O principal objetivo deste estudo é propor uma nova metodologia para lidar com o problema de Planejamento da Expansão de Redes de Transmissão de Energia Elétrica com Múltiplos Cenários de Geração (PERTEEG). Com a metodologia proposta neste trabalho almeja-se construir planos de expansão de redes de transmissão de energia elétrica que sejam capazes de, no menor custo de investimento possível, satisfazer às novas exigências dos sistemas elétricos modernos, tais como construção de redes de transmissão livres de congestionamento e robustas à incerteza em relação aos cenários de geração futuros. Através de estudos realizados na literatura do problema, verificou-se que novos modelos e metodologias de abordagem do PERTEEG se fazem necessários. Ao se modelar o PERTEEG visando construir redes de transmissão que contornem as incertezas em relação aos cenários de geração futuros e concomitantemente minimizar o custo de investimento para a expansão do sistema, o planejador se depara com um problema de otimização multiobjetivo. Existem na literatura da pesquisa operacional diversos algoritmos que visam lidar com problemas multiobjetivos. Nesta tese, foram aplicados dois desses algoritmos: Nondominated Sorting Genetic Algorithms-II (NSGA-II) e SPEA2: Strength Pareto Evolutionary Algorithm (SPEA2). Em primeira análise, se destacou uma das maiores dificuldade de lidar com o PERTEEG, a saber, o esforço computacional elevado. Por isso, vislumbrou-se que uma possível solução para contornar esta dificuldade esteja na computação paralela. Para se confirmar esta suspeita, nesta tese foram implementadas versões paralelas dos algoritmos sequenciais testados. A qualidade das soluções encontradas pelos algoritmos foram bastante superiores às soluções encontradas pelos algoritmos sequenciais. Neste trabalho também será mostrado que as soluções ótimas clássicas considerando somente o objetivo de m´mínimo custo são incapazes de atender às novas necessidades dos sistemas elétricos de potência. Testes computacionais foram realizados e analisados neste trabalho. Considerando as metodologias conhecidas na literatura para medição da qualidade das soluções encontradas por algoritmos multiobjetivo, se pode afirmar de que a proposta de abordagem do problema de PERTEEG pode ser viável tanto do ponto de vista de engenharia como do ponto de vista da computação matemática. / The main objective of this study is to propose a new methodology to deal with the long-term transmission system expansion planning with multiple generation dispatch scenarios problem (TEP-MDG). With the methodology proposed in this thesis we aim to build expansion plans with minimum investment cost and also capable of meeting the new demands of modern electrical systems, such as uncertainty about the future generation scenarios and congestion in the transmission systems. By modeling the TEP-MDG aiming to build transmission networks that circumvent the uncertainties regarding the future generation scenarios and simultaneously minimize the cost of investment for transmission networks expansion, the planner faces a multiobjective optimization problem. One can find various algorithms that aim to deal with multiobjective problems in the literature of operations research. In this thesis, we apply two of these algorithms: Nondominated Sorting Genetic Algorithms-II (NSGA-II) and SPEA2: Strength Pareto Evolutionary Algorithm (SPEA2). In a first analysis, we have found that the most critical issue with the TEP-MOG is the high computational demand. Therefore, in order to circumvent this difficulty we have implemented parallel versions of the sequential algorithms tested. In performed tests, the parallel algorithms have found solutions of superior quality than the solutions found by the sequential algorithms. In this thesis we also show that optimal solutions considering only the classical least cost objective are unable to meet the electric power systems new demands. Tests have been performed and analyzed in this work. By considering the methods known in the literature convinced to measure the quality of solutions found by multiobjective algorithms, we concluded that the proposed approach to TEP-MDG may be feasible from the point of view of both engineering and computational mathematics.

