Matching Items (8)
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- All Subjects: Electric power systems--Reliability.
- Creators: Hedman, Kory W
- Creators: Sieradzki, Karl
- Member of: Theses and Dissertations
Description
Lithium ion batteries are quintessential components of modern life. They are used to power smart devices — phones, tablets, laptops, and are rapidly becoming major elements in the automotive industry. Demand projections for lithium are skyrocketing with production struggling to keep up pace. This drive is due mostly to the rapid adoption of electric vehicles; sales of electric vehicles in 2020 are more than double what they were only a year prior. With such staggering growth it is important to understand how lithium is sourced and what that means for the environment. Will production even be capable of meeting the demand as more industries make use of this valuable element? How will the environmental impact of lithium affect growth? This thesis attempts to answer these questions as the world looks to a decade of rapid growth for lithium ion batteries.
ContributorsMelton, John (Author) / Brian, Jennifer (Thesis director) / Karwat, Darshawn (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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
This work presents research on practices in the day-ahead electric energy market, including replication practices and reliability coordinators used by some market operators to demonstrate the impact these practices have on market outcomes. The practice of constraint relaxations similar to those an Independent System Operator (ISO) might perform in day-ahead market models is implemented. The benefits of these practices are well understood by the industry; however, the implications these practices have on market outcomes and system security have not been thoroughly investigated. By solving a day-ahead market model with and without select constraint relaxations and comparing the resulting market outcomes and possible effects on system security, the effect of these constraint relaxation practices is demonstrated.
Proposed market solutions are often infeasible because constraint relaxation practices and approximations that are incorporated into market models. Therefore, the dispatch solution must be corrected to ensure its feasibility. The practice of correcting the proposed dispatch solution after the market is solved is known as out-of-market corrections (OMCs), defined as any action an operator takes that modifies a proposed day-ahead dispatch solution to ensure operating and reliability requirements. The way in which OMCs affect market outcomes is illustrated through the use of different corrective procedures. The objective of the work presented is to demonstrate the implications of these industry practices and assess the impact these practices have on market outcomes.
Proposed market solutions are often infeasible because constraint relaxation practices and approximations that are incorporated into market models. Therefore, the dispatch solution must be corrected to ensure its feasibility. The practice of correcting the proposed dispatch solution after the market is solved is known as out-of-market corrections (OMCs), defined as any action an operator takes that modifies a proposed day-ahead dispatch solution to ensure operating and reliability requirements. The way in which OMCs affect market outcomes is illustrated through the use of different corrective procedures. The objective of the work presented is to demonstrate the implications of these industry practices and assess the impact these practices have on market outcomes.
ContributorsAl-Abdullah, Yousef Mohammad (Author) / Hedman, Kory W (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald T (Committee member) / Sankar, Lalitha (Committee member) / Arizona State University (Publisher)
Created2016
Description
This research develops heuristics for scheduling electric power production amid uncertainty. Reliability is becoming more difficult to manage due to growing uncertainty from renewable resources. This challenge is compounded by the risk of resource outages, which can occur any time and without warning. Stochastic optimization is a promising tool but remains computationally intractable for large systems. The models used in industry instead schedule for the forecast and withhold generation reserve for scenario response, but they are blind to how this reserve may be constrained by network congestion. This dissertation investigates more effective heuristics to improve economics and reliability in power systems where congestion is a concern.
Two general approaches are developed. Both approximate the effects of recourse decisions without actually solving a stochastic model. The first approach procures more reserve whenever approximate recourse policies stress the transmission network. The second approach procures reserve at prime locations by generalizing the existing practice of reserve disqualification. The latter approach is applied for feasibility and is later extended to limit scenario costs. Testing demonstrates expected cost improvements around 0.5%-1.0% for the IEEE 73-bus test case, which can translate to millions of dollars per year even for modest systems. The heuristics developed in this dissertation perform somewhere between established deterministic and stochastic models: providing an economic benefit over current practices without substantially increasing computational times.
Two general approaches are developed. Both approximate the effects of recourse decisions without actually solving a stochastic model. The first approach procures more reserve whenever approximate recourse policies stress the transmission network. The second approach procures reserve at prime locations by generalizing the existing practice of reserve disqualification. The latter approach is applied for feasibility and is later extended to limit scenario costs. Testing demonstrates expected cost improvements around 0.5%-1.0% for the IEEE 73-bus test case, which can translate to millions of dollars per year even for modest systems. The heuristics developed in this dissertation perform somewhere between established deterministic and stochastic models: providing an economic benefit over current practices without substantially increasing computational times.
ContributorsLyon, Joshua Daniel (Author) / Zhang, Muhong (Thesis advisor) / Hedman, Kory W (Thesis advisor) / Askin, Ronald G. (Committee member) / Mirchandani, Pitu (Committee member) / Arizona State University (Publisher)
Created2015
Description
As global energy demand has dramatically increased and traditional fossil fuels will be depleted in the foreseeable future, clean and unlimited renewable energies are recognized as the future global energy challenge solution. Today, the power grid in U.S. is building more and more renewable energies like wind and solar, while the electric power system faces new challenges from rapid growing percentage of wind and solar. Unlike combustion generators, intermittency and uncertainty are the inherent features of wind and solar. These features bring a big challenge to the stability of modern electric power grid, especially for a small scale power grid with wind and solar. In order to deal with the intermittency and uncertainty of wind and solar, energy storage systems are considered as one solution to mitigate the fluctuation of wind and solar by smoothing their power outputs. For many different types of energy storage systems, this thesis studied the operation of battery energy storage systems (BESS) in power systems and analyzed the benefits of the BESS. Unlike many researchers assuming fixed utilization patterns for BESS and calculating the benefits, this thesis found the BESS utilization patterns and benefits through an investment planning model. Furthermore, a cost is given for utilizing BESS and to find the best way of operating BESS rather than set an upper bound and a lower bound for BESS energy levels. Two planning models are proposed in this thesis and preliminary conclusions are derived from simulation results. This work is organized as below: chapter 1 briefly introduces the background of this research; chapter 2 gives an overview of previous related work in this area; the main work of this thesis is put in chapter 3 and chapter 4 contains the generic BESS model and the investment planning model; the following chapter 5 includes the simulation and results analysis of this research and chapter 6 provides the conclusions from chapter 5.
