transformer is proposed. That correlation is used to estimate GIC in a transformer utilizing existing reactive power measuring infrastructure within the electrical grid without the need for dedicated measurement equipment. This technique is validated by simulations with electromagnetic transients software, laboratory work and through data recorded during a GIC event on the Hydro One network. The slope correlating reactive power absorption to GIC from an electromagnetic transient model of the transformer may be used to predict GIC levels in the actual transformers. The application of the technique correlating GIC with reactive power absorption is examined on a segment of a real 500 kV power transmission system. This technique allows GIC to be taken into account during load flow studies. Additionally, some benefits of increased visibility of GIC in the system are shown. A method to determine the frequency and magnitude of the harmonic currents generated by a saturated transformer is also proposed. It is expected that studies conducted in this thesis will be of value to utilities like Hydro One in planning mitigation measures against GICs

Hybrid Smart Transformer for Enhanced Power System Protection Against DC With Advanced Grid Support

The traditional grid is rapidly transforming into smart substations and grid assets incorporating advanced control equipment with enhanced functionalities and rapid self-healing features. The most important and strategic equipment in the substation is the transformer and is expected to perform a variety of functions beyond mere voltage conversion and isolation. While the concept of smart solid-state transformers (SSTs) is being widely recognized, their respective lifetime and reliability raise concerns, thus hampering the complete replacement of traditional transformers with SSTs. Under this scenario, introducing smart features in conventional transformers utilizing simple, cost-effective, and easy to install modules is a highly desired and logical solution. This dissertation is focused on the design and evaluation of a power electronics-based module integrated between the neutral of power transformers and substation ground. The proposed module transforms conventional transformers into hybrid smart transformers (HST). The HST enhances power system protection against DC flow in grid that could result from solar storms, high-elevation nuclear explosions, monopolar or ground return mode (GRM) operation of high-voltage direct current (HVDC) transmission and non-ideal switching in inverter-based resources (IBRs). The module also introduces a variety of advanced grid-support features in conventional transformers. These include voltage regulation, voltage and impedance balancing, harmonics isolation, power flow control and voltage ride through (VRT) capability for distributed energy resources (DERs) or grid connected IBRs. The dissertation also proposes and evaluates a hybrid bypass switch for HST module and associated transformer protection during high-voltage events at the module output, such as, ground faults, inrush currents, lightning and switching transients. The proposed strategy is evaluated on a scaled hardware prototype utilizing controller hardware-in-the-loop (C-HIL) and power hardware-in-the-loop (P-HIL) techniques. The dissertation also provides guidelines for field implementation and deployment of the proposed HST scheme. The device is proposed as an all-inclusive solution to multiple grid problems as it performs a variety of functions that are currently being performed through separate devices increasing efficiency and justifying its installation

Topology Control Analysis Mitigations for Geomagnetically Induced Currents

Geomagnetic disturbances (GMD) are caused by corona mass ejections (CMEs) from the sun. These solar CMEs cause changes in the earths magnetic field, which in turn produce non-uniform electric fields. These GMDs have the ability to disrupt the electric grid by causing quasi-dc geomagnetically induced currents (GICs) in the high voltage transmission grid. The 2015 National Space Weather Action Plan released by the White House called for protection, mitigation, response, and recovery from potential devastating effects of space weather for the reliability of electric power. GICs have the ability to severely disrupt the operations of our power system, including possible permanent damage to our critical assets, such as our high-voltage transformers, due to overheating and the loss of reactive power support in our transmission lines, which could lead to a voltage collapse and thus, a large-scale blackout. With an increase in interest of GICs on the transmission grid, it has become essential for engineers to determine possible protection devices, as well as mitigation and recovery schemes to lower the effect and possible damages of these GMDs. One specific area of interest is the mitigation of GICs by transmission control analysis (TCA). TCA is used on a daily basis to optimally dispatch the network topology along with generation resources, which has the ability to bypass significant congestion costs on the system and increase transfer capability. Research shows that implementing a specific TCA can also have the ability to reduce reactive power losses, which in turn can help prevent a voltage collapse and large-scale blackout.Grainger Center for Electric Machinery and ElectromechanicsOpe

