Concentrated solar power (CSP) is a fast-growing technology for electricity production. With mirrors (heliostats) irradiation of the sun is concentrated onto a receiver run through by a heat transfer fluid (HTF). The fluid by that reaches high temperatures and is used to drive a steam turbine for electricity production. A CSP power plant is most often coupled with an energy storage unit, where the HTF is stored before it is dispatched and used to generate electricity. Electricity is most often sold at an open market with a fluctuating spot-prices. It is therefore of high importance to generate and sell the electricity at the highest paid hours, increasingly important also since the governmental support mechanisms aimed to support renewable energy production is faded out since the technology is starting to be seen as mature enough to compete by itself on the market. A solar power plant thus has an operational protocol determining when energy is dispatched, and electricity is sold. These protocols are often pre-defined which means an optimal production is not achieved since irradiation and electricity selling price vary. In this master thesis, an optimization algorithm for electricity sales is designed (in MATLAB). The optimization algorithm is designed by for a given timeframe solve an optimization problem where the objective is maximized revenue from electricity sales from the solar power plant. The function takes into consideration hourly varying electricity spot price, hourly varying solar field efficiency, energy flows in the solar power plant, start-up costs (from on to off) plus conditions for the logic governing the operational modes. Two regular pre-defined protocols were designed to be able to compare performance in a solar power plant with the optimized dispatch protocol. These three operational protocols were evaluated in three different markets; one with fluctuating spot price, one regulated market of three fixed price levels and one in spot market but with zero-prices during sunny hours. It was found that the optimized dispatch protocol gave both bigger electricity production and revenue in all markets, but with biggest differences in the spot markets. To evaluate in what type of powerplant the optimizer performs best, a parametric analysis was made where size of storage and power block, the time-horizon of optimizer and the cost of start-up were varied. For size of storage and power block it was found that revenue increased with increased size, but only up to the level where the optimizer can dispatch at optimal hours. After that there is no increase in revenue. Increased time horizon gives increased revenue since it then has more information. With a 24-hour time horizon, morning price-peaks will be missed for example. To change start-up costs makes the power plant less flexible and with fewer cycles, without affect income much. / Koncentrerad solkraft (CSP) är en snabbt växande teknologi för elektricitets-produktion. Med speglar (heliostater) koncentreras solstrålar på en mottagare som genomflödas av en värmetransporteringsvätska. Denna uppnår därmed höga temperaturer vilket används för att driva en ångturbin för att generera el. Ett CSP kraftverk är oftast kopplat till en energilagringstank, där värmelagringsvätskan lagras innan den används för att generera el. El säljs i de flesta fall på en öppen elmarknad, där spotpriset fluktuerar. Det är därför av stor vikt att generera elen och sälja den vid de timmar med högst elpris, vilket också är av ökande betydelse då supportmekanismerna för att finansiellt stödja förnybar energiproduktion används i allt mindre grad för denna teknologi då den börjar anses mogen att konkurrera utan. Ett solkraftverk har således ett driftsprotokoll som bestämmer när el ska genereras. Dessa protokoll är oftast förutbestämda, vilket innebär att en optimal produktion inte fås då exempelvis elspotpriset och solinstrålningen varierar. I detta examensarbete har en optimeringsalgoritm för elförsäljning designats (i MATLAB). Optimeringsscriptet är designat genom att för en given tidsperiod lösa ett optimeringsproblem där objektivet är maximerad vinst från såld elektricitet från solkraftverket. Funktionen tar hänsyn till timvist varierande elpris, timvist varierande solfältseffektivitet, energiflöden i solkraftverket, kostnader för uppstart (on till off) samt villkor för att logiskt styra de olika driftlägena. För att jämföra prestanda hos ett solkraftverk med det optimerade driftsprotokollet skapades även två traditionella förutbestämda driftprotokoll. Dessa tre driftsstrategier utvärderades i tre olika marknader, en med ett varierande el-spotpris, en i en reglerad elmarknad med tre prisnivåer och en i en marknad med spotpris men noll-pris under de soliga timmarna. Det fanns att det optimerade driftsprotokollet gav både större elproduktion och högre vinst i alla marknader, men störst skillnad fanns i de öppna spotprismarknaderna. För att undersöka i vilket slags kraftverk som protokollet levererar mest förbättring i gjordes en parametrisk analys där storlek på lagringstank och generator varierades, samt optimerarens tidshorisont och kostnad för uppstart. För lagringstank och generator fanns att vinst ökar med ökande storlek upp tills den storlek optimeraren har möjlighet att fördela produktion på dyrast timmar. Ökande storlek efter det ger inte ökad vinst. Ökande tidshorisont ger ökande vinst eftersom optimeraren då har mer information. Att ändra uppstartkostnaden gör att solkraftverket uppträder mindre flexibelt och har färre cykler, dock utan så stor påverkan på inkomst.

