This dissertation has two major sections. The first section focuses on analyzing objective data gathered from public sources to investigate factors influencing industrial location to Texas. Areas of investigation include (1) where Texas stands--on economic, demographic, sociologic, climatic, and technological terms--in relation to the remaining forty-seven contiguous states; (2) what are the locational characteristics of Texas compared to other states; and (3) what types of industry move to Texas and from where. Regional and state comparisons are also made in terms of factors that can influence business success. The second section is concerned with analyzing survey data gathered from three test groups. The three groups are (1) civic interest groups consisting of Texas mayors, city managers, and chamber of commerce executives; (2) manufacturing executives who have located a new plant in Texas from outside the state since 1978; and (3) out-of-state manufacturing executives who have considered Texas as a possible location but decided not to locate within the state during the period 1978-1983. The major purposes of this section are to determine (1) whether manufacturing executives and Texas community leaders possess different views concerning the relative importance of location factors and factors that are specifically advantageous to the state of Texas, (2) what factors motivate out-of-state manufacturers to select Texas as a location for their plant, and (3) what factors they see as disadvantages. A comparison is made between the findings of the survey data and the objective data. A variety of nonparametric statistical tests are used in testing the hypotheses.

Yes / This article proposes a novel technique for operation of distribution networks with considering active network management (ANM) schemes and demand response (DR) within a joint active and reactive distribution market environment. The objective of the proposed model is to maximize social welfare using market-based joint active and reactive optimal power flow. First, the intermittent behavior of renewable sources (solar irradiance, wind speed) and load demands is modeled through scenario-tree technique. Then, a network frame is recast using mixed-integer linear programming, which is solvable using efficient off-the-shelf branch-and cut solvers. Additionaly, this article explores the impact of wind and solar power penetration on the active and reactive distribution locational prices within the distribution market environment with integration of ANM schemes and DR. A realistic case study (16-bus UK generic medium voltage distribution system) is used to demonstrate the effectiveness of the proposed method. / This work was supported in part by the Ministry of Higher Education Scientific Research in Iraq and in part by British Academy under Grant GCRFNGR3\1541.

Distributed generators (DGs) are proposed as a possible solution to supply economic and reliable electricity to customers. It is adapted to overcome the challenges that are characterized by centralized generation such as transmission and distribution losses, high cost of fossil fuels and environmental damage. This work presents the basic principles of integrating renewable DGs in low voltage distribution networks and particularly focuses on the operation of DG installations and their impacts on active and reactive power. In this thesis, a novel technique that applies the stochastic approach for the operation of distribution networks with considering active network management (ANM) schemes and demand response (DR) within a joint active and reactive distribution market environment is proposed. The projected model is maximized based on social welfare (SW) using market-based joint active and reactive optimal power flow (OPF). The intermittent behaviour of renewable sources (such as solar irradiance and wind speed) and the load demands are modelled through Scenario-Tree technique. The distributed network frame is recast using mixed-integer linear programming (MILP) that is solved by using the GAMS software and then the obtained results are being analysed and discussed. In addition, the impact of wind and solar power penetration on the active and reactive distribution locational prices (D-LMPs) within the distribution market environment is explored in terms of the maximization of SW considering the uncertainty related to solar irradiance, wind speed and load demands. Finally, a realistic case study (16-bus UK generic medium voltage distribution system) is used to demonstrate the effectiveness of the proposed method. Results show that ANM schemes and DR integration lead to an increase in the social welfare and total dispatched active and reactive power and consequently decrease in active and reactive D-LMPs. / Ministry of Higher Education and Scientific Research - Iraq / The selected author's publications, the published versions of which were attached at the end of the thesis, have been removed due to copyright.

No description available.