Risk analysis of Geomagnetically Induced Current (GIC) in Power Systems

Solar storms are a phenomenon that has a wide array of adverse consequences on technological systems, power systems in particular. During severe solar storms a geomagnetically induced current (GIC) starts to flow through long conducting structures, such as power lines and pipelines. The probability of solar storms has a roughly linear relation with the sunspot activity level which varies in 11 years cycles and at the moment of writing this thesis we are approaching the maxima of solar cycle 24. This thesis is a risk analysis of GIC in power systems and describes the causes and sources of GIC, the consequences, both on component level and on system level, and the likelihood of occurrence. When GIC flows through a transformer it causes the core to saturate, which leads to (a) increased reactive power consumption, (b) high levels of harmonics in the power system and (c) localized heating of the transformer. Point a and b are confirmed through simulations. High harmonics levels can cause protective relays to sense false fault conditions and trip. On a system level this can lead to (a) loss of production (b) local blackouts or (c) widespread blackouts. Localized heating of transformers can lead to permanent damage and spare parts and replacement units are associated with having long lead times. Communication and control systems are also subject to GIC and other solar storm related interferences. The thesis also contains a discussion about GIC risk associated to gas pipelines. The likelihood of solar storms is discussed and a method for determining the exceedance probability of extreme values for solar storms such as a 100-year storm is presented. The exceedance probability of a 100- year storm during 2012-2014 is estimated to 4.7%. Possible risk treatment strategies and forecasting capabilities are also briefly discussed, in order to briefly illustrate possible risk management schemes. This report should facilitate risk evaluation and provide the information needed to calculate quantitative risk values with respect to solar storms and power systems. In order to fully understand the extent of the consequences of a 100-year storm further studies are needed in order to take the complexities of covariance and the interconnectedness of different components and systems into account

Energizing the Future! Texas Synthetic Grid Geomagnetic Disturbances Analysis

The electrical grid is constantly evolving and it is essential to modify existing designs to assure preparation and safety for new threats such as geomagnetic disturbances (GMDs). It is necessary to maximize the functionality of the grid by utilizing the synthetic model of the Texas Interconnect. PowerWorld (visual software) was used to simulate the electrical grid and design modifications were integrated to the synthetic grid in order to withstand geomagnetic disturbance electric fields. It is necessary to conduct North American Electric Reliability Corporation (NERC) assessments to find the maximum effective geomagnetically induced current value for the worst case geoelectric field orientation. By simulating the disturbances on the power grid for the GMDs, the results will provide distinct solutions to threatening scenarios. It is essential to conduct such studies to predict the behavior of the grid to various natural phenomena and gather data to energize the future to create a more sustainable world

Optimization Methods in Electric Power Systems: Global Solutions for Optimal Power Flow and Algorithms for Resilient Design under Geomagnetic Disturbances

An electric power system is a network of various components that generates and delivers power to end users. Since 1881, U.S. electric utilities have supplied power to billions of industrial, commercial, public, and residential customers continuously. Given the rapid growth of power utilities, power system optimization has evolved with developments in computing and optimization theory. In this dissertation, we focus on two optimization problems associated with power system planning: the AC optimal power flow (ACOPF) problem and the optimal transmission line switching (OTS) problem under geomagnetic disturbances (GMDs). The former problem is formulated as a nonlinear, non-convex network optimization problem, while the latter is the network design version of the ACOPF problem that allows topology reconfiguration and considers space weather-induced effects on power systems. Overall, the goal of this research includes: (1) developing computationally efficient approaches for the ACOPF problem in order to improve power dispatch efficiency and (2) identifying an optimal topology configuration to help ISO operate power systems reliably and efficiently under geomagnetic disturbances. Chapter 1 introduces the problems we are studying and motivates the proposed research. We present the ACOPF problem and the state-of-the-art solution methods developed in recent years. Next, we introduce geomagnetic disturbances and describe how they can impact electrical power systems. In Chapter 2, we revisit the polar power-voltage formulation of the ACOPF problem and focus on convex relaxation methods to develop lower bounds on the problem objective. Based on these approaches, we propose an adaptive, multivariate partitioning algorithm with bound tightening and heuristic branching strategies that progressively improves these relaxations and, given sufficient time, converges to the globally optimal solution. Computational results show that our methodology provides a computationally tractable approach to obtain tight relaxation bounds for hard ACOPF cases from the literature. In Chapter 3, we focus on the impact that extreme GMD events could potentially have on the ability of a power system to deliver power reliably. We develop a mixed-integer, nonlinear model which captures and mitigates GMD effects through line switching, generator dispatch, and load shedding. In addition, we present a heuristic algorithm that provides high-quality solutions quickly. Our work demonstrates that line switching is an effective way to mitigate GIC impacts. In Chapter 4, we extend the preliminary study presented in Chapter 3 and further consider the uncertain nature of GMD events. We propose a two-stage distributionally robust (DR) optimization model that captures geo-electric fields induced by uncertain GMDs. Additionally, we present a reformulation of a two-stage DRO that creates a decomposition framework for solving our problem. Computational results show that our DRO approach provides solutions that are robust to errors in GMD event predictions. Finally, in Chapter 5, we summarize the research contributions of our work and provide directions for future research