An analysis of a transport operator´s job description My degree work is centred on the problems of a transport operator´s job in a forwarding agency. The introduction provides an explanation of a term of "dispatch service" and explains why logistics is so important in transport. Then there is a description of the transport development after 1990 and the changes transport had to undergo in the time of globalization. The main part of the work deals with the operator´s working procedure from an offer to a demand, an order and other actions to the final realization. A model example is given to represent an actual transporting process. The work also states conditions under which transport is executed, for example payment terms and terms of delivery. Next chapters outline the way of calculation, give a detailed description of collecting service (which is implemented within the bounds of CS Expres system) and of storing problems including the introduction of bar codes in stores and possibilities of logistic service extension. The conclusion is focused on the firm developing strategy.

The objective of an Energy Control Center (ECC) is to ensure secure and economic operation of power system. The challenge to optimize power system operation, while maintaining system security and quality of power supply to customers, is increasing. Growing demand without matching expansion of generation and transmission facilities and more tightly interconnected power systems contribute to the increased complexity of system operation. Rising costs due to inflation and increased environmental concerns has made transmission, as well as generation systems to be operated closure to design limits, with smaller safety margins and hence greater exposure to unsatisfactory operating conditions following a disturbance. Investigations of recent blackouts indicate that the root cause of most of these major power system disturbances is voltage collapse. Information gathered and preliminary analysis, from the most recent blackout incident in North America on 14th August 2003, is pointing the finger on voltage instability due to some unexpected contingency. In this incident, reports indicate that approximately 50 million people were affected interruption from continuous supply for more than 15 hours. Most of the incidents are related to heavily stressed system where large amounts of real and reactive power are transported over long transmission lines while appropriate real and reactive power resources are not available to maintain normal system conditions. Hence, the problem of voltage stability and voltage collapse has become a major concern in power system planning and operation. Reliable operation of large scale electric power networks requires that system voltages and currents stay within design limits. Operation beyond those limits can lead to equipment failures and blackouts. In the last few decades, the problem of reactive power control for improving economy and security of power system operation has received much attention. Generally, the load bus voltages can be maintained within their permissible limits by reallocating reactive power generations in the system. This can be achieved by adjusting transformer taps, generator voltages, and switchable Ar sources. In addition, the system losses can be minimized via redistribution of reactive power in the system. Therefore, the problem of the reactive power dispatch can be optimized to improve the voltage profile and minimize the system losses as well. The Instability in power system could be relieved or at least minimized with the help of most recent developed devices called Flexible AC Transmission System (FACTS) controllers. The use of Flexible AC Transmission System (FACTS) controllers in power transmission system have led to many applications of these controllers not only to improve the stability of the existing power network resources but also provide operating flexibility to the power system. In the past, transmission systems were owned by regulated, vertically integrated utility companies. They have been designed and operated so that conditions in close proximity to security boundaries are not frequently encountered. However, in the new open access environment, operating conditions tend to be much closer to security boundaries, as transmission use is increasing in sudden and unpredictable directions. Transmission unbundling, coupled with other regulatory requirements, has made new transmission facility construction more difficult. In fact, there are numerous technical challenges emerging from the new market structure. There is an acute need for research work in the new market structure, especially in the areas of voltage security, reactive power support and congestion management. In the last few decades more attention was paid to optimal reactive power dispatch. Since the problem of reactive power optimization is non-linear in nature, nonlinear programming methods have been used to solve it. These methods work quite well for small power systems but may develop convergence problems as system size increases. Linear programming techniques with iterative schemes are certainly the most promising tools for solving these types of problems. The thesis presents efficient algorithms with different objectives for reactive power optimization. The approach adopted is an iterative scheme with successive power-flow analysis using decoupled technique, formulation and