ContributorsDai, Daihong (Author) / Hedman, Kory W (Thesis advisor) / Zhang, Muhong (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2014
Description
Lithium conducting garnets in the family of Li7La3Zr2O12 (LLZO) are promising lithium conductors for solid-state batteries, due to their high ionic conductivity, thermal stability, and electrochemical stability with metallic lithium. Despite these advantages, LLZO requires a large energy input to synthesize and process. Generally, LLZO is synthesized using solid-state reaction (SSR) from oxide precursors, requiring high reaction temperatures (900-1000 °C) and producing powder with large particle sizes, necessitating high energy milling to improve sinterability. In this dissertation, two classes of advanced synthesis methods – sol-gel polymer-combustion and molten salt synthesis (MSS) – are employed to obtain LLZO submicron powders at lower temperatures. In the first case, nanopowders of LLZO are obtained in a few hours at 700 °C via a novel polymer combustion process, which can be sintered to dense electrolytes possessing ionic conductivity up to 0.67 mS cm-1 at room temperature. However, the limited throughput of this combustion process motivated the use of molten salt synthesis, wherein a salt mixture is used as a high temperature solvent, allowing faster interdiffusion of atomic species than solid-state reactions. A eutectic mixture of LiCl-KCl allows formation of submicrometer undoped, Al-doped, Ga-doped, and Ta-doped LLZO at 900 °C in 4 h, with total ionic conductivities between 0.23-0.46 mS cm-1. By using a highly basic molten salt medium, Ta-doped LLZO (LLZTO) can be obtained at temperatures as low as 550 °C, with an ionic conductivity of 0.61 mS cm-1. The formation temperature can be further reduced by using Ta-doped, La-excess pyrochlore-type lanthanum zirconate (La2Zr2O7, LZO) as a quasi-single-source precursor, which convert to LLZTO as low as 400 °C upon addition of a Li-source. Further, doped pyrochlores can be blended with a Li-source and directly sintered to a relative density up to 94.7% with high conductivity (0.53 mS cm-1). Finally, a propensity for compositional variation in LLZTO powders and sintered ceramics was observed and for the first time explored in detail. By comparing LLZTO obtained from combustion, MSS, and SSR, a correlation between increased elemental inhomogeneity and reduced ionic conductivity is observed. Implications for garnet-based solid-state batteries and strategies to mitigate elemental inhomogeneity are discussed.
ContributorsWeller, Jon Mark (Author) / Chan, Candace K (Thesis advisor) / Crozier, Peter (Committee member) / Sieradzki, Karl (Committee member) / Arizona State University (Publisher)
Created2021
Description
Current Li-ion battery technologies are limited by the low capacities of theelectrode materials and require developments to meet stringent performance demands for
future energy storage devices. Electrode materials that alloy with Li, such as Si, are one
of the most promising alternatives for Li-ion battery anodes due to their high capacities.
Tetrel (Si, Ge, Sn) clathrates are a class of host-guest crystalline structures in which
Tetrel elements form a cage framework and encapsulate metal guest atoms. These
structures can form with defects such as framework/guest atom substitutions and
vacancies which result in a wide design space for tuning materials properties. The goal of
this work is to establish structure property relationships within the context of Li-ion
battery anode applications. The type I Ba 8 Al y Ge 46-y clathrates are investigated for their
electrochemical reactions with Li and show high capacities indicative of alloying
reactions. DFT calculations show that Li insertion into the framework vacancies is
favorable, but the migration barriers are too high for room temperature diffusion. Then,
guest free type I clathrates are investigated for their Li and Na migration barriers. The
results show that Li migration in the clathrate frameworks have low energy barriers (0.1-
0.4 eV) which suggest the possibility for room temperature diffusion. Then, the guest
free, type II Si clathrate (Na 1 Si 136 ) is synthesized and reversible Li insertion into the type
II Si clathrate structure is demonstrated. Based on the reasonable capacity (230 mAh/g),
low reaction voltage (0.30 V) and low volume expansion (0.21 %), the Si clathrate could
be a promising insertion anode for Li-ion batteries. Next, synchrotron X-ray
measurements and pair distribution function (PDF) analysis are used to investigate the
lithiation pathways of Ba 8 Ge 43 , Ba 8 Al 16 Ge 30 , Ba 8 Ga 15 Sn 31 and Na 0.3 Si 136 . The results
show that the Ba-clathrates undergo amorphous phase transformations which is distinct
from their elemental analogues (Ge, Sn) which feature crystalline lithiation pathways.
Based on the high capacities and solid-solution reaction mechanism, guest-filled
clathrates could be promising precursors to form alloying anodes with novel
electrochemical properties. Finally, several high temperature (300-550 °C)
electrochemical synthesis methods for Na-Si and Na-Ge clathrates are demonstrated in a
cell using a Na β’’-alumina solid electrolyte.
ContributorsDopilka, Andrew (Author) / Chan, Candace K (Thesis advisor) / Zhuang, Houlong (Committee member) / Peng, Xihong (Committee member) / Sieradzki, Karl (Committee member) / Arizona State University (Publisher)
Created2021