Neste trabalho realizamos um estudo do Despacho de Potência Ativa AC, o qual é uma estratégia de alocação da geração de potência entre as usinas de um sistema. Para isto, obtivemos dados teóricos, a partir de levantamento bibliográfico, que explicitaram os conceitos de Despacho Ativo. Fundamentamos, metodologicamente, nossa pesquisa no Método da Função Lagrangeana Aumentada. O sistema de equações resultantes das condições de otimalidade foram resolvidos pelo Método de Newton Modificado. Apresentamos os resultados de estudos de casos acadêmicos para a validação e verificação da eficiência da abordagem proposta. Os resultados indicaram uma coerência com as perspectivas reais de contribuição na resolução do Despacho Ótimo de Potência Ativa AC. / In this work we accomplished a study of the AC Active Power Dispatch, which is a strategy of distribution of the power generation among the plants of a system. For this, we obtained theoretical data, starting from bibliographical investigation, that elucidated the concepts of Active Dispatch. We based our research in the Method of the Augmented Lagrangian Function. The equation system originated of the optimal conditions was solved for Modified Newton\'s Method. We presented the results of studies of academic cases for the validation and verification of the efficiency of the proposal approach. The results indicated a coherence with the real perspectives of contribution in the resolution of the AC Active Optimal Power Dispatch.

Shipment Consolidation (SCL) is a logistics strategy that combines two or more orders or shipments so that a larger quantity can be dispatched on the same vehicle to the same market region. This dissertation aims to emphasize the importance and substantial cost saving opportunities that come with SCL in a logistics supply chain, by offering new models or by improving on the current body of literature. Our research revolves around "three main axes" in SCL: Single-Item Shipment Consolidation (SISCL), Multi-Item Shipment Consolidation (MISCL), and Pricing and Shipment Consolidation. We investigate those topics by employing various Operations Research concepts or techniques such as renewal theory, dynamic optimization, and simulation. In SISCL, we focus on analytical models, when the orders arrive randomly. First, we examine the conditions under which an SCL program enables positive savings. Then, in addition to the current SCL policies used in practice and studied in the literature, i.e. Quantity-Policy (Q-P), Time-Policy (T-P) and Hybrid Policy (H-P), we introduce a new one that we call the Controlled Dispatch Policy (CD-P). Moreover, we provide a cost-based comparison of those policies. We show that the Q-P yields the lowest cost per order amongst the others, yet with the highest randomness in dispatch times. On the other hand, we also show that, between the service-level dependent policies (i.e. the CD-P, H-P and T-P), H-P provides the lowest cost per order, while CD-P turns out to be more flexible and responsive to dispatch times, again with a lower cost than the T-P. In MISCL, we construct dispatch decision rules. We employ a myopic analysis, and show that it is optimal, when costs and the order-arrival processes are dependent on the type of items. In a dynamic setting, we apply the concept of time-varying probability to integrate the dispatching and load planning decisions. For the most common dispatch objectives such as cost per order, cost per unit time or cost per unit weight, we use simulation and observe that the variabilities in both cost and the optimal consolidation cycle are smaller for the objective of cost per unit weight. Finally on our third axis, we study the joint optimization of pricing and time-based SCL policy. We do this for a price- and time-sensitive logistics market, both for common carriage (transport by a public, for-hire trucking company) and private carriage (employing one's own fleet of trucks). The main motivation for introducing pricing in SCL decisions stems from the fact that transportation is a service, and naturally demand is affected by price. Suitable pricing decisions may influence the order-arrival rates, enabling extra savings. Those savings emanate from two sources: Scale economies (in private carriage) or discount economies (in common carriage) that come with SCL, and additional revenue generated by employing an appropriate pricing scheme. Throughout the dissertation, we offer numerical examples and as many managerial insights as possible. Suggestions for future research are offered.