solution of the linear-programmingproblem with only upper-bound limits on the state variables. Further the thesispresents critical analysis of the three following objectives, Viz., •Minimization of the sum of the squares of the voltage deviations (Vdesired) •Minimization of sum of the squares of the voltage stability L indices (Vstability) •Minimization of real power losses (Ploss) Voltage stability problems normally occur in heavily stressed systems. While the disturbance leading to voltage collapse may be initiated by a variety of causes, the underlying problem is an inherent weakness in the power system. The factors contributing to voltage collapse are the generator reactive power /voltage control limits, load characteristics, characteristics of reactive compensation devices, and the action of the voltage control devices such as transformer On Load Tap Changers (OLTCs). Power system experiences abnormal operating conditions following a disturbance, and subsequently a reduction in the EHV level voltages at load centers will be reflected on the distribution system. The OLTCs of distribution transformers would restore distribution voltages. With each tap change operation, the MW and MVAR loading on the EHV lines would increase, thereby causing great voltage drops in EHV levels and increasing the losses. As a result, with each tap changing operation, the reactive output of generators throughout the system would increase gradually and the generators may hit their reactive power capability limits, causing voltage instability problems. Thus, the operation of certain OLTCs has a significant influence on voltage instability under some operating conditions. These transformers can be made manual to avoid possible voltage instability due to their operation during heavy load conditions. Tap blocking, based on local measurement of high voltage side of load tap changers, is a common practice of power utilities to prevent voltage collapse. The great advantage of this method is that it can be easily implemented, but does not guarantee voltage stability. So a proper approach for identification of critical OLTC s based on voltage stability criteria is essential to guide the operator in ECC, which has been proposed in this thesis. It discusses the effect of OLTCs with different objectives of reactive power dispatch and proposes a technique to identify critical OLTCs based on voltage stability criteria. The fast development of power electronics based on new and powerful semiconductor devices has led to innovative technologies, such as High Voltage DC transmission (HVDC) and Flexible AC Transmission System (FACTS), which can be applied in transmission and distribution systems. The technical and economicalBenefits of these technologies represent an alternative to the application in AC systems. Deregulation in the power industry and opening of the market for delivery of cheaper energy to the customers is creating additional requirements for the operation of power systems. HVDC and FACTS offer major advantages in meeting these requirements. .A method for co-ordinated optimum allocation of reactive power in AC/DC power systems by including FACTS controller UPFC, with an objective of minimization of the sum of the squares of the voltage deviations of all the load buses has been proposed in this thesis. The study results show that under contingency conditions, the presence of FACTS controllers has considerable impact on over all system voltage stability and also on power loss minimization.minimization of the sum of the squares of the voltage deviations of all the load buses has been proposed in this thesis. The study results show that under contingency conditions, the presence of FACTS controllers has considerable impact on over all system voltage stability and also on power loss minimization. As power systems grow in their size and interconnections, their complexity increases. For secure operation and control of power systems under normal and contingency conditions, it is essential to provide solutions in real time to the operator in ECC. For real time control of power systems, the conventional algorithmic software available in ECC are found to be inadequate as they are computationally very intensive and not organized to guide the operator during contingency conditions. Artificial Intelligence (AI) techniques such as, Expert systems, Neural Networks, Fuzzy systems are emerging decision support system tools which give fast, though approximate, but acceptable right solutions in real time as they mostly use symbolic processing with a minimum number of numeric computations. The solution thus obtained can be used as a guide by the operator in ECC for power system control. Optimum real and reactive power dispatch play an important role in the day-to-day operation of power systems. Existing conventional Optimal Power Flow (OPF) methods use all of the controls in solving the optimization problem. The operators can not move so many control devices within a reasonable time. In this context an algorithm using fuzzy-expert approach has been proposed in this thesis to curtail the number of control actions, in order to realize real time objectives in voltage/reactive power control. The technique is formulated using membership functions of linguistic variables such as voltage deviations at all the load buses and the voltage deviation sensitivity to control variables. Voltage deviations and controlling variables