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- Genre: Academic theses
- Creators: Vittal, Vijay
- Resource Type: Text
- Status: Published
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
The flexibility in power system networks is not fully modeled in existing real-time contingency analysis (RTCA) and real-time security-constrained economic dispatch (RT SCED) applications. Thus, corrective transmission switching (CTS) is proposed in this dissertation to enable RTCA and RT SCED to take advantage of the flexibility in the transmission system in a practical way.
RTCA is first conducted to identify critical contingencies that may cause violations. Then, for each critical contingency, CTS is performed to determine the beneficial switching actions that can reduce post-contingency violations. To reduce computational burden, fast heuristic algorithms are proposed to generate candidate switching lists. Numerical simulations performed on three large-scale realistic power systems (TVA, ERCOT, and PJM) demonstrate that CTS can significantly reduce post-contingency violations. Parallel computing can further reduce the solution time.
RT SCED is to eliminate the actual overloads and potential post-contingency overloads identified by RTCA. Procedure-A, which is consistent with existing industry practices, is proposed to connect RTCA and RT SCED. As CTS can reduce post-contingency violations, higher branch limits, referred to as pseudo limits, may be available for some contingency-case network constraints. Thus, Procedure-B is proposed to take advantage of the reliability benefits provided by CTS. With the proposed Procedure-B, CTS can be modeled in RT SCED implicitly through the proposed pseudo limits for contingency-case network constraints, which requires no change to existing RT SCED tools. Numerical simulations demonstrate that the proposed Procedure-A can effectively eliminate the flow violations reported by RTCA and that the proposed Procedure-B can reduce most of the congestion cost with consideration of CTS.
The system status may be inaccurately estimated due to false data injection (FDI) cyber-attacks, which may mislead operators to adjust the system improperly and cause network violations. Thus, a two-stage FDI detection (FDID) approach, along with several metrics and an alert system, is proposed in this dissertation to detect FDI attacks. The first stage is to determine whether the system is under attack and the second stage would identify the target branch. Numerical simulations demonstrate the effectiveness of the proposed two-stage FDID approach.
RTCA is first conducted to identify critical contingencies that may cause violations. Then, for each critical contingency, CTS is performed to determine the beneficial switching actions that can reduce post-contingency violations. To reduce computational burden, fast heuristic algorithms are proposed to generate candidate switching lists. Numerical simulations performed on three large-scale realistic power systems (TVA, ERCOT, and PJM) demonstrate that CTS can significantly reduce post-contingency violations. Parallel computing can further reduce the solution time.
RT SCED is to eliminate the actual overloads and potential post-contingency overloads identified by RTCA. Procedure-A, which is consistent with existing industry practices, is proposed to connect RTCA and RT SCED. As CTS can reduce post-contingency violations, higher branch limits, referred to as pseudo limits, may be available for some contingency-case network constraints. Thus, Procedure-B is proposed to take advantage of the reliability benefits provided by CTS. With the proposed Procedure-B, CTS can be modeled in RT SCED implicitly through the proposed pseudo limits for contingency-case network constraints, which requires no change to existing RT SCED tools. Numerical simulations demonstrate that the proposed Procedure-A can effectively eliminate the flow violations reported by RTCA and that the proposed Procedure-B can reduce most of the congestion cost with consideration of CTS.
The system status may be inaccurately estimated due to false data injection (FDI) cyber-attacks, which may mislead operators to adjust the system improperly and cause network violations. Thus, a two-stage FDI detection (FDID) approach, along with several metrics and an alert system, is proposed in this dissertation to detect FDI attacks. The first stage is to determine whether the system is under attack and the second stage would identify the target branch. Numerical simulations demonstrate the effectiveness of the proposed two-stage FDID approach.
ContributorsLi, Xingpeng (Author) / Hedman, Kory (Thesis advisor) / Heydt, Gerald (Committee member) / Vittal, Vijay (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2017
Description
This research develops decision support mechanisms for power system operation and planning practices. Contemporary industry practices rely on deterministic approaches to approximate system conditions and handle growing uncertainties from renewable resources. The primary purpose of this research is to identify soft spots of the contemporary industry practices and propose innovative algorithms, methodologies, and tools to improve economics and reliability in power systems.
