Matching Items (9)
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- All Subjects: engineering
- Genre: Doctoral Dissertation
- Creators: Badger, William
- Member of: Theses and Dissertations
- Status: Published
Description
Transmission expansion planning (TEP) is a complex decision making process that requires comprehensive analysis to determine the time, location, and number of electric power transmission facilities that are needed in the future power grid. This dissertation investigates the topic of solving TEP problems for large power systems. The dissertation can be divided into two parts. The first part of this dissertation focuses on developing a more accurate network model for TEP study. First, a mixed-integer linear programming (MILP) based TEP model is proposed for solving multi-stage TEP problems. Compared with previous work, the proposed approach reduces the number of variables and constraints needed and improves the computational efficiency significantly. Second, the AC power flow model is applied to TEP models. Relaxations and reformulations are proposed to make the AC model based TEP problem solvable. Third, a convexified AC network model is proposed for TEP studies with reactive power and off-nominal bus voltage magnitudes included in the model. A MILP-based loss model and its relaxations are also investigated. The second part of this dissertation investigates the uncertainty modeling issues in the TEP problem. A two-stage stochastic TEP model is proposed and decomposition algorithms based on the L-shaped method and progressive hedging (PH) are developed to solve the stochastic model. Results indicate that the stochastic TEP model can give a more accurate estimation of the annual operating cost as compared to the deterministic TEP model which focuses only on the peak load.
ContributorsZhang, Hui (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald T (Thesis advisor) / Mittelmann, Hans D (Committee member) / Hedman, Kory W (Committee member) / Arizona State University (Publisher)
Created2013
Description
The goal of this research study was to identify the competencies the Project Manager (PM) will need to respond to the challenges the construction industry faces in 2022 and beyond. The study revealed twenty-one emerging challenges for construction PMs grouped into four primary disruptive forces: workforce demographics, globalization, rapidly evolving technology, and changing organizational structures. The future PM will respond to these emerging challenges using a combination of fourteen competencies. The competencies are grouped into four categories: technical (multi-disciplined, practical understanding of technology), management (keen business insight, understanding of project management, knowledge network building, continuous risk monitoring), cognitive (complex decisions making, emotional maturity, effective communication), and leadership (leveraging diverse thinking, building relationships, engaging others, mentoring, building trust). Popular data collection methods used in project management research, such as surveys and interviews, have received criticism about the differences between stated responses to questions, what respondents say they will do, and revealed preferences, what they actually practice in the workplace. Rather than relying on surveys, this research study utilized information generated from games and exercises bundled into one-day training seminars conducted by Construction Industry Institute (CII) companies for current and upcoming generations of PMs. Educational games and exercises provide participants with the opportunity to apply classroom learning and workplace experience to resolve issues presented in real-world scenarios, providing responses that are more closely aligned with the actual decisions and activities occurring on projects. The future competencies were identified by combining results of the literature review with information from the games and exercises through an iterative cycle of data mining, analysis, and consolidation review sessions with CII members. This competency forecast will be used as a basis for company recruiting and to create tools for professional development programs and project management education at the university level. In addition to the competency forecast, the research identified simulation games and exercises as components of a project management development program in a classroom setting. An instrument that links the emerging challenges with the fourteen competencies and learning tools that facilitate the mastering of these competencies has also been developed.
ContributorsKing, Cynthia Joyce (Author) / Wiezel, Avi (Thesis advisor) / Badger, William (Committee member) / Sullivan, Kenneth (Committee member) / Arizona State University (Publisher)
Created2012
Description
Owner organizations in the architecture, engineering, and construction (AEC) industry are presented with a wide variety of project delivery approaches. Implementation of these approaches, while enticing due to their potential to save money, reduce schedule delays, or improve quality, is extremely difficult to accomplish and requires a concerted change management effort. Research in the field of organizational behavior cautions that perhaps more than half of all organizational change efforts fail to accomplish their intended objectives. This study utilizes an action research approach to analyze change message delivery within owner organizations, model owner project team readiness and adoption of change, and identify the most frequently encountered types of resistance from lead project members. The analysis methodology included Spearman's rank order correlation, variable selection testing via three methods of hierarchical linear regression, relative weight analysis, and one-way ANOVA. Key findings from this study include recommendations for communicating the change message within owner organizations, empirical validation of critical predictors for change readiness and change adoption among project teams, and identification of the most frequently encountered resistive behaviors within change implementation in the AEC industry. A key contribution of this research is the recommendation of change management strategies for use by change practitioners.
