Matching Items (43)
Description
Today, more and more substations are created and reconstructed to satisfy the growing electricity demands for both industry and residence. It is always a big concern that the designed substation must guarantee the safety of persons who are in the area of the substation. As a result, the safety metrics (touch voltage, step voltage and grounding resistance), which should be considered at worst case, are supposed to be under the allowable values. To improve the accuracy of calculating safety metrics, at first, it is necessary to have a relatively accurate soil model instead of uniform soil model. Hence, the two-layer soil model is employed in this thesis. The new approximate finite equations with soil parameters (upper-layer resistivity, lower-layer resistivity and upper-layer thickness) are used, which are developed based on traditional infinite expression. The weighted- least-squares regression with new bad data detection method (adaptive weighted function) is applied to fit the measurement data from the Wenner-method. At the end, a developed error analysis method is used to obtain the error (variance) of each parameter. Once the soil parameters are obtained, it is possible to use a developed complex images method to calculate the mutual (self) resistance, which is the induced voltage of a conductor/rod by unit current form another conductor/rod. The basis of the calculation is Green's function between two point current sources, thus, it can be expanded to either the functions between point and line current sources, or the functions between line and line current sources. Finally, the grounding system optimization is implemented with developed three-step optimization strategy using MATLAB solvers. The first step is using "fmincon" solver to optimize the cost function with differentiable constraint equations from IEEE standard. The result of the first step is set as the initial values to the second step, which is using "patternsearch" solver, thus, the non-differentiable and more accurate constraint calculation can be employed. The final step is a backup step using "ga" solver, which is more robust but lager time cost.
ContributorsWu, Xuan (Author) / Tylavsky, Daniel (Thesis advisor) / Undrill, John (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
Description
This thesis presents a new technique to develop an air-conditioner (A/C) compressor single phase induction motor model for use in an electro-magnetic transient program (EMTP) simulation tool. The method developed also has the capability to represent multiple units of the component in a specific three-phase distribution feeder and investigate the phenomenon of fault-induced delayed voltage recovery (FIDVR) and the cause of motor stalling. The system of differential equations representing the single phase induction motor model is developed and formulated. Implicit backward Euler method is applied to numerically integrate the stator currents that are to be drawn from the electric network. The angular position dependency of the rotor shaft is retained in the inductance matrix associated with the model to accurately capture the dynamics of the motor loads. The equivalent circuit of the new model is interfaced with the electric network in the EMTP. The dynamic response of the motor when subjected to faults at different points on voltage waveform has been studied using the EMTP simulator. The mechanism and the impacts of motor stalling need to be explored with multiple units of the detailed model connected to a realistic three-phase distribution system. The model developed can be utilized to assess and improve the product design of compressor motors by air-conditioner manufacturers. Another critical application of the model would be to examine the impacts of asymmetric transmission faults on distribution systems to investigate and develop mitigation measures for the FIDVR problem.
ContributorsLiu, Yuan (Author) / Vittal, Vijay (Thesis advisor) / Undrill, John (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2012
Description
A pressurized water reactor (PWR) nuclear power plant (NPP) model is introduced into Positive Sequence Load Flow (PSLF) software by General Electric in order to evaluate the load-following capability of NPPs. The nuclear steam supply system (NSSS) consists of a reactor core, hot and cold legs, plenums, and a U-tube steam generator. The physical systems listed above are represented by mathematical models utilizing a state variable lumped parameter approach. A steady-state control program for the reactor, and simple turbine and governor models are also developed. Adequacy of the isolated reactor core, the isolated steam generator, and the complete PWR models are tested in Matlab/Simulink and dynamic responses are compared with the test results obtained from the H. B. Robinson NPP. Test results illustrate that the developed models represents the dynamic features of real-physical systems and are capable of predicting responses due to small perturbations of external reactivity and steam valve opening. Subsequently, the NSSS representation is incorporated into PSLF and coupled with built-in excitation system and generator models. Different simulation cases are run when sudden loss of generation occurs in a small power system which includes hydroelectric and natural gas power plants besides the developed PWR NPP. The conclusion is that the NPP can respond to a disturbance in the power system without exceeding any design and safety limits if appropriate operational conditions, such as achieving the NPP turbine control by adjusting the speed of the steam valve, are met. In other words, the NPP can participate in the control of system frequency and improve the overall power system performance.