First, this dissertation focuses on transmission thermal constraint relaxation practices. Most system operators employ constraint relaxation practices, which allow certain constraints to be relaxed for penalty prices, in their market models. A proper selection of penalty prices is imperative due to the influence that penalty prices have on generation scheduling and market settlements. However, penalty prices are primarily decided today based on stakeholder negotiations or system operator’s judgments. There is little to no methodology or engineered approach around the determination of these penalty prices. This work proposes new methods that determine the penalty prices for thermal constraint relaxations based on the impact overloading can have on the residual life of the line. This study evaluates the effectiveness of the proposed methods in the short-term operational planning and long-term transmission expansion planning studies.
The second part of this dissertation investigates an advanced methodology to handle uncertainties associated with high penetration of renewable resources, which poses new challenges to power system reliability and calls attention to include stochastic modeling within resource scheduling applications. However, the inclusion of stochastic modeling within mathematical programs has been a challenge due to computational complexities. Moreover, market design issues due to the stochastic market environment make it more challenging. Given the importance of reliable and affordable electric power, such a challenge to advance existing deterministic resource scheduling applications is critical. This ongoing and joint research attempts to overcome these hurdles by developing a stochastic look-ahead commitment tool, which is a stand-alone advisory tool. This dissertation contributes to the derivation of a mathematical formulation for the extensive form two-stage stochastic programming model, the utilization of Progressive Hedging decomposition algorithm, and the initial implementation of the Progressive Hedging subproblem along with various heuristic strategies to enhance the computational performance.
First, this dissertation focuses on transmission thermal constraint relaxation practices. Most system operators employ constraint relaxation practices, which allow certain constraints to be relaxed for penalty prices, in their market models. A proper selection of penalty prices is imperative due to the influence that penalty prices have on generation scheduling and market settlements. However, penalty prices are primarily decided today based on stakeholder negotiations or system operator’s judgments. There is little to no methodology or engineered approach around the determination of these penalty prices. This work proposes new methods that determine the penalty prices for thermal constraint relaxations based on the impact overloading can have on the residual life of the line. This study evaluates the effectiveness of the proposed methods in the short-term operational planning and long-term transmission expansion planning studies.
The second part of this dissertation investigates an advanced methodology to handle uncertainties associated with high penetration of renewable resources, which poses new challenges to power system reliability and calls attention to include stochastic modeling within resource scheduling applications. However, the inclusion of stochastic modeling within mathematical programs has been a challenge due to computational complexities. Moreover, market design issues due to the stochastic market environment make it more challenging. Given the importance of reliable and affordable electric power, such a challenge to advance existing deterministic resource scheduling applications is critical. This ongoing and joint research attempts to overcome these hurdles by developing a stochastic look-ahead commitment tool, which is a stand-alone advisory tool. This dissertation contributes to the derivation of a mathematical formulation for the extensive form two-stage stochastic programming model, the utilization of Progressive Hedging decomposition algorithm, and the initial implementation of the Progressive Hedging subproblem along with various heuristic strategies to enhance the computational performance.
ContributorsKwon, Jonghwan (Author) / Hedman, Kory Walter (Thesis advisor) / Heydt, Gerald (Committee member) / Vittal, Vijay (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2017
Description
Distributed energy resources have experienced dramatic growth and are beginning to support a significant amount of customer loads. Power electronic converters are the primary interface between the grid and the distributed energy resources/storage and offer several advantages including fast control, flexibility and high efficiency. The efficiency and the power density by volume are important performance metrics of a power converter. Compact and high efficiency power converter is beneficial to the cost-effectiveness of the converter interfaced generations. In this thesis, a soft-switching technique is proposed to reduce the size of passive components in a grid-connected converter while maintaining a high power conversion efficiency. The dynamic impact of the grid-connected converters on the power system is causing concerns as the penetration level of the converter interfaced generation increases, necessitating a detailed dynamic analysis. The unbalanced nature of distribution systems makes the conventional transient stability simulation based on positive sequence components unsuitable for this purpose. Methods suitable for the dynamic simulation of grid-connected converters in large scale unbalanced and single-phase systems are presented in this thesis to provide an effective way to study the dynamic interactions between the grid and the converters. Dynamic-link library (DLL) of converter dynamic models are developed by which converter dynamic simulations can be easily conducted in OpenDSS. To extend the converter controls testing beyond pure simulation, real-time simulation can be utilized where partial realistic scenarios can be created by including realistic components in the simulation loop. In this work, a multi-platform, real-time simulation testbed including actual digital controller platforms, communication networks and inverters has been developed for validating the microgrid concepts and implementations. A hierarchical converted based microgrid control scheme is proposed which enables the islanded microgrid operation with 100% penetration level of converter interfaced generation. Impact of the load side dynamic modeling on the converter response is also discussed in this thesis.
