Matching Items (7)
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- All Subjects: Power Systems
- Creators: Ayyanar, Raja
- Member of: ASU Electronic Theses and Dissertations
Description
As renewable energy becomes more prevalent in transmission and distribution systems, it is vital to understand the uncertainty and variability that accompany these resources. Microgrids have the potential to mitigate the effects of resource uncertainty. With the ability to exist in either an islanded mode or maintain connections with the main-grid, a microgrid can increase reliability, defer T&D; infrastructure and effectively utilize demand response. This study presents a co-optimization framework for a microgrid with solar photovoltaic generation, emergency generation, and transmission switching. Today unit commitment models ensure reliability with deterministic criteria, which are either insufficient to ensure reliability or can degrade economic efficiency for a microgrid that uses a large penetration of variable renewable resources. A stochastic mixed integer linear program for day-ahead unit commitment is proposed to account for uncertainty inherent in PV generation. The model incorporates the ability to trade energy and ancillary services with the main-grid, including the designation of firm and non-firm imports, which captures the ability to allow for reserve sharing between the two systems. In order to manage the computational complexities, a Benders' decomposition approach is utilized. The commitment schedule was validated with solar scenario analysis, i.e., Monte-Carlo simulations are conducted to test the proposed dispatch solution. For this test case, there were few deviations to power imports, 0.007% of solar was curtailed, no load shedding occurred in the main-grid, and 1.70% load shedding occurred in the microgrid.
ContributorsHytowitz, Robin Broder (Author) / Hedman, Kory W (Thesis advisor) / Heydt, Gerald T (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
Description
Due to restructuring and open access to the transmission system, modern electric power systems are being operated closer to their operational limits. Additionally, the secure operational limits of modern power systems have become increasingly difficult to evaluate as the scale of the network and the number of transactions between utilities increase. To account for these challenges associated with the rapid expansion of electric power systems, dynamic equivalents have been widely applied for the purpose of reducing the computational effort of simulation-based transient security assessment. Dynamic equivalents are commonly developed using a coherency-based approach in which a retained area and an external area are first demarcated. Then the coherent generators in the external area are aggregated and replaced by equivalenced models, followed by network reduction and load aggregation. In this process, an improperly defined retained area can result in detrimental impacts on the effectiveness of the equivalents in preserving the dynamic characteristics of the original unreduced system. In this dissertation, a comprehensive approach has been proposed to determine an appropriate retained area boundary by including the critical generators in the external area that are tightly coupled with the initial retained area. Further-more, a systematic approach has also been investigated to efficiently predict the variation in generator slow coherency behavior when the system operating condition is subject to change. Based on this determination, the critical generators in the external area that are tightly coherent with the generators in the initial retained area are retained, resulting in a new retained area boundary. Finally, a novel hybrid dynamic equivalent, consisting of both a coherency-based equivalent and an artificial neural network (ANN)-based equivalent, has been proposed and analyzed. The ANN-based equivalent complements the coherency-based equivalent at all the retained area boundary buses, and it is designed to compensate for the discrepancy between the full system and the conventional coherency-based equivalent. The approaches developed have been validated on a large portion of the Western Electricity Coordinating Council (WECC) system and on a test case including a significant portion of the eastern interconnection.