are translated into fuzzy set notations to formulate the relation between voltage deviations and controlling ability of controlling devices. Control variables considered are switchable VAR compensators, OLTC transformers and generator excitations. A fuzzy rule based system is formed to select the critical controllers, their movement direction and step size. Results show that the proposed approach is effective for improving voltage security to acceptable levels with fewer numbers of controllers. So, under emergency conditions the operator need not move all the controllers to different settings and the solution obtained is fast with significant speedups. Hence, the proposed method has the potential to be integrated for on-line implementation in energy management systems to achieve the goals of secure power system operation. In a deregulated electricity market, it may not be always possible to dispatch all of the contracted power transactions due to congestion of the transmission corridors. System operators try to manage congestion, which otherwise increases the cost of the electricity and also threatens the system security and stability. An approach for alleviation of network over loads in the day-to-day operation of power systems under deregulated environment is presented in this thesis. The control used for overload alleviation is real power generation rescheduling based on Relative Electrical Distance (RED) concept. The method estimates the relative location of load nodes with respect to the generator nodes. The contribution of each generator for a particular over loaded line is first identified , then based on RED concept the desired proportions of generations for the desired overload relieving is obtained, so that the system will have minimum transmission losses and more stability margins with respect to voltage profiles, bus angles and better transmission tariff. The results obtained reveal that the proposed method is not only effective for overload relieving but also reduces the system power loss and improves the voltage stability margin. The presented concepts are better suited for finding the utilization of resources generation/load and network by various players involved in the day-to-day operation of the system under normal and contingency conditions. This will help in finding the contribution by various players involved in the congestion management and the deviations can be used for proper tariff purposes. Suitable computer programs have been developed based on the algorithms presented in various chapters and thoroughly tested. Studies have been carried out on various equivalent systems of practical real life Indian power networks and also on some standard IEEE systems under simulated conditions. Results obtained on a modified IEEE 30 bus system, IEEE 39 bus New England system and four Indian power networks of EHV 24 bus real life equivalent power network, an equivalent of 36 bus EHV Indian western grid, Uttar Pradesh 96 bus AC/DC system and 205 Bus real life interconnected grid system of Indian southern region are presented for illustration purposes.

This dissertation focuses on selected issues in regard to the mathematical modeling of electricity markets. In a first step the interrelations of electric power market modeling are highlighted a crossroad between operations research, applied economics, and engineering. In a second step the development of a large-scale continental European economic engineering model named ELMOD is described and the model is applied to the issue of wind integration. It is concluded that enabling the integration of low-carbon technologies appears feasible for wind energy. In a third step algorithmic work is carried out regarding a game theoretic model. Two approaches in order to solve a discretely-constrained mathematical program with equilibrium constraints using disjunctive constraints are presented. The first one reformulates the problem as a mixed-integer linear program and the second one applies the Benders decomposition technique. Selected numerical results are reported.

My dissertation address is to describe the long distance bus (LDB) transport, its structure, service adequacy and the role it plays in linking the core to the periphery of Ethiopia. The study applied both qualitative and quantitative data analyses. The quantitative data was mainly collected by using questionnaires, from the selected passengers and operators by longitudinal survey, 384 passengers, or 10 %, from each bus took part in the survey. Of these, only 241 questionnaires (63%) were fully completed and used for this analysis. And 6 % of buses or operators (64) were selected by systematic sampling. The routes and towns were also selected by lottery method. The qualitative data was mainly collected by interview. Among these, 5 % (twenty-five) of experts from the City Transport Bureau; the heads of LDB Associations; the owners of LDB; the Federal Transport bureau; and the Mercato Bus terminal. An interview was analyzed based on their own explanations. FGDs were carried out with passengers awaiting departure in the terminal (off-journey). The secondary sources were taken from both the EFTA and Mercato bus terminal dispatch report. The analysis was made mostly by integrating method, and in some cases with separate analysis. Beside with other inferential statistical, Pearson correlation was also applied. The growth rate for level one and level two buses had