Matching Items (14)
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- All Subjects: Electric power systems
- Creators: Sankar, Lalitha
- Creators: Heydt, Gerald
- Creators: Tylavsky, Daniel J
Description
Due to great challenges from aggressive environmental regulations, increased demand due to new technologies and the integration of renewable energy sources, the energy industry may radically change the way the power system is operated and designed. With the motivation of studying and planning the future power system under these new challenges, the development of the new tools is required. A network equivalent that can be used in such planning tools needs to be generated based on an accurate power flow model and an equivalencing procedure that preserves the key characteristics of the original system. Considering the pervasive use of the dc power flow models, their accuracy is of great concern. The industry seems to be sanguine about the performance of dc power flow models, but recent research has shown that the performance of different formulations is highly variable. In this thesis, several dc power-flow models are analyzed theoretically and evaluated numerically in IEEE 118-bus system and Eastern Interconnection 62,000-bus system. As shown in the numerical example, the alpha-matching dc power flow model performs best in matching the original ac power flow solution. Also, the possibility of applying these dc models in the various applications has been explored and demonstrated. Furthermore, a novel hot-start optimal dc power-flow model based on ac power transfer distribution factors (PTDFs) is proposed, implemented and tested. This optimal-reactance-only dc model not only matches the original ac PF solution well, but also preserves the congestion pattern obtain from the OPF results of the original ac model. Three improved strategies were proposed for applying the bus-aggregation technique to the large-scale systems, like EI and ERCOT, to improve the execution time, and memory requirements when building a reduced equivalent model. Speed improvements of up to a factor of 200 were observed.
ContributorsQi, Yingying (Author) / Tylavsky, Daniel J (Thesis advisor) / Hedman, Kory W (Committee member) / Sankar, Lalitha (Committee member) / Arizona State University (Publisher)
Created2013
Description
Today, the electric power system faces new challenges from rapid developing technology and the growing concern about environmental problems. The future of the power system under these new challenges needs to be planned and studied. However, due to the high degree of computational complexity of the optimization problem, conducting a system planning study which takes into account the market structure and environmental constraints on a large-scale power system is computationally taxing. To improve the execution time of large system simulations, such as the system planning study, two possible strategies are proposed in this thesis. The first one is to implement a relative new factorization method, known as the multifrontal method, to speed up the solution of the sparse linear matrix equations within the large system simulations. The performance of the multifrontal method implemented by UMFAPACK is compared with traditional LU factorization on a wide range of power-system matrices. The results show that the multifrontal method is superior to traditional LU factorization on relatively denser matrices found in other specialty areas, but has poor performance on the more sparse matrices that occur in power-system applications. This result suggests that multifrontal methods may not be an effective way to improve execution time for large system simulation and power system engineers should evaluate the performance of the multifrontal method before applying it to their applications. The second strategy is to develop a small dc equivalent of the large-scale network with satisfactory accuracy for the large-scale system simulations. In this thesis, a modified Ward equivalent is generated for a large-scale power system, such as the full Electric Reliability Council of Texas (ERCOT) system. In this equivalent, all the generators in the full model are retained integrally. The accuracy of the modified Ward equivalent is validated and the equivalent is used to conduct the optimal generation investment planning study. By using the dc equivalent, the execution time for optimal generation investment planning is greatly reduced. Different scenarios are modeled to study the impact of fuel prices, environmental constraints and incentives for renewable energy on future investment and retirement in generation.