ContributorsArda, Samet Egemen (Author) / Holbert, Keith E. (Thesis advisor) / Undrill, John (Committee member) / Tylavsky, Daniel (Committee member) / Arizona State University (Publisher)
Created2013
Description
With the increased penetration of solar PV, it has become considerable for the system planners and operators to recognize the impact of PV plant on the power system stability and reliable operation of grid. This enforced the development of adequate PV system models for grid planning and interconnection studies. Western Electricity Coordinating Council (WECC) Renewable Energy Modeling Task Force has developed generator/converter, electrical controller and plant controller modules to represent positive sequence solar PV plant model for grid interconnection studies. This work performs the validation of these PV plant models against the field measured data. Sheer purpose of this validation effort is to authenticate model accuracy and their capability to represent dynamics of a solar PV plant. Both steady state and dynamic models of PV plant are discussed in this work. An algorithm to fine tune and determine the electrical controller and plant controller module gains is developed. Controller gains as obtained from proposed algorithm is used in PV plant dynamic simulation model. Model is simulated for a capacitor bank switching event and simulated plant response is then compared with field measured data. Validation results demonstrate that, the proposed algorithm is performing well to determine controller gains within the region of interest. Also, it concluded that developed PV plant models are adequate enough to capture PV plant dynamics.
ContributorsSoni, Sachin (Author) / Karady, George G. (Thesis advisor) / Undrill, John (Committee member) / Vittal, Vijay (Committee member) / Arizona State University (Publisher)
Created2014
Description
With growing complexity of power grid interconnections, power systems may become increasingly vulnerable to low frequency oscillations (especially inter-area oscillations) and dependent on stabilizing controls using either local signals or wide-area signals to provide adequate damping. In recent years, the ability and potential to use wide-area signals for control purposes has increased since a significant investment has been made in the U. S. in deploying synchrophasor measurement technology. Fast and reliable communication systems are essential to enable the use of wide-area signals in controls. If wide-area signals find increased applicability in controls the security and reliability of power systems could be vulnerable to disruptions in communication systems. Even though numerous modern techniques have been developed to lower the probability of communication errors, communication networks cannot be designed to be always reliable. Given this background the motivation of this work is to build resiliency in the power grid controls to respond to failures in the communication network when wide-area control signals are used. In addition, this work also deals with the delay uncertainty associated with the wide-area signal transmission. In order to counteract the negative impact of communication failures on control effectiveness, two approaches are proposed and both approaches are motivated by considering the use of a robustly designed supplementary damping control (SDC) framework associated with a static VAr compensator (SVC). When there is no communication failure, the designed controller guarantees enhanced improvement in damping performance. When the wide-area signal in use is lost due to a communication failure, however, the resilient control provides the required damping of the inter-area oscillations by either utilizing another wide-area measurement through a healthy communication route or by simply utilizing an appropriate local control signal. Simulation results prove that with either of the proposed controls included, the system is stabilized regardless of communication failures, and thereby the reliability and sustainability of power systems is improved. The proposed approaches can be extended without loss of generality to the design of any resilient controller in cyber-physical engineering systems.
ContributorsZhang, Song (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald (Committee member) / Si, Jennie (Committee member) / Undrill, John (Committee member) / Arizona State University (Publisher)
Created2014
Description
Substation ground system insures safety of personnel, which deserves considerable attentions. Basic substation safety requirement quantities include ground grid resistance, mesh touch potential and step potential, moreover, optimal design of a substation ground system should include both safety concerns and ground grid construction cost. In the purpose of optimal designing the ground grid in the accurate and efficient way, an application package coded in MATLAB is developed and its core algorithm and main features are introduced in this work.