ContributorsYu, Ziwei (Author) / Ayyanar, Raja (Thesis advisor) / Vittal, Vijay (Committee member) / Qin, Jiangchao (Committee member) / Weng, Yang (Committee member) / Arizona State University (Publisher)
Created2018
Description
The phrase water-energy nexus is commonly used to describe the inherent and critical interdependencies between the electric power system and the water supply systems (WSS). The key interdependencies between the two systems are the power plant’s requirement of water for the cooling cycle and the water system’s need of electricity for pumping for water supply. While previous work has considered the dependency of WSS on the electrical power, this work incorporates into an optimization-simulation framework, consideration of the impact of short and long-term limited availability of water and/or electrical energy.
This research focuses on the water supply system (WSS) facet of the multi-faceted optimization and control mechanism developed for an integrated water – energy nexus system under U.S. National Science Foundation (NSF) project 029013-0010 CRISP Type 2 – Resilient cyber-enabled electric energy and water infrastructures modeling and control under extreme mega drought scenarios. A water supply system (WSS) conveys water from sources (such as lakes, rivers, dams etc.) to the treatment plants and then to users via the water distribution systems (WDS) and/or water supply canal systems (WSCS). Optimization-simulation methodologies are developed for the real-time operation of water supply systems (WSS) under critical conditions of limited electrical energy and/or water availability due to emergencies such as extreme drought conditions, electric grid failure, and other severe conditions including natural and manmade disasters. The coupling between WSS and the power system was done through alternatively exchanging data between the power system and WSS simulations via a program control overlay developed in python.
A new methodology for WDS infrastructural-operational resilience (IOR) computation was developed as a part of this research to assess the real-time performance of the WDS under emergency conditions. The methodology combines operational resilience and component level infrastructural robustness to provide a comprehensive performance assessment tool.
The optimization-simulation and resilience computation methodologies developed were tested for both hypothetical and real example WDS and WSCS, with results depicting improved resilience for operations of the WSS under normal and emergency conditions.
This research focuses on the water supply system (WSS) facet of the multi-faceted optimization and control mechanism developed for an integrated water – energy nexus system under U.S. National Science Foundation (NSF) project 029013-0010 CRISP Type 2 – Resilient cyber-enabled electric energy and water infrastructures modeling and control under extreme mega drought scenarios. A water supply system (WSS) conveys water from sources (such as lakes, rivers, dams etc.) to the treatment plants and then to users via the water distribution systems (WDS) and/or water supply canal systems (WSCS). Optimization-simulation methodologies are developed for the real-time operation of water supply systems (WSS) under critical conditions of limited electrical energy and/or water availability due to emergencies such as extreme drought conditions, electric grid failure, and other severe conditions including natural and manmade disasters. The coupling between WSS and the power system was done through alternatively exchanging data between the power system and WSS simulations via a program control overlay developed in python.
A new methodology for WDS infrastructural-operational resilience (IOR) computation was developed as a part of this research to assess the real-time performance of the WDS under emergency conditions. The methodology combines operational resilience and component level infrastructural robustness to provide a comprehensive performance assessment tool.
The optimization-simulation and resilience computation methodologies developed were tested for both hypothetical and real example WDS and WSCS, with results depicting improved resilience for operations of the WSS under normal and emergency conditions.
ContributorsKhatavkar, Puneet (Author) / Mays, Larry W. (Thesis advisor) / Vittal, Vijay (Committee member) / Mascaro, Giuseppe (Committee member) / Fox, Peter (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2019
Description
Until late 1970’s the primary focus in power system modeling has been largely directed towards power system generation and transmission. Over the years, the importance of load modeling grew and having an accurate representation of load played an important role in the planning and operation studies. With an emphasis on tackling the topic of load modeling, this thesis presents the following intermediary steps in developing accurate load models:
1. Synthesis of a three-phase standard feeder and load model using the measured voltages and currents, for events such as faults and feeder pickup cases, obtained at the head of the feeder.