ContributorsLi, Nan (Author) / Tylavsky, Daniel J (Thesis advisor) / Vittal, Vijay (Committee member) / Hedman, Kory W (Committee member) / Arizona State University (Publisher)
Created2012
Description
Contemporary methods for dynamic security assessment (DSA) mainly re-ly on time domain simulations to explore the influence of large disturbances in a power system. These methods are computationally intensive especially when the system operating point changes continually. The trajectory sensitivity method, when implemented and utilized as a complement to the existing DSA time domain simulation routine, can provide valuable insights into the system variation in re-sponse to system parameter changes. The implementation of the trajectory sensitivity analysis is based on an open source power system analysis toolbox called PSAT. Eight categories of sen-sitivity elements have been implemented and tested. The accuracy assessment of the implementation demonstrates the validity of both the theory and the imple-mentation. The computational burden introduced by the additional sensitivity equa-tions is relieved by two innovative methods: one is by employing a cluster to per-form the sensitivity calculations in parallel; the other one is by developing a mod-ified very dishonest Newton method in conjunction with the latest sparse matrix processing technology. The relation between the linear approximation accuracy and the perturba-tion size is also studied numerically. It is found that there is a fixed connection between the linear approximation accuracy and the perturbation size. Therefore this finding can serve as a general application guide to evaluate the accuracy of the linear approximation. The applicability of the trajectory sensitivity approach to a large realistic network has been demonstrated in detail. This research work applies the trajectory sensitivity analysis method to the Western Electricity Coordinating Council (WECC) system. Several typical power system dynamic security problems, in-cluding the transient angle stability problem, the voltage stability problem consid-ering load modeling uncertainty and the transient stability constrained interface real power flow limit calculation, have been addressed. Besides, a method based on the trajectory sensitivity approach and the model predictive control has been developed for determination of under frequency load shedding strategy for real time stability assessment. These applications have shown the great efficacy and accuracy of the trajectory sensitivity method in handling these traditional power system stability problems.
ContributorsHou, Guanji (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald (Committee member) / Tylavsky, Daniel (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2012
Description
Electric power systems are facing great challenges from environmental regulations, changes in demand due to new technologies like electric vehicle, as well as the integration of various renewable energy sources. These factors taken together require the development of new tools to help make policy and investment decisions for the future power grid. The requirements of a network equivalent to be used in such planning tools are very different from those assumed in the development of traditional equivalencing procedures. This dissertation is focused on the development, implementation and verification of two network equivalencing approaches on large power systems, such as the Eastern Interconnection. Traditional Ward-type equivalences are a class of equivalencing approaches but this class has some significant drawbacks. It is well known that Ward-type equivalents "smear" the injections of external generators over a large number of boundary buses. For newer long-term investment applications that take into account such things as greenhouse gas (GHG) regulations and generator availability, it is computationally impractical to model fractions of generators located at many buses. A modified-Ward equivalent is proposed to address this limitation such that the external generators are moved wholesale to some internal buses based on electrical distance. This proposed equivalencing procedure is designed so that the retained-line power flows in the equivalent match those in the unreduced (full) model exactly. During the reduction process, accommodations for special system elements are addressed, including static VAr compensators (SVCs), high voltage dc (HVDC) transmission lines, and phase angle regulators. Another network equivalencing approach based on the dc power flow assumptions and the power transfer distribution factors (PTDFs) is proposed. This method, rather than eliminate buses via Gauss-reduction, aggregates buses on a zonal basis. The bus aggregation approach proposed here is superior to the existing bus aggregation methods in that a) under the base case, the equivalent-system inter-zonal power flows exactly match those calculated using the full-network-model b) as the operating conditions change, errors in line flows are reduced using the proposed bus clustering algorithm c) this method is computationally more efficient than other bus aggregation methods proposed heretofore. A critical step in achieving accuracy with a bus aggregation approach is selecting which buses to cluster together and how many clusters are needed. Clustering in this context refers to the process of partitioning a network into subsets of buses. An efficient network clustering method is proposed based on the PTDFs and the data mining techniques. This method is applied to the EI topology using the "Saguaro" supercomputer at ASU, a resource with sufficient memory and computational capability for handling this 60,000-bus and 80,000-branch system. The network equivalents generated by the proposed approaches are verified and tested for different operating conditions and promising results have been observed.