To ensure accuracy and personnel safety, a two-layer soil model is applied instead of the uniform soil model in this research. Some soil model parameters are needed for the two-layer soil model, namely upper-layer resistivity, lower-layer resistivity and upper-layer thickness. Since the ground grid safety requirement is considered under the earth fault, the value of fault current and fault duration time are also needed.
After all these parameters are obtained, a Resistance Matrix method is applied to calculate the mutual and self resistance between conductor segments on both the horizontal and vertical direction. By using a matrix equation of the relationship of mutual and self resistance and unit current of the conductor segments, the ground grid rise can be calculated. Green's functions are applied to calculate the earth potential at a certain point produced by horizontal or vertical line of current. Furthermore, the three basic ground grid safety requirement quantities: the mesh touch potential in the worst case point can be obtained from the earth potential and ground grid rise; the step potential can be obtained from two points' earth potential difference; the grid resistance can be obtained from ground grid rise and fault current.
Finally, in order to achieve ground grid optimization problem more accurate and efficient, which includes the number of meshes in the horizontal grid and the number of vertical rods, a novel two-step hybrid genetic algorithm-pattern search (GA-PS) optimization method is developed. The Genetic Algorithm (GA) is used first to search for an approximate starting point, which is used by the Pattern Search (PS) algorithm to find the final optimal result. This developed application provides an optimal grid design meeting all safety constraints. In the cause of the accuracy of the application, the touch potential, step potential, ground potential rise and grid resistance are compared with these produced by the industry standard application WinIGS and some theoretical ground grid model.
In summary, the developed application can solve the ground grid optimization problem with the accurate ground grid modeling method and a hybrid two-step optimization method.
To ensure accuracy and personnel safety, a two-layer soil model is applied instead of the uniform soil model in this research. Some soil model parameters are needed for the two-layer soil model, namely upper-layer resistivity, lower-layer resistivity and upper-layer thickness. Since the ground grid safety requirement is considered under the earth fault, the value of fault current and fault duration time are also needed.
After all these parameters are obtained, a Resistance Matrix method is applied to calculate the mutual and self resistance between conductor segments on both the horizontal and vertical direction. By using a matrix equation of the relationship of mutual and self resistance and unit current of the conductor segments, the ground grid rise can be calculated. Green's functions are applied to calculate the earth potential at a certain point produced by horizontal or vertical line of current. Furthermore, the three basic ground grid safety requirement quantities: the mesh touch potential in the worst case point can be obtained from the earth potential and ground grid rise; the step potential can be obtained from two points' earth potential difference; the grid resistance can be obtained from ground grid rise and fault current.
Finally, in order to achieve ground grid optimization problem more accurate and efficient, which includes the number of meshes in the horizontal grid and the number of vertical rods, a novel two-step hybrid genetic algorithm-pattern search (GA-PS) optimization method is developed. The Genetic Algorithm (GA) is used first to search for an approximate starting point, which is used by the Pattern Search (PS) algorithm to find the final optimal result. This developed application provides an optimal grid design meeting all safety constraints. In the cause of the accuracy of the application, the touch potential, step potential, ground potential rise and grid resistance are compared with these produced by the industry standard application WinIGS and some theoretical ground grid model.
In summary, the developed application can solve the ground grid optimization problem with the accurate ground grid modeling method and a hybrid two-step optimization method.
ContributorsZhang, Qianzhi (Author) / Tylavsky, Daniel (Thesis advisor) / Undrill, John (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2014
Description
Power flow calculation plays a significant role in power system studies and operation. To ensure the reliable prediction of system states during planning studies and in the operating environment, a reliable power flow algorithm is desired. However, the traditional power flow methods (such as the Gauss Seidel method and the Newton-Raphson method) are not guaranteed to obtain a converged solution when the system is heavily loaded.