ContributorsMa, Feng (Author) / Vittal, Vijay (Thesis advisor) / Tylavsky, Daniel (Committee member) / Heydt, Gerald (Committee member) / Si, Jennie (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2011
Description
The Smart Grid initiative describes the collaborative effort to modernize the U.S. electric power infrastructure. Modernization efforts incorporate digital data and information technology to effectuate control, enhance reliability, encourage small customer sited distributed generation (DG), and better utilize assets. The Smart Grid environment is envisioned to include distributed generation, flexible and controllable loads, bidirectional communications using smart meters and other technologies. Sensory technology may be utilized as a tool that enhances operation including operation of the distribution system. Addressing this point, a distribution system state estimation algorithm is developed in this thesis. The state estimation algorithm developed here utilizes distribution system modeling techniques to calculate a vector of state variables for a given set of measurements. Measurements include active and reactive power flows, voltage and current magnitudes, phasor voltages with magnitude and angle information. The state estimator is envisioned as a tool embedded in distribution substation computers as part of distribution management systems (DMS); the estimator acts as a supervisory layer for a number of applications including automation (DA), energy management, control and switching. The distribution system state estimator is developed in full three-phase detail, and the effect of mutual coupling and single-phase laterals and loads on the solution is calculated. The network model comprises a full three-phase admittance matrix and a subset of equations that relates measurements to system states. Network equations and variables are represented in rectangular form. Thus a linear calculation procedure may be employed. When initialized to the vector of measured quantities and approximated non-metered load values, the calculation procedure is non-iterative. This dissertation presents background information used to develop the state estimation algorithm, considerations for distribution system modeling, and the formulation of the state estimator. Estimator performance for various power system test beds is investigated. Sample applications of the estimator to Smart Grid systems are presented. Applications include monitoring, enabling demand response (DR), voltage unbalance mitigation, and enhancing voltage control. Illustrations of these applications are shown. Also, examples of enhanced reliability and restoration using a sensory based automation infrastructure are shown.
ContributorsHaughton, Daniel Andrew (Author) / Heydt, Gerald T (Thesis advisor) / Vittal, Vijay (Committee member) / Ayyanar, Raja (Committee member) / Hedman, Kory W (Committee member) / Arizona State University (Publisher)
Created2012
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
Transmission voltages worldwide are increasing to accommodate higher power transfer from power generators to load centers. Insulator dimensions cannot increase linearly with the voltage, as supporting structures become too tall and heavy. Therefore, it is necessary to optimize the insulator design considering all operating conditions including dry, wet and contaminated. In order to design insulators suitably, a better understanding of the insulator flashover is required, as it is a serious issue regarding the safe operation of power systems. However, it is not always feasible to conduct field and laboratory studies due to limited time and money.
The desire to accurately predict the performance of insulator flashovers requires mathematical models. Dynamic models are more appropriate than static models in terms of the instantaneous variation of arc parameters. In this dissertation, a dynamic model including conditions for arc dynamics, arc re-ignition and arc motion with AC supply is first developed.
For an AC power source, it is important to consider the equivalent shunt capacitance in addition to the short circuit current when evaluating pollution test results. By including the power source in dynamic models, the effects of source parameters on the leakage current waveform, the voltage drop and the flashover voltage were systematically investigated. It has been observed that for the same insulator under the same pollution level, there is a large difference among these flashover performances in high voltage laboratories and real power systems. Source strength is believed to be responsible for this discrepancy. Investigations of test source strength were conducted in this work in order to study its impact on different types of insulators with a variety of geometries.
Traditional deterministic models which have been developed so far can only predict whether an insulator would flashover or withstand. In practice, insulator flashover is a statistical process, given that both pollution severity and flashover voltage are probabilistic variables. A probability approach to predict the insulator flashover likelihood is presented based on the newly developed dynamic model.
The desire to accurately predict the performance of insulator flashovers requires mathematical models. Dynamic models are more appropriate than static models in terms of the instantaneous variation of arc parameters. In this dissertation, a dynamic model including conditions for arc dynamics, arc re-ignition and arc motion with AC supply is first developed.
For an AC power source, it is important to consider the equivalent shunt capacitance in addition to the short circuit current when evaluating pollution test results. By including the power source in dynamic models, the effects of source parameters on the leakage current waveform, the voltage drop and the flashover voltage were systematically investigated. It has been observed that for the same insulator under the same pollution level, there is a large difference among these flashover performances in high voltage laboratories and real power systems. Source strength is believed to be responsible for this discrepancy. Investigations of test source strength were conducted in this work in order to study its impact on different types of insulators with a variety of geometries.
Traditional deterministic models which have been developed so far can only predict whether an insulator would flashover or withstand. In practice, insulator flashover is a statistical process, given that both pollution severity and flashover voltage are probabilistic variables. A probability approach to predict the insulator flashover likelihood is presented based on the newly developed dynamic model.