ContributorsShi, Di (Author) / Tylavsky, Daniel J (Thesis advisor) / Vittal, Vijay (Committee member) / Hedman, Kory (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2012
Description
In electric power systems, phasor measurement units (PMUs) are capable of providing synchronized voltage and current phasor measurements which are superior to conventional measurements collected by the supervisory control and data acquisition (SCADA) system in terms of resolution and accuracy. These measurements are known as synchrophasor measurements. Considerable research work has been done on the applications of PMU measurements based on the as-sumption that a high level of accuracy is obtained in the field. The study in this dissertation is conducted to address the basic issue concerning the accuracy of actual PMU measurements in the field. Synchronization is one of the important features of PMU measurements. However, the study presented in this dissertation reveals that the problem of faulty synchronization between measurements with the same time stamps from different PMUs exists. A Kalman filter model is proposed to analyze and calcu-late the time skew error caused by faulty synchronization. In order to achieve a high level of accuracy of PMU measurements, inno-vative methods are proposed to detect and identify system state changes or bad data which are reflected by changes in the measurements. This procedure is ap-plied as a key step in adaptive Kalman filtering of PMU measurements to over-come the insensitivity of a conventional Kalman filter. Calibration of PMU measurements is implemented in specific PMU instal-lation scenarios using transmission line (TL) parameters from operation planning data. The voltage and current correction factors calculated from the calibration procedure indicate the possible errors in PMU measurements. Correction factors can be applied in on-line calibration of PMU measurements. A study is conducted to address an important issue when integrating PMU measurements into state estimation. The reporting rate of PMU measurements is much higher than that of the measurements collected by the SCADA. The ques-tion of how to buffer PMU measurements is raised. The impact of PMU meas-urement buffer length on state estimation is discussed. A method based on hy-pothesis testing is proposed to determine the optimal buffer length of PMU meas-urements considering the two conflicting features of PMU measurements, i. e. un-certainty and variability. Results are presented for actual PMU synchrophasor measurements.
ContributorsZhang, Qing (Author) / Heydt, Gerald (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Ayyanar, Raja (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2012
Description
Many methods have been proposed to estimate power system small signal stability, for either analysis or control, through identification of modal frequencies and their damping levels. Generally, estimation methods have been employed to assess small signal stability from collected field measurements. However, the challenge to using these methods in assessing field measurements is their ability to accurately estimate stability in the presence of noise. In this thesis a new method is developed which estimates the modal content of simulated and actual field measurements using orthogonal polynomials and the results are compared to other commonly used estimators. This new method estimates oscillatory performance by fitting an associate Hermite polynomial to time domain data and extrapolating its spectrum to identify small signal power system frequencies. Once the frequencies are identified, damping assessment is performed using a modified sliding window technique with the use of linear prediction (LP). Once the entire assessment is complete the measurements can be judged to be stable or unstable. Collectively, this new technique is known as the associate Hermite expansion (AHE) algorithm. Validation of the AHE method versus results from four other spectral estimators demonstrates the method's accuracy and modal estimation ability with and without the presence of noise. A Prony analysis, a Yule-Walker autoregressive algorithm, a second sliding window estimator and the Hilbert-Huang Transform method are used in comparative assessments in support of this thesis. Results from simulated and actual field measurements are used in the comparisons, as well as artificially generated simple signals. A search for actual field testing results performed by a utility was undertaken and a request was made to obtain the measurements of a brake insertion test. Comparison results show that the AHE method is accurate as compared to the other commonly used spectral estimators and its predictive capability exceeded the other estimators in the presence of Gaussian noise. As a result, the AHE method could be employed in areas including operations and planning analysis, post-mortem analysis, power system damping scheme design and other analysis areas.