This thesis describes a novel non-iterative holomorphic embedding (HE) method to solve the power flow problem that eliminates the convergence issues and the uncertainty of the existence of the solution. It is guaranteed to find a converged solution if the solution exists, and will signal by an oscillation of the result if there is no solution exists. Furthermore, it does not require a guess of the initial voltage solution.
By embedding the complex-valued parameter α into the voltage function, the power balance equations become holomorphic functions. Then the embedded voltage functions are expanded as a Maclaurin power series, V(α). The diagonal Padé approximant calculated from V(α) gives the maximal analytic continuation of V(α), and produces a reliable solution of voltages. The connection between mathematical theory and its application to power flow calculation is described in detail.
With the existing bus-type-switching routine, the models of phase shifters and three-winding transformers are proposed to enable the HE algorithm to solve practical large-scale systems. Additionally, sparsity techniques are used to store the sparse bus admittance matrix. The modified HE algorithm is programmed in MATLAB. A study parameter β is introduced in the embedding formula βα + (1- β)α^2. By varying the value of β, numerical tests of different embedding formulae are conducted on the three-bus, IEEE 14-bus, 118-bus, 300-bus, and the ERCOT systems, and the numerical performance as a function of β is analyzed to determine the “best” embedding formula. The obtained power-flow solutions are validated using MATPOWER.
This thesis describes a novel non-iterative holomorphic embedding (HE) method to solve the power flow problem that eliminates the convergence issues and the uncertainty of the existence of the solution. It is guaranteed to find a converged solution if the solution exists, and will signal by an oscillation of the result if there is no solution exists. Furthermore, it does not require a guess of the initial voltage solution.
By embedding the complex-valued parameter α into the voltage function, the power balance equations become holomorphic functions. Then the embedded voltage functions are expanded as a Maclaurin power series, V(α). The diagonal Padé approximant calculated from V(α) gives the maximal analytic continuation of V(α), and produces a reliable solution of voltages. The connection between mathematical theory and its application to power flow calculation is described in detail.
With the existing bus-type-switching routine, the models of phase shifters and three-winding transformers are proposed to enable the HE algorithm to solve practical large-scale systems. Additionally, sparsity techniques are used to store the sparse bus admittance matrix. The modified HE algorithm is programmed in MATLAB. A study parameter β is introduced in the embedding formula βα + (1- β)α^2. By varying the value of β, numerical tests of different embedding formulae are conducted on the three-bus, IEEE 14-bus, 118-bus, 300-bus, and the ERCOT systems, and the numerical performance as a function of β is analyzed to determine the “best” embedding formula. The obtained power-flow solutions are validated using MATPOWER.
ContributorsLi, Yuting (Author) / Tylavsky, Daniel J (Thesis advisor) / Undrill, John (Committee member) / Vittal, Vijay (Committee member) / Arizona State University (Publisher)
Created2015
Description
The uncertainty and variability associated with stochastic resources, such as wind and solar, coupled with the stringent reliability requirements and constantly changing system operating conditions (e.g., generator and transmission outages) introduce new challenges to power systems. Contemporary approaches to model reserve requirements within the conventional security-constrained unit commitment (SCUC) models may not be satisfactory with increasing penetration levels of stochastic resources; such conventional models pro-cure reserves in accordance with deterministic criteria whose deliverability, in the event of an uncertain realization, is not guaranteed. Smart, well-designed reserve policies are needed to assist system operators in maintaining reliability at least cost.
Contemporary market models do not satisfy the minimum stipulated N-1 mandate for generator contingencies adequately. This research enhances the traditional market practices to handle generator contingencies more appropriately. In addition, this research employs stochastic optimization that leverages statistical information of an ensemble of uncertain scenarios and data analytics-based algorithms to design and develop cohesive reserve policies. The proposed approaches modify the classical SCUC problem to include reserve policies that aim to preemptively anticipate post-contingency congestion patterns and account for resource uncertainty, simultaneously. The hypothesis is to integrate data-mining, reserve requirement determination, and stochastic optimization in a holistic manner without compromising on efficiency, performance, and scalability. The enhanced reserve procurement policies use contingency-based response sets and post-contingency transmission constraints to appropriately predict the influence of recourse actions, i.e., nodal reserve deployment, on critical transmission elements.
