Civil & Environmental Engineering
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Item Planning for Integration of Wind Power Capacity in Power Generation Using Stochastic Optimization(2013) Aliari Kardehdeh, Yashar; Haghani, Ali; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The demand for energy is constantly rising in the world while most of the conventional sources of energy are getting more scarce and expensive. Additionally, environmental issues such as dealing with excessive greenhouse gas emissions (especially CO2) impose further constraints on energy industry all over the globe. Therefore, there is an increasing need for the energy sector to raise the share of clean and renewable sources of energy in power generation. Wind power has specifically attracted large scale investment in recent years since it is ample, widely distributed and has minimal environmental impact. Wind flow and consequently wind-generated power have a stochastic nature. Therefore, wind power should be used in combination with more reliable and fuel-based power generation methods. As a result, it is important to investigate how much capacity from each source of energy should be installed in order to meet electricity demand at the desired reliability level while considering cost and environmental implications. For this purpose, a probabilistic optimization model is proposed where demand and wind power generation are both assumed stochastic. The stochastic model uses a combination of recourse and chance-constrained approaches and is capable of assigning optimal production levels for different sources of energy while considering the possibility of importation, exportation and storage of electricity in the network.Item SUSTAINABLE INFRASTRUCTURE MODELING AND POLICY ANALYSES: CONSTRUCTION, ENERGY AND TRANSPORTATION INDUSTRIES(2013) Avetisyan, Hakob; Gabriel, Steven A.; Miller-Hooks, Elise D.; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Sustainable infrastructure operation assumes consideration of interrelated elements and problems within interacting industries in which the decisions made for one industry may affect those in interrelated industries. Problems related to global climate change and resource scarcity are main concerns for a society trying to build a sustainable infrastructure. These problems are targeted from many perspectives, including government-enforced policies and regulations that call for energy efficiency and transportation efficiency to build a sustainable infrastructure. There is a growing interest among engineers in accounting for sustainability under the impact of climate change policies that limit the amount of pollutants being released from projects and facilities. While specific problems can be targeted by specialists in each industry or field, an optimal sustainable solution will be very difficult to find if considered separately. Despite that directions for improvement are defined, the methods and techniques for reaching these specified goals are not yet well developed. Decision-makers do not have the necessary models to evaluate the impact of proposed carbon policies supporting sustainable infrastructure development. Yet, it is important to analyze the problem in a systematic fashion to find cost-efficient, technically well-designed and constructed and sustainable solutions. In this dissertation, an interdisciplinary approach is used with the aim of analyzing programs geared at reducing emissions and costs, and determining optimal allocation of resources along with profit maximization by developing and employing optimization, regression and game-theoretic models for the construction, energy and transportation industries. These models can be used by national, state, local and private agencies for assessing carbon-mitigation policies and low-cost carbon policy developments. Concepts from integer programming, multi-objective decision-making, bi-level programming, simulation and regression are employed in the development of models to support informed decision-making and policy analyses in the construction, transportation and energy sectors. The models incorporate industry-specific details covering engineering, economic and environmental aspects of sustainable practices. The application of these models to real-world case studies provides insights that will allow defined specific goals to be achieved in a cost-efficient way. Results of case studies were optimal and most importantly not intuitive.Item GOVERNANCE STRATEGIES FOR ENTERPRISE APPLICATION SYSTEM IMPLEMENTATIONS(2013) Ghosh, Saumyendu N.; Skibniewski, Miroslaw J; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Enterprise application system implementations are highly complex implementations that automate several business functions, such as financials, accounting, supply chain, customer services management, human resources management and reporting among others. This study aims at providing an alternative view of organization's enterprise application system (EAS) acceptance. Despite the large body of literature, there are still empirical inquiries to investigate the EAS system implementation from adopters' perspectives and how to identify risks in a multi-stakeholder and dynamic environment. The thesis consists of three essays on various aspects of relationship between enterprise application implementation in a multi-stakeholder environment and project governance. Valid measurement scales for predicting organization's acceptance of enterprise systems are in short supply. The first essay develops and validates new scales for two specific variables, integration and inter-dependency risks. These variables are hypothesized as key determinant for organizational success of enterprise application implementations by mitigating risks involved in a multi-stakeholder environment. A model of organization acceptance of enterprise systems was developed using these two scales and then tested for reliability from a total of 365 users and nine application groups. The measures were validated using ten different direct measures with reliabilities between 0.72 and 0.96. Integration risk was significantly related with perceived ease of use, consultant's product knowledge and training provided to the end users. Inter-dependency risk was significantly correlated with perceived usefulness, consultant's industry and product knowledge. Both integration and inter-dependency risks are significantly related with success of the new enterprise application. This study would benefit project executives by offering valuable managerial insights that enable them to appreciate and improve integration and inter-dependency of stakeholders. Implications for theory and practice are discussed for two sub-groups: that less experienced resources treat risks differently than more experienced resources, and business applications compared to technical enterprise applications. Academic community has not addressed governance of enterprise application projects that involve dynamic environments and how to mitigate integration and inter-dependency risks. In the second essay it is argued that acceptance of the system from end users is not enough? Adopters of new enterprise wide information technology solutions get most benefit when the solution continues to be adaptable when business, environment or other organizational priorities change - therefore making an implementation sustainable. The second essay discussed characteristics of sustainability of enterprise application implementation from organizational perspective. A case study was used to validate the characteristics of sustainability. The thesis sought to demonstrate the causal relationship between the organization's preparedness for sustainability and the emergence of implementation problems. The study extracted insight into the criticality of certain factors and the type of problems making decisions under weak governance situation. The third essay develops determinants for project governance success of enterprise application implementations by mitigating risks in a multi-stakeholder environment. This essay develops and validates new scales for five specific variables. Definitions of five variables were used to develop a model that was presented for content validity and then tested for reliability from a total of 117 project executives globally. The measures were validated with reliabilities between 0.73 and 0.94. Relationships between five measures were broken down to meaningful components and a three tier project governance structure was proposed to mitigate integration and inter-dependency risks in a multi-stakeholder environment.Item Modeling Vehicle Ownership Decisions in Maryland: A Preliminary Stated Preference Survey and Model(2010) Maness, Michael; Cirillo, Cinzia; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In the near future, the culmination of new vehicle technologies, greater competition in the energy markets, and government policies to fight pollution and reduce energy consumption will result in changes in the United States' vehicle marketplace. This project proposes to create a stated preference (SP) survey along with discrete choice models to predict future demand for electric, hybrid, alternative fuel, and gasoline vehicles. The survey is divided into three parts: socioeconomics, revealed preference (RP), and SP sections. The socioeconomics portion asks respondents about themselves and their households. The RP portion asks about household's current vehicles. The SP section presents respondents with various hypothetical scenarios over a future five-year period using one of three game designs. The designs correspond to: changing vehicle technology, fuel pricing and availability, and taxation policy. With these changes to the vehicle marketplace, respondents are asked whether they will keep or replace their current vehicles and if he will purchase a new vehicle and its type. To facilitate the design and administering of the survey, a web survey framework, JULIE, was created specifically for creating stated preference surveys. A preliminary trial of the survey was conducted in September and October 2010 with a sample size of 141 respondents. Using the SP results from this preliminary trial, a multinomial logit model is used to estimate future vehicle ownership by vehicle type. The models show that the survey design allows for estimation of important parameters in vehicle choice.