ContributorsKokanos, Barrie Lee (Author) / Karady, George G. (Thesis advisor) / Heydt, Gerald (Committee member) / Farmer, Richard G (Committee member) / Ayyanar, Raja (Committee member) / Karam, Lina (Committee member) / Arizona State University (Publisher)
Created2010
Description
After a power system blackout, system restoration is the most important task for the operators. Most power systems rely on an off&ndashline; restoration plan and the experience of operators to select scenarios for the black start path. Using an off&ndashline; designed restoration plan based on past experience may not be the most reliable approach under changing network configurations and loading levels. Hence, an objective restoration path selection procedure, including the option to check constraints, may be more responsive in providing directed guidance to the operators to identify the optimal transmission path to deliver power to other power plants or to pick up load as needed. After the system is subjected to a blackout, parallel restoration is an efficient way to speed up the restoration process. For a large scale power system, this system sectionalizing problem is quite complicated when considering black&ndashstart; constraints, generation/load balance constraints and voltage constraints. This dissertation presents an ordered binary decision diagram (OBDD) &ndashbased; system sectionalizing method, by which the splitting points can be quickly found. The simulation results on the IEEE 39 and 118&ndashbus; system show that the method can successfully split the system into subsystems satisfying black&ndashstart; constraints, generation/load balance constraints and voltage constraints. A power transfer distribution factor (PTDF)&ndashbased; approach will be described in this dissertation to check constraints while restoring the system. Two types of restoration performance indices are utilized considering all possible restoration paths, which are then ranked according to their expected performance characteristics as reflected by the restoration performance index. PTDFs and weighting factors are used to determine the ordered list of restoration paths, which can enable the load to be picked up by lightly loaded lines or relieve stress on heavily loaded lines. A transmission path agent can then be formulated by performing the automatic path selection under different system operating conditions. The proposed restoration strategy is tested on the IEEE&ndash39; bus system and on the Western region of the Entergy system. The testing results reveal that the proposed strategy can be used in real time.
ContributorsWang, Chong (Author) / Vittal, Vijay (Thesis advisor) / Tylavsky, Daniel (Committee member) / Heydt, Gerald (Committee member) / Farmer, Richard (Committee member) / Arizona State University (Publisher)
Created2010
Description
The large distributed electric power system is a hierarchical network involving the
transportation of power from the sources of power generation via an intermediate
densely connected transmission network to a large distribution network of end-users
at the lowest level of the hierarchy. At each level of the hierarchy (generation/ trans-
mission/ distribution), the system is managed and monitored with a combination of
(a) supervisory control and data acquisition (SCADA); and (b) energy management
systems (EMSs) that process the collected data and make control and actuation de-
cisions using the collected data. However, at all levels of the hierarchy, both SCADA
and EMSs are vulnerable to cyber attacks. Furthermore, given the criticality of the
electric power infrastructure, cyber attacks can have severe economic and social con-
sequences.
This thesis focuses on cyber attacks on SCADA and EMS at the transmission
level of the electric power system. The goal is to study the consequences of three
classes of cyber attacks that can change topology data. These classes include: (i)
unobservable state-preserving cyber attacks that only change the topology data; (ii)
unobservable state-and-topology cyber-physical attacks that change both states and
topology data to enable a coordinated physical and cyber attack; and (iii) topology-
targeted man-in-the-middle (MitM) communication attacks that alter topology data
shared during inter-EMS communication. Specically, attack class (i) and (ii) focus on
the unobservable attacks on single regional EMS while class (iii) focuses on the MitM
attacks on communication links between regional EMSs. For each class of attacks,
the theoretical attack model and the implementation of attacks are provided, and the
worst-case attack and its consequences are exhaustively studied. In particularly, for
class (ii), a two-stage optimization problem is introduced to study worst-case attacks
that can cause a physical line over
ow that is unobservable in the cyber layer. The long-term implication and the system anomalies are demonstrated via simulation.
For attack classes (i) and (ii), both mathematical and experimental analyses sug-
gest that these unobservable attacks can be limited or even detected with resiliency
mechanisms including load monitoring, anomalous re-dispatches checking, and his-
torical data comparison. For attack class (iii), countermeasures including anomalous
tie-line interchange verication, anomalous re-dispatch alarms, and external contin-
gency lists sharing are needed to thwart such attacks.
transportation of power from the sources of power generation via an intermediate
densely connected transmission network to a large distribution network of end-users
at the lowest level of the hierarchy. At each level of the hierarchy (generation/ trans-
mission/ distribution), the system is managed and monitored with a combination of
(a) supervisory control and data acquisition (SCADA); and (b) energy management
systems (EMSs) that process the collected data and make control and actuation de-
cisions using the collected data. However, at all levels of the hierarchy, both SCADA
and EMSs are vulnerable to cyber attacks. Furthermore, given the criticality of the
electric power infrastructure, cyber attacks can have severe economic and social con-
sequences.