Foreign Direct Investment (FDI) in the United States, which predominately occurs in the manufacturing sector, remains critically important for a strong regional and local economy, due to the resulting increase in employment, wages, and tax revenue. Traditionally, local economic development strategies have focused on attracting external manufacturing plants or facilities as the primary route to economic growth, through the expansion of the tax base and/or an increase in employment. In comparison, Sustainable Local Economic Development (SLED) emphasizes the establishment of a minimum standard of living for all and an increase in this standard over time; a reduction in the steady growth in inequality among people; a reduction in spatial inequality; and the promotion and encouragement of sustainable resource use and production (Blakely & Leigh, 2010). These essential SLED principles motivate this study, which will seek to develop a better understanding of whether and how FDI contributes to SLED in terms of its spatial patterns and its impact on middle class earnings. By selecting Georgia as a case study area, this research specifically examines whether and how the location of manufacturing FDI has reduced (or increased) spatial inequality at the intra-state and intra-metropolitan levels. It also identifies whether and how manufacturing FDI has reduced (or increased) inequality among people, focusing on its impact on middle class earnings. This study finds a strong spatial concentration of manufacturing FDI employment in metropolitan areas, particularly in a large metropolitan area, at the intra-state spatial pattern analysis. The results of panel regression analysis suggest that presence of agglomeration economies in metropolitan areas has positively influenced the location of manufacturing FDI jobs. The study also finds a suburbanization pattern of manufacturing FDI employment in the intra-metropolitan spatial pattern analysis. This intra-metropolitan suburbanization of FDI in manufacturing jobs is associated with loss of urban industrial land in the central areas within a large metropolitan area. These uneven distribution patterns of manufacturing FDI jobs indicate increased spatial inequality at both intra-state and intra-metropolitan levels, but the implications of this finding are mixed. Using individual earnings data from the American Community Survey Public Use Microdata Sample files, this study also conducts a quantile regression to estimate the earnings distribution effects that a concentration of manufacturing FDI may have on different earnings groups. The findings both from place-of-work and place-of-residence earnings analysis suggest that manufacturing FDI generally has reduced inequality among people. The concentration of manufacturing FDI in a certain area show the largest distribution effects on area workers in the lower earnings group and residents in the middle earnings group.

Le sujet principal de ce texte est une forme très ciblée de ségrégation démographique : la ségrégation selon le type de famille. Cependant, puisque la répartition spatiale des familles mariées, des familles en union libre, des familles monoparentales à chef féminin et de celles à chef masculin ne dépend pas uniquement de leur structure, il faut aussi considérer d'autres facettes de leur identité, notamment leurs caractéristiques socio-économiques et ethnoculturelles. La combinaison de ces facteurs engendre une ségrégation croisée que nous explorons avec les données du recensement de 2006 pour la région métropolitaine de Montréal. Nous utilisons d'abord des indices de ségrégation pour mettre en évidence une ségrégation familiale "brute", puis nous avons recours à des modèles de locational attainment pour déterminer l'effet "net" du type de famille sur le revenu médian du quartier de résidence et sur la distance qui sépare ce quartier du centre-ville. Nous trouvons qu'il existe une interaction importante entre l'appartenance ethnoculturelle, le revenu familial et le type de famille ce qui nous conduit à relativiser les résultats de recherches qui ne prennent pas en compte l'hétérogénéité interne des types de famille. / The main topic of this text is a narrowly defined form of demographic segregation: segregation by family type. However, since the spatial distribution of married, cohabiting, lone-mother, or lone-father families does not depend solely on their structure, we must also consider other aspects of their identity, including their socio-economic and ethno-cultural characteristics. The combination of these factors produces a cross-segregation that we investigate using 2006 census data for the Montreal metropolitan area. We first use segregation indices to highlight a "raw" family type segregation and we then use locational attainment models to determine its "net" effect on the median household income of the neighborhood and on the distance between the neighborhood and the city core. We find a significant interaction between ethnicity, family income and family type which leads us to put in perspective the findings of studies that do not take into account the internal heterogeneity of family types.