2. Investigated the impact of the synthesized standard feeder and load model on the sub-transmission system for a feeder pick-up case.
In the first phase of this project, a standard feeder and load model had been synthesized by capturing the current transients when three-phase voltage measurements (obtained from a local electric utility) are played-in as input to the synthesized model. The comparison between the measured currents and the simulated currents obtained using an electromagnetic transient analysis software (PSCAD) are made at the head of the designed feeder. The synthesized load model has a load composition which includes impedance loads, single-phase induction motor loads and three-phase induction motor loads. The parameters of the motor models are adjusted to obtain a good correspondence between measured three-phase currents and simulated current responses at the head of the feeder when subjected to events under which measurements were obtained on the feeder. These events include faults which occurred upstream of the feeder at a higher voltage level and a feeder pickup event that occurred downstream from the head of the feeder. Two different load compositions have been obtained for this feeder and load model depending on the types of load present in the surrounding area (residential or industrial/commercial).
The second phase of this project examines the impact of the feeder pick-up event on the 69 kV sub-transmission system using the obtained standard feeder and load model. Using the 69 kV network data obtained from a local utility, a sub-transmission network has been built in PSCAD. The main difference between the first and second phase of this project is that no measurements are played-in to the model in the latter case. Instead, the feeder pick-up event at a particular substation is simulated using the reduced equivalent of the 69 kV sub-transmission circuit together with the synthesized three-phase models of the feeder and the loads obtained in the first phase of the project. Using this analysis, it is observed that a good correspondence between the PSCAD simulated values of both three-phase voltages and currents with their corresponding measured responses at the substation is achieved.
1. Synthesis of a three-phase standard feeder and load model using the measured voltages and currents, for events such as faults and feeder pickup cases, obtained at the head of the feeder.
2. Investigated the impact of the synthesized standard feeder and load model on the sub-transmission system for a feeder pick-up case.
In the first phase of this project, a standard feeder and load model had been synthesized by capturing the current transients when three-phase voltage measurements (obtained from a local electric utility) are played-in as input to the synthesized model. The comparison between the measured currents and the simulated currents obtained using an electromagnetic transient analysis software (PSCAD) are made at the head of the designed feeder. The synthesized load model has a load composition which includes impedance loads, single-phase induction motor loads and three-phase induction motor loads. The parameters of the motor models are adjusted to obtain a good correspondence between measured three-phase currents and simulated current responses at the head of the feeder when subjected to events under which measurements were obtained on the feeder. These events include faults which occurred upstream of the feeder at a higher voltage level and a feeder pickup event that occurred downstream from the head of the feeder. Two different load compositions have been obtained for this feeder and load model depending on the types of load present in the surrounding area (residential or industrial/commercial).
The second phase of this project examines the impact of the feeder pick-up event on the 69 kV sub-transmission system using the obtained standard feeder and load model. Using the 69 kV network data obtained from a local utility, a sub-transmission network has been built in PSCAD. The main difference between the first and second phase of this project is that no measurements are played-in to the model in the latter case. Instead, the feeder pick-up event at a particular substation is simulated using the reduced equivalent of the 69 kV sub-transmission circuit together with the synthesized three-phase models of the feeder and the loads obtained in the first phase of the project. Using this analysis, it is observed that a good correspondence between the PSCAD simulated values of both three-phase voltages and currents with their corresponding measured responses at the substation is achieved.
ContributorsNekkalapu, Sameer (Author) / Vittal, Vijay (Thesis advisor) / Undrill, John M (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2018
Description
For a (N+1)-bus power system, possibly 2N solutions exists. One of these solutions
is known as the high-voltage (HV) solution or operable solution. The rest of the solutions
are the low-voltage (LV), or large-angle, solutions.
In this report, a recently developed non-iterative algorithm for solving the power-
flow (PF) problem using the holomorphic embedding (HE) method is shown as
being capable of finding the HV solution, while avoiding converging to LV solutions
nearby which is a drawback to all other iterative solutions. The HE method provides a
novel non-iterative procedure to solve the PF problems by eliminating the
non-convergence and initial-estimate dependency issues appeared in the traditional
iterative methods. The detailed implementation of the HE method is discussed in the
report.