This thesis focuses on cyber attacks on SCADA and EMS at the transmission
level of the electric power system. The goal is to study the consequences of three
classes of cyber attacks that can change topology data. These classes include: (i)
unobservable state-preserving cyber attacks that only change the topology data; (ii)
unobservable state-and-topology cyber-physical attacks that change both states and
topology data to enable a coordinated physical and cyber attack; and (iii) topology-
targeted man-in-the-middle (MitM) communication attacks that alter topology data
shared during inter-EMS communication. Specically, attack class (i) and (ii) focus on
the unobservable attacks on single regional EMS while class (iii) focuses on the MitM
attacks on communication links between regional EMSs. For each class of attacks,
the theoretical attack model and the implementation of attacks are provided, and the
worst-case attack and its consequences are exhaustively studied. In particularly, for
class (ii), a two-stage optimization problem is introduced to study worst-case attacks
that can cause a physical line over
ow that is unobservable in the cyber layer. The long-term implication and the system anomalies are demonstrated via simulation.
For attack classes (i) and (ii), both mathematical and experimental analyses sug-
gest that these unobservable attacks can be limited or even detected with resiliency
mechanisms including load monitoring, anomalous re-dispatches checking, and his-
torical data comparison. For attack class (iii), countermeasures including anomalous
tie-line interchange verication, anomalous re-dispatch alarms, and external contin-
gency lists sharing are needed to thwart such attacks.
ContributorsZhang, Jiazi (Author) / Sankar, Lalitha (Thesis advisor) / Hedman, Kory (Committee member) / Kosut, Oliver (Committee member) / Arizona State University (Publisher)
Created2015
Description
Understanding the graphical structure of the electric power system is important
in assessing reliability, robustness, and the risk of failure of operations of this criti-
cal infrastructure network. Statistical graph models of complex networks yield much
insight into the underlying processes that are supported by the network. Such gen-
erative graph models are also capable of generating synthetic graphs representative
of the real network. This is particularly important since the smaller number of tradi-
tionally available test systems, such as the IEEE systems, have been largely deemed
to be insucient for supporting large-scale simulation studies and commercial-grade
algorithm development. Thus, there is a need for statistical generative models of
electric power network that capture both topological and electrical properties of the
network and are scalable.
Generating synthetic network graphs that capture key topological and electrical
characteristics of real-world electric power systems is important in aiding widespread
and accurate analysis of these systems. Classical statistical models of graphs, such as
small-world networks or Erd}os-Renyi graphs, are unable to generate synthetic graphs
that accurately represent the topology of real electric power networks { networks
characterized by highly dense local connectivity and clustering and sparse long-haul
links.
This thesis presents a parametrized model that captures the above-mentioned
unique topological properties of electric power networks. Specically, a new Cluster-
and-Connect model is introduced to generate synthetic graphs using these parameters.
Using a uniform set of metrics proposed in the literature, the accuracy of the proposed
model is evaluated by comparing the synthetic models generated for specic real
electric network graphs. In addition to topological properties, the electrical properties
are captured via line impedances that have been shown to be modeled reliably by well-studied heavy tailed distributions. The details of the research, results obtained and
conclusions drawn are presented in this document.
in assessing reliability, robustness, and the risk of failure of operations of this criti-
cal infrastructure network. Statistical graph models of complex networks yield much
insight into the underlying processes that are supported by the network. Such gen-
erative graph models are also capable of generating synthetic graphs representative
of the real network. This is particularly important since the smaller number of tradi-
tionally available test systems, such as the IEEE systems, have been largely deemed
to be insucient for supporting large-scale simulation studies and commercial-grade
algorithm development. Thus, there is a need for statistical generative models of
electric power network that capture both topological and electrical properties of the
network and are scalable.