ContributorsLines, Brian (Author) / Sullivan, Kenneth (Thesis advisor) / Wiezel, Avi (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2014
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
Within the vast area of study in Organizational Change lays the industrial application of Change Management, which includes the understanding of both resisters and facilitators to organizational change. This dissertation presents an approach of gauging levels of change as it relates to both external and internal organization factors. The arena of such a test is given through the introduction of the same initiative change model, which attempts to improve transparency and accountability, across six different organizations where the varying results of change are measured. The change model itself consists of an interdisciplinary approach which emphasizes education of advanced organizational measurement techniques as fundamental drivers of converging change. The observations are documented in the real-time observed cased studies of six organizations as they progressed through the change process. This research also introduces a scaled metric for determining preliminary levels of change and endeavors to test both internal and external, or environmental, factors of change. A key contribution to the work is the analysis between both observed and surveyed data where a grounded theory analysis is used to help answer the question of what are factors of change in organizations. This work is considered to be foundational in real-time observational studies but has a promise for future additional contributions which would further elaborate on the phenomenon of prescribed organizational change.
ContributorsStone, Brian (Author) / Sullivan, Kenneth T. (Thesis advisor) / Verdini, William (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2012
Description
Recent studies have identified that contractors in the Saudi construction industry are not the main party that cause risks as owners and other parties have the major share of causing risks. However, with the identification that risks out of contractors’ control are a leading cause of low performance, there is a lack of efficient risk mitigation practices in Saudi to manage these risks. The main aim of this dissertation is to assess the current practices applied by contractors to minimize risk out of their control and develop a risk mitigation model to manage these risks. The main objectives of the study are: investigating the risks that are out of contractors’ control, assessing the contractors’ current risk mitigation and performance measurement practices, and finally developing and validating a risk mitigation model to minimize risks out of contractors’ control and measure performance of involved project parties. To achieve the study aim, a mixed methodological approach was adopted. Theoretical approaches were utilized to review previous research and to develop a conceptual risk mitigation framework followed by a practical approach that is considered with collecting data from contractors. The quantitative method was mainly used to meet the study objectives through distributing a survey in the form of a questionnaire. As a consolidation of the study findings, the top ranked risks that are out of contractors’ control were identified. Furthermore, the results identified that the contractors’ current risk management and performance measurement practices are not effective in minimizing projects risks caused by other parties and ineffective in measuring performance of all parties. The developed model focuses on increasing accountability of project parties through mitigating project parties’ activities and risks with measuring the deviations and identifying sources of deviations. Transparency is utilized in the model through sharing weekly updates of the activities and risks combined with updated information of performance measurements of all project parties. The study results showed that project risks can be minimized and projects’ performance can be increased if contractors shift their focus using the developed model from only managing their own activities and risks to managing all project parties’ activities and risks.
ContributorsAlgahtany, Mohammed (Author) / Sullivan, Kenneth (Thesis advisor) / Kashiwagi, Dean (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2018
Description
The success or failure of projects is not determined only by procedures, tasks, and technologies, but also by the project team and its effectiveness. In order to lead project teams towards successful outcomes, project managers must maintain high quality relationships in the workplace. When looking at employees’ relationships in the workplace, Social Exchange Theory introduces two types of exchanges: employee-organization and leader-member exchanges. While both types of exchanges focus exclusively on the employee’s longitudinal relationships, the interpersonal relationships among the team members are usually overlooked.
This research presents the results of a quantitative study of the interpersonal relationships of 327 project managers and assistant project managers in their workplace. Specifically, the study investigates if the quality of the relationship with particular stakeholders, such as one’s immediate supervisor (boss), peers, or subordinates, drives the individual’s quality of the relationship with other stakeholders.
Contrary to the expectations, in strictly hierarchical organizations (one direct supervisor), there is no significant correlation between the quality of relationships with the boss and the overall quality of the individual’s relationships. However, in the case of matrix organizations (two or three bosses), there are significant correlations between several variables such as the quality of the relationship, perceived importance and the time spent with each stakeholder, as well the inclination of the participant towards leadership actions. The driving relationship in matrix organizations is the one with “the most important peer”.
This research presents the results of a quantitative study of the interpersonal relationships of 327 project managers and assistant project managers in their workplace. Specifically, the study investigates if the quality of the relationship with particular stakeholders, such as one’s immediate supervisor (boss), peers, or subordinates, drives the individual’s quality of the relationship with other stakeholders.
Contrary to the expectations, in strictly hierarchical organizations (one direct supervisor), there is no significant correlation between the quality of relationships with the boss and the overall quality of the individual’s relationships. However, in the case of matrix organizations (two or three bosses), there are significant correlations between several variables such as the quality of the relationship, perceived importance and the time spent with each stakeholder, as well the inclination of the participant towards leadership actions. The driving relationship in matrix organizations is the one with “the most important peer”.