Shipment Consolidation (SCL) is a logistics strategy that combines two or more orders or shipments so that a larger quantity can be dispatched on the same vehicle to the same market region. This dissertation aims to emphasize the importance and substantial cost saving opportunities that come with SCL in a logistics supply chain, by offering new models or by improving on the current body of literature. Our research revolves around "three main axes" in SCL: Single-Item Shipment Consolidation (SISCL), Multi-Item Shipment Consolidation (MISCL), and Pricing and Shipment Consolidation. We investigate those topics by employing various Operations Research concepts or techniques such as renewal theory, dynamic optimization, and simulation. In SISCL, we focus on analytical models, when the orders arrive randomly. First, we examine the conditions under which an SCL program enables positive savings. Then, in addition to the current SCL policies used in practice and studied in the literature, i.e. Quantity-Policy (Q-P), Time-Policy (T-P) and Hybrid Policy (H-P), we introduce a new one that we call the Controlled Dispatch Policy (CD-P). Moreover, we provide a cost-based comparison of those policies. We show that the Q-P yields the lowest cost per order amongst the others, yet with the highest randomness in dispatch times. On the other hand, we also show that, between the service-level dependent policies (i.e. the CD-P, H-P and T-P), H-P provides the lowest cost per order, while CD-P turns out to be more flexible and responsive to dispatch times, again with a lower cost than the T-P. In MISCL, we construct dispatch decision rules. We employ a myopic analysis, and show that it is optimal, when costs and the order-arrival processes are dependent on the type of items. In a dynamic setting, we apply the concept of time-varying probability to integrate the dispatching and load planning decisions. For the most common dispatch objectives such as cost per order, cost per unit time or cost per unit weight, we use simulation and observe that the variabilities in both cost and the optimal consolidation cycle are smaller for the objective of cost per unit weight. Finally on our third axis, we study the joint optimization of pricing and time-based SCL policy. We do this for a price- and time-sensitive logistics market, both for common carriage (transport by a public, for-hire trucking company) and private carriage (employing one's own fleet of trucks). The main motivation for introducing pricing in SCL decisions stems from the fact that transportation is a service, and naturally demand is affected by price. Suitable pricing decisions may influence the order-arrival rates, enabling extra savings. Those savings emanate from two sources: Scale economies (in private carriage) or discount economies (in common carriage) that come with SCL, and additional revenue generated by employing an appropriate pricing scheme. Throughout the dissertation, we offer numerical examples and as many managerial insights as possible. Suggestions for future research are offered.

Abstract This dissertation presents a new algorithm by integrating evolutionary programming (EP), tabu search (TS) and quadratic programming (QP), named the evolutionary-tabu quadratic programming (ETQ) method, to solve the nonconvex economic dispatch problem (NED). This problem involves the economic dispatch with valve-point effects (EDVP), economic dispatch with piecewise quadratic cost function (EDPQ), and economic dispatch with prohibited operating zones (EDPO). EDPV, EDPQ and EDPO are similar problems when ETQ was employed. The problem was solved in two phases, the cost-curve-selection subproblem, and the typical ED solving subproblem. The first phase was resolved by using a hybrid EP and TS, and the second phase by QP. In the solving process, EP with repairing strategy was used to generate feasible solutions, TS was used to prevent prematurity, and QP was used to enhance the performance. Numerical results show that the proposed method is more effective than other previously developed evolutionary computation algorithms.

A power system with multiple interconnected areas needs to be operated coordinately for the purposes of the system reliability and economic operation, although each area has its own ISO under the market environment. In consolidation of different areas under a common grid coordinator, analysis of a power system becomes more computationally demanding. Furthermore, the analysis becomes more challenging because each area cannot obtain the network operating or economic data of other areas. This dissertation investigates decomposition algorithms for multi-area power system transfer capability analysis and economic dispatch analysis. All of the proposed algorithms assume that areas do not share their network operating and economic information among themselves, while they are willing to cooperate via a central coordinator for system wide analyses. The first proposed algorithm is based on power transfer distribution factors (PTDFs). A quadratic approximation, developed for the nonlinear PTDFs, is used to update tie-line power flows calculated by Repeated Power Flow (RPF). These tie-line power flows are then treated as injections in the TTC calculation of each area, as the central entity coordinates these results to determine the final system-wide TTC value. The second proposed algorithm is based on REI-type network equivalents. It uses the Continuation Power Flow (CPF) as the computational tool and, thus, the problem of voltage stability is considered in TTC studies. Each area uses REI equivalents of external areas to compute its TTC via the CPF. The choice and updating procedure for the continuation parameter employed by the CPF is implemented in a distributed but coordinated manner. The third proposed algorithm is based on inexact penalty functions. The traditional OPF is treated as the optimization problems with global variables. Quadratic penalty functions are used to relax the compatible constraints between the global variables and the local variables. The solution is proposed to be implemented by using a two-level computational architecture. All of the proposed algorithms are verified by numerical comparisons between the integrated and proposed decomposition algorithms. The proposed algorithms lead to potential gains in the computational efficiency with limited data exchanges among areas.