Generating synthetic network graphs that capture key topological and electrical
characteristics of real-world electric power systems is important in aiding widespread
and accurate analysis of these systems. Classical statistical models of graphs, such as
small-world networks or Erd}os-Renyi graphs, are unable to generate synthetic graphs
that accurately represent the topology of real electric power networks { networks
characterized by highly dense local connectivity and clustering and sparse long-haul
links.
This thesis presents a parametrized model that captures the above-mentioned
unique topological properties of electric power networks. Specically, a new Cluster-
and-Connect model is introduced to generate synthetic graphs using these parameters.
Using a uniform set of metrics proposed in the literature, the accuracy of the proposed
model is evaluated by comparing the synthetic models generated for specic real
electric network graphs. In addition to topological properties, the electrical properties
are captured via line impedances that have been shown to be modeled reliably by well-studied heavy tailed distributions. The details of the research, results obtained and
conclusions drawn are presented in this document.
ContributorsHu, Jiale (Author) / Sankar, Lalitha (Thesis advisor) / Vittal, Vijay (Committee member) / Scaglione, Anna (Committee member) / Arizona State University (Publisher)
Created2015
Description
Constraint relaxation by definition means that certain security, operational, or financial constraints are allowed to be violated in the energy market model for a predetermined penalty price. System operators utilize this mechanism in an effort to impose a price-cap on shadow prices throughout the market. In addition, constraint relaxations can serve as corrective approximations that help in reducing the occurrence of infeasible or extreme solutions in the day-ahead markets. This work aims to capture the impact constraint relaxations have on system operational security. Moreover, this analysis also provides a better understanding of the correlation between DC market models and AC real-time systems and analyzes how relaxations in market models propagate to real-time systems. This information can be used not only to assess the criticality of constraint relaxations, but also as a basis for determining penalty prices more accurately.
Constraint relaxations practice was replicated in this work using a test case and a real-life large-scale system, while capturing both energy market aspects and AC real-time system performance. System performance investigation included static and dynamic security analysis for base-case and post-contingency operating conditions. PJM peak hour loads were dynamically modeled in order to capture delayed voltage recovery and sustained depressed voltage profiles as a result of reactive power deficiency caused by constraint relaxations. Moreover, impacts of constraint relaxations on operational system security were investigated when risk based penalty prices are used. Transmission lines in the PJM system were categorized according to their risk index and each category was as-signed a different penalty price accordingly in order to avoid real-time overloads on high risk lines.
This work also extends the investigation of constraint relaxations to post-contingency relaxations, where emergency limits are allowed to be relaxed in energy market models. Various scenarios were investigated to capture and compare between the impacts of base-case and post-contingency relaxations on real-time system performance, including the presence of both relaxations simultaneously. The effect of penalty prices on the number and magnitude of relaxations was investigated as well.
Constraint relaxations practice was replicated in this work using a test case and a real-life large-scale system, while capturing both energy market aspects and AC real-time system performance. System performance investigation included static and dynamic security analysis for base-case and post-contingency operating conditions. PJM peak hour loads were dynamically modeled in order to capture delayed voltage recovery and sustained depressed voltage profiles as a result of reactive power deficiency caused by constraint relaxations. Moreover, impacts of constraint relaxations on operational system security were investigated when risk based penalty prices are used. Transmission lines in the PJM system were categorized according to their risk index and each category was as-signed a different penalty price accordingly in order to avoid real-time overloads on high risk lines.
This work also extends the investigation of constraint relaxations to post-contingency relaxations, where emergency limits are allowed to be relaxed in energy market models. Various scenarios were investigated to capture and compare between the impacts of base-case and post-contingency relaxations on real-time system performance, including the presence of both relaxations simultaneously. The effect of penalty prices on the number and magnitude of relaxations was investigated as well.
ContributorsSalloum, Ahmed (Author) / Vittal, Vijay (Thesis advisor) / Hedman, Kory (Thesis advisor) / Heydt, Gerald (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2016