Submitted by Maria Aparecida (cidazen@gmail.com) on 2017-08-02T11:31:43Z No. of bitstreams: 1 Felipe Oliveira.pdf: 3179442 bytes, checksum: 0988804a0a58c2aaf337ea2f5034dc42 (MD5) / Made available in DSpace on 2017-08-02T11:31:43Z (GMT). No. of bitstreams: 1 Felipe Oliveira.pdf: 3179442 bytes, checksum: 0988804a0a58c2aaf337ea2f5034dc42 (MD5) Previous issue date: 2017-02-17 / The locational marginal prices (LMPs) are essential financial guidelines for the electricity industry, which orientates most of the projects and deliberations in electrical market environments. In current scenario of the electricity markets, wind power plants and energy storage systems have been revealing itself as feasible and relevant electrical energy supply alternatives. In this work a generic methodology based on artificial intelligence (AI) techniques is formulated and applied to the calculation and decomposition of LMPs of electric power systems (EPS) with the insertion of energy storage systems and wind farms. In the proposed AI-based methodology the optimal power flow (OPF) model, on which the calculation and decomposition of LMP is based, considers the wind behavior profile volatility, the risks of wind power levels previously scheduled, and the energy storage systems operative peculiarities. The proposed AI-based methodology takes into account the mathematical and computational models of the particle swarm optimization (PSO) algorithm. This proposal was properly implemented and applied for the computation and decomposition of LMPs of test systems and considering different operative scenarios involving conventional power plants, wind farms, and energy storage systems. / Os preços marginais locacionais (LMPs – Locational Marginal Prices) consistem em diretrizes financeiras mercadologicamente indispensáveis para a indústria da eletricidade, os quais norteiam grande parte dos projetos e deliberações no âmbito dos mercados elétricos. No panorama vigente dos mercados elétricos, as plantas de geração eólica e os sistemas de armazenamento de energia vêm progressiva e ininterruptamente se revelando alternativas de suprimento de eletricidade cada vez mais relevantes e viáveis. Neste trabalho, é formulada uma metodologia genérica baseada em técnicas de inteligência artificial (IA) cuja aplicação tem o objetivo de computar e decompor os LMPs associados às barras constituintes de um sistema elétrico de potência (SEP) integrado por geradores convencionais, plantas de geração eólica e por sistemas de armazenamento de energia. Na metodologia IA proposta, o modelo de fluxo de potência ótimo (FPO) sobre o qual se alicerça o cômputo e a decomposição dos LMPs associados às barras de um SEP, leva em consideração a volatilidade inerente ao perfil comportamental dos ventos, os riscos associados à assunção de níveis previamente programados de potência proveniente da geração eólica e as peculiaridades operativas concernentes aos sistemas de armazenamento de energia. Adotando-se os modelos matemáticos e computacionais dos algoritmos de otimização por enxame de partículas (PSO – Particle Swarm Optimization), a metodologia IA proposta foi devidamente implementada e aplicada na aquisição e decomposição dos LMPs associados às barras constituintes de sistemas-testes submetidos a diferentes cenários operativos envolvendo centrais de geração convencionais, plantas de geração eólica e sistemas de armazenamento de energia.

The growth of electricity markets around the world has introduced new challenges in which one of the challenges is the uncertainty that has become a structural element in this new environment. Market players have to deal with it to guarantee the appropriate power system planning and operation as well as its own economical liquidity. Under an open access environment in a deregulated power system, transmission management holds a vital role in supporting transactions between suppliers and customers. Nevertheless, a transmission network has some constraints that should be addressed in order to ensure sufficient control to maintain the security level of a power system while maximizing market efficiency. The most obvious drawback of transmission constraints is a congestion problem that becomes an obstacle of perfect competition among the market participants since it can influence spot market pricing. The system becomes congested when the supplier and customer agree to produce and consume a particular amount of electric power, but this can cause the transmission network to exceed its thermal limits. Congestion can cause the market players to exercise market power that can result in price volatility beyond the marginal costs. Thus, it is important to manage congestion efficiently in the design of a power market. One mechanism that has direct correlation with transmission management is market clearing price (MCP). Under an open access environment, energy prices throughout the network will be different and measured based on transmission constraint and network losses. When network losses are ignored and there is no congestion on the transmission lines, the power price will be the same at all nodes. This is known as uniform marginal pricing (UMP). However, as the power flow violates transmission constraints, redispatching generating units is required and this will cause the price at every node to vary. This phenomenon is defined as locational marginal pricing (LMP). Therefore, the market clearing price has a strong relationship with transmission management, which is needed to be assessed in order to obtain an efficient and transparent price but satisfying all market participants. This project investigates an alternative solution to the dispatch mechanism, and then formulates a new Locational Marginal Price scheme using optimization technique that may well control congestion as the main issue. The model will vary and be improved, to be distilled into energy price, congestion revenue, cost of losses, as well as transmission usage tariff. The objective of the project is to support developing standard market design (SMD) in managing transmission systems which promotes economic efficiency, lowers delivered energy costs, maintains power system reliability and mitigates exercising market power.