While published work focuses mainly on finding the HV PF solution, modified
holomorphically embedded formulations are proposed in this report to find the
LV/large-angle solutions of the PF problem. It is theoretically proven that the proposed
method is guaranteed to find a total number of 2N solutions to the PF problem
and if no solution exists, the algorithm is guaranteed to indicate such by the oscillations
in the maximal analytic continuation of the coefficients of the voltage power series
obtained.
After presenting the derivation of the LV/large-angle formulations for both PQ
and PV buses, numerical tests on the five-, seven- and 14-bus systems are conducted
to find all the solutions of the system of nonlinear PF equations for those systems using
the proposed HE method.
After completing the derivation to find all the PF solutions using the HE method, it
is shown that the proposed HE method can be used to find only the of interest PF solutions
(i.e. type-1 PF solutions with one positive real-part eigenvalue in the Jacobian
matrix), with a proper algorithm developed. The closet unstable equilibrium point
(UEP), one of the type-1 UEP’s, can be obtained by the proposed HE method with
limited dynamic models included.
The numerical performance as well as the robustness of the proposed HE method is
investigated and presented by implementing the algorithm on the problematic cases and
large-scale power system.
is known as the high-voltage (HV) solution or operable solution. The rest of the solutions
are the low-voltage (LV), or large-angle, solutions.
In this report, a recently developed non-iterative algorithm for solving the power-
flow (PF) problem using the holomorphic embedding (HE) method is shown as
being capable of finding the HV solution, while avoiding converging to LV solutions
nearby which is a drawback to all other iterative solutions. The HE method provides a
novel non-iterative procedure to solve the PF problems by eliminating the
non-convergence and initial-estimate dependency issues appeared in the traditional
iterative methods. The detailed implementation of the HE method is discussed in the
report.
While published work focuses mainly on finding the HV PF solution, modified
holomorphically embedded formulations are proposed in this report to find the
LV/large-angle solutions of the PF problem. It is theoretically proven that the proposed
method is guaranteed to find a total number of 2N solutions to the PF problem
and if no solution exists, the algorithm is guaranteed to indicate such by the oscillations
in the maximal analytic continuation of the coefficients of the voltage power series
obtained.
After presenting the derivation of the LV/large-angle formulations for both PQ
and PV buses, numerical tests on the five-, seven- and 14-bus systems are conducted
to find all the solutions of the system of nonlinear PF equations for those systems using
the proposed HE method.
After completing the derivation to find all the PF solutions using the HE method, it
is shown that the proposed HE method can be used to find only the of interest PF solutions
(i.e. type-1 PF solutions with one positive real-part eigenvalue in the Jacobian
matrix), with a proper algorithm developed. The closet unstable equilibrium point
(UEP), one of the type-1 UEP’s, can be obtained by the proposed HE method with
limited dynamic models included.
The numerical performance as well as the robustness of the proposed HE method is
investigated and presented by implementing the algorithm on the problematic cases and
large-scale power system.
ContributorsMine, Yō (Author) / Tylavsky, Daniel (Thesis advisor) / Armbruster, Dieter (Committee member) / Holbert, Keith E. (Committee member) / Sankar, Lalitha (Committee member) / Vittal, Vijay (Committee member) / Undrill, John (Committee member) / Arizona State University (Publisher)
Created2015
Description
Corrective transmission topology control schemes are an essential part of grid operations and are used to improve the reliability of the grid as well as the operational efficiency. However, topology control schemes are frequently established based on the operator's past knowledge of the system as well as other ad-hoc methods. This research presents robust corrective topology control, which is a transmission switching methodology used for system reliability as well as to facilitate renewable integration.
This research presents three topology control (corrective transmission switching) methodologies along with the detailed formulation of robust corrective switching. The robust model can be solved off-line to suggest switching actions that can be used in a dynamic security assessment tool in real-time. The proposed robust topology control algorithm can also generate multiple corrective switching actions for a particular contingency. The solution obtained from the robust topology control algorithm is guaranteed to be feasible for the entire uncertainty set, i.e., a range of system operating states.