This research improves the conventional deterministic models, including reserve scheduling decisions, and facilitates the transition to stochastic models by addressing the reserve allocation issue. The performance of the enhanced SCUC model is compared against con-temporary deterministic models and a stochastic unit commitment model. Numerical results are based on the IEEE 118-bus and the 2383-bus Polish test systems. Test results illustrate that the proposed reserve models consistently outperform the benchmark reserve policies by improving the market efficiency and enhancing the reliability of the market solution at reduced costs while maintaining scalability and market transparency. The proposed approaches require fewer ISO discretionary adjustments and can be employed by present-day solvers with minimal disruption to existing market procedures.
Contemporary market models do not satisfy the minimum stipulated N-1 mandate for generator contingencies adequately. This research enhances the traditional market practices to handle generator contingencies more appropriately. In addition, this research employs stochastic optimization that leverages statistical information of an ensemble of uncertain scenarios and data analytics-based algorithms to design and develop cohesive reserve policies. The proposed approaches modify the classical SCUC problem to include reserve policies that aim to preemptively anticipate post-contingency congestion patterns and account for resource uncertainty, simultaneously. The hypothesis is to integrate data-mining, reserve requirement determination, and stochastic optimization in a holistic manner without compromising on efficiency, performance, and scalability. The enhanced reserve procurement policies use contingency-based response sets and post-contingency transmission constraints to appropriately predict the influence of recourse actions, i.e., nodal reserve deployment, on critical transmission elements.
This research improves the conventional deterministic models, including reserve scheduling decisions, and facilitates the transition to stochastic models by addressing the reserve allocation issue. The performance of the enhanced SCUC model is compared against con-temporary deterministic models and a stochastic unit commitment model. Numerical results are based on the IEEE 118-bus and the 2383-bus Polish test systems. Test results illustrate that the proposed reserve models consistently outperform the benchmark reserve policies by improving the market efficiency and enhancing the reliability of the market solution at reduced costs while maintaining scalability and market transparency. The proposed approaches require fewer ISO discretionary adjustments and can be employed by present-day solvers with minimal disruption to existing market procedures.
ContributorsSinghal, Nikita Ghanshyam (Author) / Hedman, Kory W (Thesis advisor) / Vittal, Vijay (Committee member) / Sankar, Lalitha (Committee member) / Pal, Anamitra (Committee member) / Arizona State University (Publisher)
Created2018
Description
Large-scale blackouts that have occurred across North America in the past few decades have paved the path for substantial amount of research in the field of security assessment of the grid. With the aid of advanced technology such as phasor measurement units (PMUs), considerable work has been done involving voltage stability analysis and power system dynamic behavior analysis to ensure security and reliability of the grid. Online dynamic security assessment (DSA) analysis has been developed and applied in several power system control centers. Existing applications of DSA are limited by the assumption of simplistic load profiles, which often considers a normative day to represent an entire year. To overcome these aforementioned challenges, this research developed a novel DSA scheme to provide security prediction in real-time for load profiles corresponding to different seasons. The major contributions of this research are to (1) develop a DSA scheme incorporated with PMU data, (2) consider a comprehensive seasonal load profile, (3) account for varying penetrations of renewable generation, and (4) compare the accuracy of different machine learning (ML) algorithms for DSA. The ML algorithms that will be the focus of this study include decision trees (DTs), support vector machines (SVMs), random forests (RFs), and multilayer neural networks (MLNNs).
This thesis describes the development of a novel DSA scheme using synchrophasor measurements that accounts for the load variability occurring across different seasons in a year. Different amounts of solar generation have also been incorporated in this study to account for increasing percentage of renewables in the modern grid. To account for the security of the operating conditions different ML algorithms have been trained and tested. A database of cases for different operating conditions has been developed offline that contains secure as well as insecure cases, and the ML models have been trained to classify the security or insecurity of a particular operating condition in real-time. Multiple scenarios are generated every 15 minutes for different seasons and stored in the database. The performance of this approach is tested on the IEEE-118 bus system.