risen more than 100 % per annum, whereas level three buses showed a decline of 18 % per year. The whole sector shows a 6.6 % growth rate, which is double that of the population growth (2.6 %). The rate of bus dispatch is very high, approximately 38 per day, on the Dessie and Mojo route. The average bus dispatch in all directions is about 32. In terms of service provision and area coverage, level one buses interlink about 23 major towns. Level two buses service more than 70 major towns, and level three more than 110. The highest record of both area and service coverage was occupied by first level buses servicing Dessie, Mekele, Shashemene, Hawassa, and Jimma. On average, the majority of towns are being serviced by one bus, irrespective of their levels. The area and service coverage is thus very high for level three buses, compared with levels two and one. The Dessie and Mojo lines enjoy the highest bus coverage. LDBs typically provide transport for distances of less than 400 kilometres. They contribute towards core to peripheral ties of the nation. This result is expressed by Krugman’s (1991) core-periphery theory. The service adequacy of the industry indicates that above half of the operators would have to wait approximately one hour to pick up passengers and 1 or 2 days per week to get the turn too. This reveals that Levels one, two and three operators are dormant for 1 or 2 days per week. Supply is thus greater than demand, causing the emergence of an informal LDB service. The fact that about 60 % of passengers have to wait for approximately an hour to catch a bus, after collecting tickets, indicates the demand. The buses’ downtimes in order to secure a full load on each departure are positively correlated with bus levels. The LDB provide more for mobility of goods and peoples that can be shape land use and development patterns, and it generate jobs. This enable more for economic growth. Thus, level one is more attractive than other levels. The study identifies the major challenges facing LDB transport. Integration within stakeholders, both internally and externally, is crucial to satisfy the passenger. / Geography / D. Phil. (Geography)

台灣大車隊股份有限公司 (Taiwan Taxi Corporation,簡稱台灣大車隊),為台灣民間第一家導入無線衛星派遣系統於2002年正式成立的計程車車隊,到2017年已是一個擁有17,000 名駕駛隊員的大企業,成功地創新了計程車派遣的經營模式。 在這十七年間,換過三個經營團隊,最後在林村田董事長經營下讓公司穩定下來並有盈餘。經營團隊接手後持續更新了早已建構完成之GPS衛星定位與PDA車機派遣系統。另外,更結合了空中排班、熱點候車點、多元化叫車服務與非現金消費系統,升級為平台經營架構。由多種面向匯集了電子技術、智慧手機雲端科技,不但有助於車輛的調度,提昇服務品質,也提昇了駕駛和乘客的安全性,增加了公司的競爭力。在此競爭激烈及節約能源的時期,台灣大車隊透過創新經營模式,持續檢討優缺點,迅速改善缺點,加強優點,增強正向迴路經營模式以創造利潤及業績,使企業持續成長。 前幾年面臨國內外叫車服務系統的挑戰時,如2013年6月Uber入台以及政府推行多元化計程車,台灣大車隊就已投入軟硬體研發和改善公司的作業流程以擴展計程車司機隊員規模、便利顧客、增加附屬營業收入、和流動資金的管理,以及電腦資訊自動化管理系統等多樣措施加強了利潤的成長。對外在環境變化的最新應變措施包括：叫車系統快速自動化、建構多元化叫車體系、增加車隊類型和功能、採取多種措施如手機APP電召,配上軟體記憶增加顧客黏著度、擴充平台經營層面,增加平台經營附加價值、綁定信用卡付費方式,建構出叫車平台營運成功的商業模式。 管理團隊認為所有的成功都基於重視隊友及顧客的價值,堅信：乘客即顧客、加盟隊員為家盟隊員,以增加人際溫暖度的心態來經營。使接觸到大車隊的人,都有得到照顧與或取得利潤的確幸。相對的,車隊營收亦可經由各個微小的服務利潤集結發揮為平台結構關聯性收益而得以實現。 / Taiwan Taxi Corporation Ltd. (Taiwan Taxi) is the first civilian taxi fleet which established a wireless satellite dispatch system in 2002. By 2017, it has succeeded in the innovating of business model for taxi dispatch, and become a large enterprise with 17,000 drivers. During seventeen years, replaced by three management teams, the revenue of Taiwan Taxi finally increasingly stabilized. At present, the manager team led by Lin Cun-Tian still constantly updating the already constructed GPS satellite positioning and PDA car dispatch system. By a variety of aspects for the integration of electronic technology, smart phone cloud technology, this platform not only helps the vehicle scheduling and improves service quality, but also enhance driving and passenger safety which increase their competitiveness. In the period of severe competition and energy conservation, Taiwan Taxi has continually reviewed the advantages and disadvantages through the innovative business model they built. Manager team quickly improves the shortcomings, enhance the advantages, so that a positive loop to create profits and performance can operate and make the enterprises continue to grow. Facing the challenges of domestic and foreign call systems, such as Uber and diversified taxi, Taiwan Taxi has developed new hardware and software research and has improved the operating process to expand their fleet of taxi drivers, facilitate customers since 2013, thus increased the subsidiary operating income, working capital management, and automize the computer management system to strengthen the growth of profits. The newly strategic approaches against external changes include: construct an on-line taxi system, a diversified taxi on call management containing mobile phone call, increase the fleet type and function. Other adoptions such as: memory of previous calls to increase customer stickiness, increase the running of additional function on platform, binding credit card payment, thus a successful business model upon taxi platform are constructed. Manager team believe: all the success is based on the values of teammates and customers, passengers are customers, and all the drivers joined are members of this family. They are happy to increase the warmth between the interpersonal through their management. As long as who contacts with Taiwan Taxi, will get a warm care and obtain profits of fortune. Synchronously, the revenue of cooperation can also be achieved through the combination of each profit margin for platform.