Furthermore, this research extends the benefits of robust corrective topology control to renewable resource integration. In recent years, the penetration of renewable resources in electrical power systems has increased. These renewable resources add more complexities to power system operations, due to their intermittent nature. This research presents robust corrective topology control as a congestion management tool to manage power flows and the associated renewable uncertainty. The proposed day-ahead method determines the maximum uncertainty in renewable resources in terms of do-not-exceed limits combined with corrective topology control. The results obtained from the topology control algorithm are tested for system stability and AC feasibility.
The scalability of do-not-exceed limits problem, from a smaller test case to a realistic test case, is also addressed in this research. The do-not-exceed limit problem is simplified by proposing a zonal do-not-exceed limit formulation over a detailed nodal do-not-exceed limit formulation. The simulation results show that the zonal approach is capable of addressing scalability of the do-not-exceed limit problem for a realistic test case.
This research presents three topology control (corrective transmission switching) methodologies along with the detailed formulation of robust corrective switching. The robust model can be solved off-line to suggest switching actions that can be used in a dynamic security assessment tool in real-time. The proposed robust topology control algorithm can also generate multiple corrective switching actions for a particular contingency. The solution obtained from the robust topology control algorithm is guaranteed to be feasible for the entire uncertainty set, i.e., a range of system operating states.
Furthermore, this research extends the benefits of robust corrective topology control to renewable resource integration. In recent years, the penetration of renewable resources in electrical power systems has increased. These renewable resources add more complexities to power system operations, due to their intermittent nature. This research presents robust corrective topology control as a congestion management tool to manage power flows and the associated renewable uncertainty. The proposed day-ahead method determines the maximum uncertainty in renewable resources in terms of do-not-exceed limits combined with corrective topology control. The results obtained from the topology control algorithm are tested for system stability and AC feasibility.
The scalability of do-not-exceed limits problem, from a smaller test case to a realistic test case, is also addressed in this research. The do-not-exceed limit problem is simplified by proposing a zonal do-not-exceed limit formulation over a detailed nodal do-not-exceed limit formulation. The simulation results show that the zonal approach is capable of addressing scalability of the do-not-exceed limit problem for a realistic test case.
ContributorsKorad, Akshay Shashikumar (Author) / Hedman, Kory W (Thesis advisor) / Ayyanar, Raja (Committee member) / Vittal, Vijay (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2015
Description
The standard optimal power flow (OPF) problem is an economic dispatch (ED) problem combined with transmission constraints, which are based on a static topology. However, topology control (TC) has been proposed in the past as a corrective mechanism to relieve overloads and voltage violations. Even though the benefits of TC are presented by several research works in the past, the computational complexity associated with TC has been a major deterrent to its implementation. The proposed work develops heuristics for TC and investigates its potential to improve the computational time for TC for various applications. The objective is to develop computationally light methods to harness the flexibility of the grid to derive maximum benefits to the system in terms of reliability. One of the goals of this research is to develop a tool that will be capable of providing TC actions in a minimal time-frame, which can be readily adopted by the industry for real-time corrective applications.
A DC based heuristic, i.e., a greedy algorithm, is developed and applied to improve the computational time for the TC problem while still maintaining the ability to find quality solutions. In the greedy algorithm, an expression is derived, which indicates the impact on the objective for a marginal change in the state of a transmission line. This expression is used to generate a priority list with potential candidate lines for switching, which may provide huge improvements to the system. The advantage of this method is that it is a fast heuristic as compared to using mixed integer programming (MIP) approach.
Alternatively, AC based heuristics are developed for TC problem and tested on actual data from PJM, ERCOT and TVA. AC based N-1 contingency analysis is performed to identify the contingencies that cause network violations. Simple proximity based heuristics are developed and the fast decoupled power flow is solved iteratively to identify the top five TC actions, which provide reduction in violations. Time domain simulations are performed to ensure that the TC actions do not cause system instability. Simulation results show significant reductions in violations in the system by the application of the TC heuristics.
A DC based heuristic, i.e., a greedy algorithm, is developed and applied to improve the computational time for the TC problem while still maintaining the ability to find quality solutions. In the greedy algorithm, an expression is derived, which indicates the impact on the objective for a marginal change in the state of a transmission line. This expression is used to generate a priority list with potential candidate lines for switching, which may provide huge improvements to the system. The advantage of this method is that it is a fast heuristic as compared to using mixed integer programming (MIP) approach.