This thesis describes the development of a novel DSA scheme using synchrophasor measurements that accounts for the load variability occurring across different seasons in a year. Different amounts of solar generation have also been incorporated in this study to account for increasing percentage of renewables in the modern grid. To account for the security of the operating conditions different ML algorithms have been trained and tested. A database of cases for different operating conditions has been developed offline that contains secure as well as insecure cases, and the ML models have been trained to classify the security or insecurity of a particular operating condition in real-time. Multiple scenarios are generated every 15 minutes for different seasons and stored in the database. The performance of this approach is tested on the IEEE-118 bus system.
ContributorsNATH, ANUBHAV (Author) / Pal, Anamitra (Thesis advisor) / Holbert, Keith (Committee member) / Wu, Meng (Committee member) / Arizona State University (Publisher)
Created2019
Description
Alternative sources of power generation interconnected at the transmission level have witnessed an increase in investment in the last few years. On the other hand, when the power systems are being operated close to their limits, power system operators and engineers face the challenge of ensuring a safe and reliable supply of electricity. In such a scenario, the reliability of the transmission system is crucial as it ensures secure transfer of uninterrupted power from the generating sources to the load centers. This thesis is aimed at ensuring the reliability of the transmission system from two perspectives. First, this work monitors power system disturbances such as unintentional islanding to ensure prompt detection and implementation of restorative actions and thus, minimizes the extent of damage. Secondly, it investigates power system disturbances such as transmission line outages through reliability evaluation and outage analysis in order to prevent reoccurrence of similar failures.
In this thesis, a passive Wide Area Measurement System (WAMS) based islanding detection scheme called Cumulative Sum of Change in Voltage Phase Angle Difference (CUSPAD) is proposed and tested on a modified 18 bus test system and a modified IEEE 118 bus system with various wind energy penetration levels. Comparative analysis between accuracies of the proposed approach and the conventional relative angle difference approach in presence of measurement errors indicate a superior performance of the former. Results obtained from the proposed approach also reveal that power system disturbances such as unintentional island formations are accurately detected in wind integrated transmission systems.
Quantitative evaluation of the transmission system reliability aids in the assessment of the existing system performance. Further, post-mortem analysis of failures is an important step in minimizing recurrent failures. Reliability evaluation and outage analysis of transmission line outages carried out in this thesis have revealed chronological trends in the system performance. A new index called Outage Impact Index (OII) is also been proposed which can identify and prioritize outages based on their severity. This would serve as a baselining index for assessing and monitoring future transmission system performances and will facilitate implementation of reliability improvement measures if found necessary.
In this thesis, a passive Wide Area Measurement System (WAMS) based islanding detection scheme called Cumulative Sum of Change in Voltage Phase Angle Difference (CUSPAD) is proposed and tested on a modified 18 bus test system and a modified IEEE 118 bus system with various wind energy penetration levels. Comparative analysis between accuracies of the proposed approach and the conventional relative angle difference approach in presence of measurement errors indicate a superior performance of the former. Results obtained from the proposed approach also reveal that power system disturbances such as unintentional island formations are accurately detected in wind integrated transmission systems.
Quantitative evaluation of the transmission system reliability aids in the assessment of the existing system performance. Further, post-mortem analysis of failures is an important step in minimizing recurrent failures. Reliability evaluation and outage analysis of transmission line outages carried out in this thesis have revealed chronological trends in the system performance. A new index called Outage Impact Index (OII) is also been proposed which can identify and prioritize outages based on their severity. This would serve as a baselining index for assessing and monitoring future transmission system performances and will facilitate implementation of reliability improvement measures if found necessary.
ContributorsBarkakati, Meghna (Author) / Pal, Anamitra (Thesis advisor) / Holbert, Keith E. (Committee member) / Weng, Yang (Committee member) / Arizona State University (Publisher)
Created2018