OPTIMAL MITIGATION OF GEOMAGNETICALLY INDUCED CURRENT EFFECTS IN POWER SYSTEMS CONSIDERING TRANSFORMER THERMAL LIMITS

An efficient energy transfer from the solar wind into the earth’s space environment causes temporary disturbance to the earth’s magnetosphere. Solar flares and coronal mass ejections (CME) of charged and magnetized particles can disturb the earth’s magnetic field and cause geomagnetic disturbance (GMD). GMDs are of particular concern as they give rise to geomagnetically induced currents (GIC) which have adverse effects on the national power grid and potentially damage transformers on the grid. GIC flowing along transmission lines and through the transformers in power systems can be attributed to problems ranging from overheating of power transformers, harmonic generation, and voltage collapse due to the half-cycle saturation of power transformers. To prevent the power system and its equipment from the adverse effects of GMD, blocking device (BD) can be placed to block the GIC flow in the transformers. However, BD placement is a complex problem, and the cost of BD is very high, so optimization techniques should be employed for BD placement to minimize the number and costs of BDs. Although there has been research on placing blocking devices and their optimal placement, none of them considers the hotspot temperature rise in transformers during GIC. Therefore, Voltage violation and rise in hotspot temperature of transformers are the main concerns in this thesis. This work presents two approaches for the optimal placement of blocking devices on the neutral of high voltage transformers to prevent the power system from the impacts of GIC caused by geomagnetic disturbance. The thesis focuses on the optimization problem based on overheating of power transformers due to GIC and maintaining the hotspot temperature of transformers within the limit, as well as maintaining the voltage profile of the power system. The problem is formulated by first calculating the GIC and increased reactive power demand of each transformer during the GIC flow, performing power flow analysis, checking if system voltage has been violated, calculating the transformers’ windings and metallic hotspot temperatures, checking if the limits are reached, and optimally placing BDs on selective transformers such that the hotspot temperature of transformers is within maximum limits, and the system voltage is recovered above minimum permissible voltage. The optimization is done using the Surrogate optimization and Genetic algorithm of the MATLAB optimization toolbox and made sure that the number of BDs is minimized. A comparative analysis is done from the results obtained from both of the methods. The findings of the thesis highlight the optimization approach for the placement of blocking devices that takes into account the hotspot temperature rise of transformer tie-plates and windings and a realistic criterion that includes the cost of the repair or replacement of transformers based on the hotspot temperature rise of transformers into the optimization approach. The thesis presents the selection criteria for the two optimization solvers, surrogate optimization and genetic algorithm, after researching and reviewing different solvers from the MATLAB optimization toolbox. The total cost of BD placement is reduced where the total load is reduced to some extent based on different levels of geoelectric field ($E$) to maintain the bus voltages above minimum permissible voltage, and the cost can be calculated based on the loss of load, and extra number of BDs can be avoided. The results obtained from surrogate optimization are proved to be effective and efficient as the total number of BDs resulting from surrogate optimization is less than the total number of BDs resulting from genetic algorithm. The nature of genetic algorithm is stochastic in nature, the result not converging to the global minimum, and the time taken by genetic algorithm for the program execution were major drawbacks. In contrast, the characteristics of surrogate algorithm, such as a result, proved to be converging, non-stochastic in nature, unlike genetic algorithm, and comparatively less time consuming than genetic algorithm proving surrogate optimization to be more reliable and efficient