「勞動派遣」在國外早已訂定相關之立法規範，日本於一九八五年制定勞動派遣法，德國、美國對勞動派遣亦制定特別的法律與相關規範，在丹麥所有關勞動派遣的禁止規定也於一九九○年廢止，由這些先進國家的例子，可知制定勞動派遣法為世界立法潮流所趨。勞動派遣與傳統僱用之契約關係，最大不同之處在於勞動派遣關係下之派遣勞工，受僱於派遣機構，雙方成立勞動契約(employment contract)關係，但派遣勞工卻在該勞動契約當事人以外之第三人要派機構處提供勞務，接受該第三人之指揮監督與管理，形成「僱用」與「使用」分離之現象。由於勞動派遣型態為勞動市場既存狀態，雖在現行法制上有一定規範，惟此種三角關係的勞動型，態涉及「要派機構」、「派遣機構」及「派遣勞工」三方當事人的互動，在現行勞動法規皆以傳統勞動關係為主要規範標的下，無法完整規範勞動派遣所衍生的問題，而造成許多勞資之間的糾紛。 我國經濟部商業司於一九九九年十月通過核准企業可登記其營業內容為「人力派遣業」，但是，國內目前卻仍未對勞動派遣制定相關法令。相較於國際勞工組織已針對勞動派遣制定相關公約及建議書，德國、日本等先進國家以制定專法之方式來規範「勞動派遣」，我國目前卻對此問題尚無任何明確的法律規範，為保障派遣勞工之就業權益，給予勞資雙方明確之依循方向，落實就業安全之理念與作法，建立符合我國國情需要之勞動派遣法制，為刻不容緩之目標。因此本研究藉由參考比較美國、德國、日本等國之勞動派遣相關規範及法制，以了解各國實施勞動派遣之狀況，並分析各國勞動派遣法制之優缺點，及可能產生之問題進行分析，藉此提供我國未來於制定勞動派遣法時之參考方向。最後，針對我國目前勞動派遣草案進行分析，並提出相關立法建議，以期建構符合我國國情之勞動派遣法制，創造勞資雙贏之局面。 / The standards about legalization of dispatched employment had been enacted in the foreign countries. Legislation of dispatched employment had been enacted in Japan in 1985; besides Germany and America also made special laws and regulations about dispatched employment. All about the forbidden regulations also had been abolished in Denmark. From those examples of developed countries above, we can understand that the legalization about dispatched employment is forced by the world trend. The difference between dispatched employment and typical employment is that the dispatched employees are employed by the dispatched work agency but they provide service to the user enterprise. Because the triangular arrangement of dispatched employment concerns the interaction among user enterprise, dispatched work agency and dispatched workers, so there are many disputations between employees and employers. Although the Department of Commerce of MOEA in Taiwan permitted the enterprise to register their operations as “Employee dispatching industry” in October 1999, there were still no relevant laws about dispatched employment. The International Labor Organization had made the conventions and recommendations about dispatched employment; moreover Germany and Japan also made the relevant laws. In order to protect the rights of dispatched labors, the law-making which correspond with our national conditions is of great urgency. By comparing of the legalization about dispatched employment of America, Germany and Japan, we want to know the practical conditions and analyze the advantages and disadvantages of those countries above. By doing so, we can provide our country with the referential aspects in making the law about the dispatched employment in the future. Finally, in order to establish the legalization about dispatched employment corresponded with our society and to create a win-win situation of employee and employer, we analyze the existent Dispatched Employment Bill in Taiwan and bring forward certain relative lawmaking proposals.