ContributorsK. Jamali, M. Hossein (Author) / Wiezel, Avi (Thesis advisor) / Sullivan, Kenneth T. (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2019
Description
With growing concern regarding environmental issues and the need for a more sustainable grid, power systems have seen a fast expansion of renewable resources in the last decade. The uncertainty and variability of renewable resources has posed new challenges on system operators. Due to its energy-shifting and fast-ramping capabilities, energy storage (ES) has been considered as an attractive solution to alleviate the increased renewable uncertainty and variability.
In this dissertation, stochastic optimization is utilized to evaluate the benefit of bulk energy storage to facilitate the integration of high levels of renewable resources in transmission systems. A cost-benefit analysis is performed to study the cost-effectiveness of energy storage. A two-step approach is developed to analyze the effectiveness of using energy storage to provide ancillary services. Results show that as renewable penetrations increase, energy storage can effectively compensate for the variability and uncertainty in renewable energy and has increasing benefits to the system.
With increased renewable penetrations, enhanced dispatch models are needed to efficiently operate energy storage. As existing approaches do not fully utilize the flexibility of energy storage, two approaches are developed in this dissertation to improve the operational strategy of energy storage. The first approach is developed using stochastic programming techniques. A stochastic unit commitment (UC) is solved to obtain schedules for energy storage with different renewable scenarios. Operating policies are then constructed using the solutions from the stochastic UC to efficiently operate energy storage across multiple time periods. The second approach is a policy function approach. By incorporating an offline analysis stage prior to the actual operating stage, the patterns between the system operating conditions and the optimal actions for energy storage are identified using a data mining model. The obtained data mining model is then used in real-time to provide enhancement to a deterministic economic dispatch model and improve the utilization of energy storage. Results show that the policy function approach outperforms a traditional approach where a schedule determined and fixed at a prior look-ahead stage is used. The policy function approach is also shown to have minimal added computational difficulty to the real-time market.
In this dissertation, stochastic optimization is utilized to evaluate the benefit of bulk energy storage to facilitate the integration of high levels of renewable resources in transmission systems. A cost-benefit analysis is performed to study the cost-effectiveness of energy storage. A two-step approach is developed to analyze the effectiveness of using energy storage to provide ancillary services. Results show that as renewable penetrations increase, energy storage can effectively compensate for the variability and uncertainty in renewable energy and has increasing benefits to the system.
With increased renewable penetrations, enhanced dispatch models are needed to efficiently operate energy storage. As existing approaches do not fully utilize the flexibility of energy storage, two approaches are developed in this dissertation to improve the operational strategy of energy storage. The first approach is developed using stochastic programming techniques. A stochastic unit commitment (UC) is solved to obtain schedules for energy storage with different renewable scenarios. Operating policies are then constructed using the solutions from the stochastic UC to efficiently operate energy storage across multiple time periods. The second approach is a policy function approach. By incorporating an offline analysis stage prior to the actual operating stage, the patterns between the system operating conditions and the optimal actions for energy storage are identified using a data mining model. The obtained data mining model is then used in real-time to provide enhancement to a deterministic economic dispatch model and improve the utilization of energy storage. Results show that the policy function approach outperforms a traditional approach where a schedule determined and fixed at a prior look-ahead stage is used. The policy function approach is also shown to have minimal added computational difficulty to the real-time market.
ContributorsLi, Nan (Author) / Hedman, Kory W (Thesis advisor) / Tylavksy, Daniel J (Committee member) / Heydt, Gerald T (Committee member) / Sankar, Lalitha (Committee member) / Arizona State University (Publisher)
Created2016
Description
The objective of the study was to examine the impact construction document deficiencies have on heavy/civil low-bid infrastructure projects. It encompasses the expertise of 202 heavy/civil construction professionals comprised of contactors and public project owners. The study was designed to determine the frequency and timing of when a contractor discovers construction document deficiencies on heavy/civil low bid projects. The information was correlated with further study data of when a contractor ultimately reports the discovered construction document deficiencies to the public project owner. This research data was compiled and analyzed to determine if contractors are withholding construction document deficiencies from public owners until after the project contract has been executed. The withholding of document deficiencies can benefit contractors by resulting in additional owner incurred costs and potential justification for project time extensions. As a result, further research was required to examine the impact construction document deficiencies have on project cost and schedule. Based on the study findings, it has led to the development of a Contractor Document Review Assessment. The Contractor Document Review Assessment is a risk mitigation device in which contractors and public project owners can identify construction document deficiencies on heavy/civil low-bid construction projects before the project contract has been executed.
ContributorsPesek, Anthony Edward (Author) / Sullivan, Kenneth (Thesis advisor) / Badger, William (Committee member) / Bingham, Evan (Committee member) / Arizona State University (Publisher)
Created2017