OPTIMAL MITIGATION OF GEOMAGNETICALLY INDUCED CURRENT EFFECTS IN POWER SYSTEMS CONSIDERING TRANSFORMER THERMAL LIMITS

An efficient energy transfer from the solar wind into the earths space environment causes temporary disturbance to the earths magnetosphere. Solar flares and coronal mass ejections (CME) of charged and magnetized particles can disturb the earths magnetic field and cause geomagnetic disturbance (GMD). GMDs are of particular concern as they give rise to geomagnetically induced currents (GIC) which have adverse effects on the national power grid and potentially damage transformers on the grid. GIC flowing along transmission lines and through the transformers in power systems can be attributed to problems ranging from overheating of power transformers, harmonic generation, and voltage collapse due to the half-cycle saturation of power transformers. To prevent the power system and its equipment from the adverse effects of GMD, blocking device (BD) can be placed to block the GIC flow in the transformers. However, BD placement is a complex problem, and the cost of BD is very high, so optimization techniques should be employed for BD placement to minimize the number and costs of BDs. Although there has been research on placing blocking devices and their optimal placement, none of them considers the hotspot temperature rise in transformers during GIC. Therefore, Voltage violation and rise in hotspot temperature of transformers are the main concerns in this thesis. This work presents two approaches for the optimal placement of blocking devices on the neutral of high voltage transformers to prevent the power system from the impacts of GIC caused by geomagnetic disturbance. The thesis focuses on the optimization problem based on overheating of power transformers due to GIC and maintaining the hotspot temperature of transformers within the limit, as well as maintaining the voltage profile of the power system. The problem is formulated by first calculating the GIC and increased reactive power demand of each transformer during the GIC flow, performing power flow analysis, checking if system voltage has been violated, calculating the transformers windings and metallic hotspot temperatures, checking if the limits are reached, and optimally placing BDs on selective transformers such that the hotspot temperature of transformers is within maximum limits, and the system voltage is recovered above minimum permissible voltage. The optimization is done using the Surrogate optimization and Genetic algorithm of the MATLAB optimization toolbox and made sure that the number of BDs is minimized. A comparative analysis is done from the results obtained from both of the methods. The findings of the thesis highlight the optimization approach for the placement of blocking devices that takes into account the hotspot temperature rise of transformer tie-plates and windings and a realistic criterion that includes the cost of the repair or replacement of transformers based on the hotspot temperature rise of transformers into the optimization approach. The thesis presents the selection criteria for the two optimization solvers, surrogate optimization and genetic algorithm, after researching and reviewing different solvers from the MATLAB optimization toolbox. The total cost of BD placement is reduced where the total load is reduced to some extent based on different levels of geoelectric field ($E$) to maintain the bus voltages above minimum permissible voltage, and the cost can be calculated based on the loss of load, and extra number of BDs can be avoided. The results obtained from surrogate optimization are proved to be effective and efficient as the total number of BDs resulting from surrogate optimization is less than the total number of BDs resulting from genetic algorithm. The nature of genetic algorithm is stochastic in nature, the result not converging to the global minimum, and the time taken by genetic algorithm for the program execution were major drawbacks. In contrast, the characteristics of surrogate algorithm, such as a result, proved to be converging, non-stochastic in nature, unlike genetic algorithm, and comparatively less time consuming than genetic algorithm proving surrogate optimization to be more reliable and efficient

Reduced Nodal Admittance Matrix Method for Probabilistic GIC Analysis in Power Grids

Efficient probabilistic geomagnetically induced current (GIC) analysis in power grids provides tools for assessing and mitigating small-probability tail risks of geomagnetic disturbances, especially in early warning and real-time scenarios. This letter employs the reduced nodal admittance matrix (RNAM) to speed up GIC calculation based on Kron reduction. Moreover, the proposed RNAM method is used to achieve a more efficient analysis of probabilistic GICs, which considers the uncertainty of the substation grounding resistances. The novel method is compared with the classical algorithms including the nodal admittance matrix method, the Lehtinen-Pirjola method, and the bus admittance matrix method, and its efficiency improvement is illustrated with several power grid test cases