Fundação de Apoio a Pesquisa e à Inovação Tecnológica do Estado de Sergipe - FAPITEC/SE / The growth of the electric energy consumption in the last years has generated the need of the increase in the amount of power sources, making the electricity sector undergo some large changes. This has provided the search for tools that promotes a better efficiency and security to the electrical power systems. A planning problem that is considered important in the daily operation of the power systems is the Unit Commitment, where the time schedule of the operation is defined, determining which machines will be online or offline, and which are the operating points. Those units must operate by load variation, respecting the operative and security constraints. This research proposes the resolution of the problem for the short-term planning, taking a set of constraints associated with the thermal generation and the power system. Among them, we can highlight the output power variation constraints of the machines and the security restrictions of the transmission system, avoided in most Unit Commitment studies. This problem is nonlinear, mixed-integer and has a large scale. The methodology used involves the utilization of an Adaptive Genetic Algorithm, for the Unit Commitment problem, and the Interior-Point Primal- Dual Predictor–Corrector Method, for DC power flow resolution in economic dispatch problem. Furthemore, this research proposes the implementation of cross-over and mutation operators of Genetic Algorithm based on a ring methodology applied in Unit Commitment matrix. The results were obtained through simulations in a mathematical simulation software, using the IEEE test systems with 30 bus and 9 generators, and another with 24 bus and 26 generators. The validation of the algorithm was done by comparing the results with other works in the literature. / O crescimento do consumo de energia elétrica nos últimos anos vem gerando a necessidade de um aumento na quantidade de fontes geradoras, fazendo com que o setor elétrico passe por grandes mudanças. Isso tem proporcionado a busca por ferramentas que ofereçam maior eficiência e segurança aos sistemas de potência. Um problema considerado de extrema importância na operação diária dos sistemas elétricos é o planejamento da Alocação das Unidades Geradoras, onde define-se a programação horária das unidades do sistema, determinando quais máquinas deverão estar ligadas ou desligadas, e quais serão seus respectivos pontos de operação. Essas unidades geradoras devem operar de forma eficaz, mediante a variação da carga, respeitando restrições operativas e de segurança do sistema. Este trabalho propõe a resolução do problema para o planejamento de curto prazo, levando em consideração uma série de restrições relacionadas a geração térmica e ao sistema elétrico. Entre elas, podemos destacar as restrições de variação de potência de saída das máquinas e as restrições de segurança do sistema de transmissão, evitadas na maioria dos estudos de Alocação de Unidades Geradoras. Este problema tem característica não-linear, inteiro-misto e de grande escala. A metodologia utilizada para resolução do problema envolve a utilização de um Algoritmo Genético Adaptativo, para Alocação das Unidades, e o Método de Pontos Interiores Primal-Dual Preditor-Corretor, para a resolução do Fluxo de Potência Ótimo DC no problema do Despacho Econômico. Além disso, este trabalho propõe a implementação dos operadores de cross-over e mutação do Algoritmo Genético com base em uma metodologia anelar aplicada na matriz de alocação de unidades. Os resultados foram obtidos através de simulações em um software de simulação matemática, utilizando os sistemas testes do IEEE de 30 barras com 9 geradores e 24 barras com 26 geradores, e a validação do algoritmo foi feita comparando os resultados obtidos com os outros trabalhos da literatura.