Le sujet principal de ce texte est une forme très ciblée de ségrégation démographique : la ségrégation selon le type de famille. Cependant, puisque la répartition spatiale des familles mariées, des familles en union libre, des familles monoparentales à chef féminin et de celles à chef masculin ne dépend pas uniquement de leur structure, il faut aussi considérer d'autres facettes de leur identité, notamment leurs caractéristiques socio-économiques et ethnoculturelles. La combinaison de ces facteurs engendre une ségrégation croisée que nous explorons avec les données du recensement de 2006 pour la région métropolitaine de Montréal. Nous utilisons d'abord des indices de ségrégation pour mettre en évidence une ségrégation familiale "brute", puis nous avons recours à des modèles de locational attainment pour déterminer l'effet "net" du type de famille sur le revenu médian du quartier de résidence et sur la distance qui sépare ce quartier du centre-ville. Nous trouvons qu'il existe une interaction importante entre l'appartenance ethnoculturelle, le revenu familial et le type de famille ce qui nous conduit à relativiser les résultats de recherches qui ne prennent pas en compte l'hétérogénéité interne des types de famille. / The main topic of this text is a narrowly defined form of demographic segregation: segregation by family type. However, since the spatial distribution of married, cohabiting, lone-mother, or lone-father families does not depend solely on their structure, we must also consider other aspects of their identity, including their socio-economic and ethno-cultural characteristics. The combination of these factors produces a cross-segregation that we investigate using 2006 census data for the Montreal metropolitan area. We first use segregation indices to highlight a "raw" family type segregation and we then use locational attainment models to determine its "net" effect on the median household income of the neighborhood and on the distance between the neighborhood and the city core. We find a significant interaction between ethnicity, family income and family type which leads us to put in perspective the findings of studies that do not take into account the internal heterogeneity of family types.

The growth of electricity markets around the world has introduced new challenges in which one of the challenges is the uncertainty that has become a structural element in this new environment. Market players have to deal with it to guarantee the appropriate power system planning and operation as well as its own economical liquidity. Under an open access environment in a deregulated power system, transmission management holds a vital role in supporting transactions between suppliers and customers. Nevertheless, a transmission network has some constraints that should be addressed in order to ensure sufficient control to maintain the security level of a power system while maximizing market efficiency. The most obvious drawback of transmission constraints is a congestion problem that becomes an obstacle of perfect competition among the market participants since it can influence spot market pricing. The system becomes congested when the supplier and customer agree to produce and consume a particular amount of electric power, but this can cause the transmission network to exceed its thermal limits. Congestion can cause the market players to exercise market power that can result in price volatility beyond the marginal costs. Thus, it is important to manage congestion efficiently in the design of a power market. One mechanism that has direct correlation with transmission management is market clearing price (MCP). Under an open access environment, energy prices throughout the network will be different and measured based on transmission constraint and network losses. When network losses are ignored and there is no congestion on the transmission lines, the power price will be the same at all nodes. This is known as uniform marginal pricing (UMP). However, as the power flow violates transmission constraints, redispatching generating units is required and this will cause the price at every node to vary. This phenomenon is defined as locational marginal pricing (LMP). Therefore, the market clearing price has a strong relationship with transmission management, which is needed to be assessed in order to obtain an efficient and transparent price but satisfying all market participants. This project investigates an alternative solution to the dispatch mechanism, and then formulates a new Locational Marginal Price scheme using optimization technique that may well control congestion as the main issue. The model will vary and be improved, to be distilled into energy price, congestion revenue, cost of losses, as well as transmission usage tariff. The objective of the project is to support developing standard market design (SMD) in managing transmission systems which promotes economic efficiency, lowers delivered energy costs, maintains power system reliability and mitigates exercising market power.