A new Markov chain based energy storage model to evaluate the power supply availability of microgrids with renewable energy generation for critical loads is proposed. Since critical loads require above-average availability to ensure reliable operation during extreme events, e.g., natural disasters, using renewable energy generation has been considered to diversify sources. However, the low availability and high variability of renewable energy sources bring a challenge in achieving the required availability for critical loads. Hence, adding energy storage systems to renewable energy generation becomes vital for ensuring the generation of enough power during natural disasters. Although adding energy storage systems would instantaneously increase power supply availability, there is another critical aspect that should be carefully considered; energy storage sizing to meet certain availability must be taken into account in order to avoid oversizing or undersizing capacity, which are two undesirable conditions leading to inadequate availability or increased system cost, respectively. This dissertation proposes to develop a power supply availability framework for renewable energy generation in a given location and to suggest the optimal size of energy storage for the required availability to power critical loads. In particular, a new Markov chain based energy storage model is presented in order to model energy states in energy storage system, which provides an understanding of the nature of charge and discharge rates for energy storage that affect the system's power output. Practical applications of the model are exemplified using electrical vehicles with photovoltaic roofs. Moreover, the minimal cut sets method is used to analyze the effects of microgrid architectures on availability characteristics of the microgrid power supply in the presence of renewable energy sources and energy storage. In addition, design considerations for energy storage power electronics interfaces and a comparison of various energy storage methods are also presented. / text

Combined heat and power (CHP) is a technology that decreases total fuel consumption and related greenhouse gas emissions by producing both electricity and useful thermal energy from a single energy source. In the industrial and commercial sectors, a typical CHP site relies upon the electricity distribution network for significant periods, i.e., for purchasing power from the grid during periods of high demand or when off-peak electricity tariffs are available. On the other hand, in some cases, a CHP plant is allowed to sell surplus power to the grid during on-peak hours when electricity prices are highest while all operating constraints and local demands are satisfied. Therefore, if the plant is connected with the external grid and allowed to participate in open energy markets in the future, it could yield significant economic benefits by selling/buying power depending on market conditions. This is achieved by solving the power system generation scheduling problem using mathematical programming. In this work, we present the application of mixed-integer nonlinear programming (MINLP) approach for scheduling of a CHP plant in the day-ahead wholesale energy markets. This work employs first principles models to describe the nonlinear dynamics of a CHP plant and its individual components (gas and steam turbines, heat recovery steam generators, and auxiliary boilers). The MINLP framework includes practical constraints such as minimum/maximum power output and steam flow restrictions, minimum up/down times, start-up and shut-down procedures, and fuel limits. We provide case studies involving the Hal C. Weaver power plant complex at the University of Texas at Austin to demonstrate this methodology. The results show that the optimized operating strategies can yield substantial net incomes from electricity sales and purchases. This work also highlights the application of a nonlinear model predictive control scheme to a heavy-duty gas turbine power plant for frequency and temperature control. This scheme is compared to a classical PID/logic based control scheme and is found to provide superior output responses with smaller settling times and less oscillatory behavior in response to disturbances in electric loads. / text

The intricate concepts of ad-hoc polymorphism and overloading permeate the field of programming languages despite their somewhat nebulous definitions. With the perspective afforded by the state of the art, object-oriented Fortress programming language, this thesis presents a contemporary account of ad-hoc polymorphism and overloading in theory and in practice. Common language constructs are reinterpreted with a new emphasis on overloading as a key facility. Furthermore, concrete problems with overloading in Fortress, encountered during the author's experience in the development of the language, are presented with an emphasis on the ad hoc nature of their solutions. / text