Alternatively, AC based heuristics are developed for TC problem and tested on actual data from PJM, ERCOT and TVA. AC based N-1 contingency analysis is performed to identify the contingencies that cause network violations. Simple proximity based heuristics are developed and the fast decoupled power flow is solved iteratively to identify the top five TC actions, which provide reduction in violations. Time domain simulations are performed to ensure that the TC actions do not cause system instability. Simulation results show significant reductions in violations in the system by the application of the TC heuristics.
ContributorsBalasubramanian, Pranavamoorthy (Author) / Hedman, Kory W (Thesis advisor) / Vittal, Vijay (Committee member) / Ayyanar, Raja (Committee member) / Sankar, Lalitha (Committee member) / Arizona State University (Publisher)
Created2016
Description
Two significant trends of recent power system evolution are: (1) increasing installa-tion of dynamic loads and distributed generation resources in distribution systems; (2) large-scale renewable energy integration at the transmission system level. A majority of these devices interface with power systems through power electronic converters. However, existing transient stability (TS) simulators are inadequate to represent the dynamic behavior of these devices accurately. On the other hand, simulating a large system using an electromagnetic transient (EMT) simulator is computationally impractical. EMT-TS hybrid simulation approach is an alternative to address these challenges. Furthermore, to thoroughly analyze the increased interactions among the transmission and distribution systems, an integrated modeling and simulation approach is essential.
The thesis is divided into three parts. The first part focuses on an improved hybrid simulation approach and software development. Compared to the previous work, the pro-posed approach has three salient features: three-sequence TS simulation algorithm, three-phase/three-sequence network equivalencing and flexible switching of the serial and par-allel interaction protocols.
The second part of the thesis concentrates on the applications of the hybrid simula-tion tool. The developed platform is first applied to conduct a detailed fault-induced de-layed voltage recovery (FIDVR) study on the Western Electricity Coordinating Council (WECC) system. This study uncovers that after a normally cleared single line to ground fault at the transmission system could cause air conditioner motors to stall in the distribu-tion systems, and the motor stalling could further propagate to an unfaulted phase under certain conditions. The developed tool is also applied to simulate power systems inter-faced with HVDC systems, including classical HVDC and the new generation voltage source converter (VSC)-HVDC system.
The third part centers on the development of integrated transmission and distribution system simulation and an advanced hybrid simulation algorithm with a capability of switching from hybrid simulation mode to TS simulation. Firstly, a modeling framework suitable for integrated transmission and distribution systems is proposed. Secondly, a power flow algorithm and a diakoptics based dynamic simulation algorithm for the integrated transmission and distribution system are developed. Lastly, the EMT-TS hybrid simulation algorithm is combined with the diakoptics based dynamic simulation algorithm to realize flexible simulation mode switching to increase the simulation efficiency.
The thesis is divided into three parts. The first part focuses on an improved hybrid simulation approach and software development. Compared to the previous work, the pro-posed approach has three salient features: three-sequence TS simulation algorithm, three-phase/three-sequence network equivalencing and flexible switching of the serial and par-allel interaction protocols.
The second part of the thesis concentrates on the applications of the hybrid simula-tion tool. The developed platform is first applied to conduct a detailed fault-induced de-layed voltage recovery (FIDVR) study on the Western Electricity Coordinating Council (WECC) system. This study uncovers that after a normally cleared single line to ground fault at the transmission system could cause air conditioner motors to stall in the distribu-tion systems, and the motor stalling could further propagate to an unfaulted phase under certain conditions. The developed tool is also applied to simulate power systems inter-faced with HVDC systems, including classical HVDC and the new generation voltage source converter (VSC)-HVDC system.
The third part centers on the development of integrated transmission and distribution system simulation and an advanced hybrid simulation algorithm with a capability of switching from hybrid simulation mode to TS simulation. Firstly, a modeling framework suitable for integrated transmission and distribution systems is proposed. Secondly, a power flow algorithm and a diakoptics based dynamic simulation algorithm for the integrated transmission and distribution system are developed. Lastly, the EMT-TS hybrid simulation algorithm is combined with the diakoptics based dynamic simulation algorithm to realize flexible simulation mode switching to increase the simulation efficiency.
ContributorsHuang, Qiuhua (Author) / Vittal, Vijay (Thesis advisor) / Undrill, John M. (Committee member) / Heydt, Gerald T. (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2016