ContributorsHe, Li (Author) / Gorur, Ravi S (Thesis advisor) / Karady, George K (Committee member) / Ayyanar, Raja (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2016
Description
Alternate sources of energy such as wind, solar photovoltaic and fuel cells are coupled to the power grid with the help of solid state converters. Continued deregulation of the power sector coupled with favorable government incentives has resulted in the rapid growth of renewable energy sources connected to the distribution system at a voltage level of 34.5kV or below. Of late, many utilities are also investing in these alternate sources of energy with the point of interconnection with the power grid being at the transmission level. These converter interfaced generation along with their associated control have the ability to provide the advantage of fast control of frequency, voltage, active, and reactive power. However, their ability to provide stability in a large system is yet to be investigated in detail. This is the primary objective of this research.
In the future, along with an increase in the percentage of converter interfaced renewable energy sources connected to the transmission network, there exists a possibility of even connecting synchronous machines to the grid through converters. Thus, all sources of energy can be expected to be coupled to the grid through converters. The control and operation of such a grid will be unlike anything that has been encountered till now. In this dissertation, the operation and behavior of such a grid will be investigated. The first step in such an analysis will be to build an accurate and simple mathematical model to represent the corresponding components in commercial software. Once this bridge has been crossed, conventional machines will be replaced with their solid state interfaced counterparts in a phased manner. At each stage, attention will be devoted to the control of these sources and also on the stability performance of the large power system.
This dissertation addresses various concerns regarding the control and operation of a futuristic power grid. In addition, this dissertation also aims to address the issue of whether a requirement may arise to redefine operational reliability criteria based on the results obtained.
In the future, along with an increase in the percentage of converter interfaced renewable energy sources connected to the transmission network, there exists a possibility of even connecting synchronous machines to the grid through converters. Thus, all sources of energy can be expected to be coupled to the grid through converters. The control and operation of such a grid will be unlike anything that has been encountered till now. In this dissertation, the operation and behavior of such a grid will be investigated. The first step in such an analysis will be to build an accurate and simple mathematical model to represent the corresponding components in commercial software. Once this bridge has been crossed, conventional machines will be replaced with their solid state interfaced counterparts in a phased manner. At each stage, attention will be devoted to the control of these sources and also on the stability performance of the large power system.
This dissertation addresses various concerns regarding the control and operation of a futuristic power grid. In addition, this dissertation also aims to address the issue of whether a requirement may arise to redefine operational reliability criteria based on the results obtained.
ContributorsRamasubramanian, Deepak (Author) / Vittal, Vijay (Thesis advisor) / Undrill, John (Committee member) / Ayyanar, Raja (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2017
Description
The broad deployment of time-synchronized continuous point-on-wave (CPoW) modules will enable electric power utilities to gain unprecedented insight into the behavior of their power system assets, loads, and distributed renewable generation in real time. By increasing the available level of detail visible to operators, serious fault events such as wildfire-inducing arc flashes, safety-jeopardizing transformer failures, and equipment-damaging power quality decline can be mitigated in a data-driven, systematic manner. In this research project, a time-synchronized micro-scale CPoW module was designed, constructed, and characterized. This inductively powered CPoW module, which operates wirelessly by using the current flowing through a typical distribution conductor as its power source and a wireless data link for communication, has been configured to measure instantaneous line current at high frequency (nominally 3,000 samples per second) with 12-bit resolution. The design process for this module is detailed in this study, including background research, individual block design and testing, printed circuit board (PCB) design, and final characterization of the system.
To validate the performance of this module, tests of power requirements, measurement accuracy, battery life, susceptibility to electromagnetic interference, and fault detection performance were performed. The results indicate that the design under investigation will satisfy the technical and physical constraints required for bulk deployment in an actual distribution network after manufacturing optimizations. After the test results were summarized, the future research and development activities needed to finalize this design for commercial deployment were identified and discussed.
ContributorsPatterson, John (Author) / Pal, Anamitra (Thesis advisor) / Ogras, Umit (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2021