This dissertation focuses on selected issues in regard to the mathematical modeling of electricity markets. In a first step the interrelations of electric power market modeling are highlighted a crossroad between operations research, applied economics, and engineering. In a second step the development of a large-scale continental European economic engineering model named ELMOD is described and the model is applied to the issue of wind integration. It is concluded that enabling the integration of low-carbon technologies appears feasible for wind energy. In a third step algorithmic work is carried out regarding a game theoretic model. Two approaches in order to solve a discretely-constrained mathematical program with equilibrium constraints using disjunctive constraints are presented. The first one reformulates the problem as a mixed-integer linear program and the second one applies the Benders decomposition technique. Selected numerical results are reported.

[ES] El triaje de los incidentes de urgencias y emergencias extrahospitalarias representa un reto difícil, debido a las limitaciones temporales y a la incertidumbre. Además, errores en este proceso pueden tener graves consecuencias para los pacientes. Por lo tanto, cualquier herramienta o estrategia novedosa que mejore estos procesos ofrece un valor sustancial en términos de atención al paciente y gestión global de los incidentes. La hipótesis en la que se basa esta tesis es que el Aprendizaje Automático, concretamente el Aprendizaje Profundo, puede mejorar estos procesos proporcionando estimaciones de la gravedad de los incidentes, mediante el análisis de millones de datos derivados de llamadas de emergencia de la Comunitat Valenciana (España) que abarcan desde 2009 hasta 2019. Por tanto, esta tesis profundiza en el diseño y desarrollo de modelos basados en Aprendizaje Profundo Multitarea que aprovechan los datos multimodales asociados a eventos de urgencias y emergencias extrahospitalarias. Nuestro objetivo principal era predecir si el incidente suponía una situación de riesgo vital, la demora admisible de la respuesta y si era competencia del sistema de emergencias o de atención primaria. Utilizando datos disponibles entre 2009 y 2012, se observaron mejoras sustanciales en las métricas macro F1, con ganancias del 12.5% para la clasificación de riesgo vital, del 17.5% para la demora en la respuesta y del 5.1% para la clasificación por jurisdicción, en comparación con el protocolo interno de triaje de la Comunidad Valenciana. Sin embargo, los sistemas, los protocolos de triaje y las prácticas operativas evolucionan de forma natural con el tiempo. Los modelos que mostraron un rendimiento excelente con el conjunto de datos inicial de 2009 a 2012 no demostraron la misma eficacia cuando se evaluaron con datos posteriores que abarcaban de 2014 a 2019. Estos últimos habían sufrido modificaciones en comparación con los anteriores, que dieron lugar a variaciones en las distribuciones de probabilidad, caracterizadas e investigadas meticulosamente en esta tesis. Continuando con nuestra investigación, nos centramos en la incorporación de técnicas de Aprendizaje Continuo Profundo en nuestros desarrollos. Gracias a ello, pudimos mitigar sustancialmente los efectos adversos consecuencia de los cambios distribucionales sobre el rendimiento. Los resultados indican que, si bien las fluctuaciones de rendimiento no se eliminan por completo, pueden mantenerse dentro de un rango manejable. En particular, con respecto a la métrica F1, cuando las variaciones distribucionales son ligeras o moderadas, el comportamiento se mantiene estable, sin variar más de un 2.5%. Además, nuestra tesis demuestra la viabilidad de construir herramientas auxiliares que permitan a los operadores interactuar con estos complejos modelos. En consecuencia, sin interrumpir el flujo de trabajo de los profesionales, se hace posible proporcionar retroalimentación mediante predicciones de probabilidad para cada clase de etiqueta de gravedad y tomar las medidas pertinentes. Por último, los resultados de esta tesis tienen implicaciones directas en la gestión de las urgencias y emergencias extrahospitalarias en la Comunidad Valenciana, al integrarse el modelo final resultante en los centros de atención de llamadas. Este modelo utilizará los datos proporcionados por los operadores telefónicos para calcular automáticamente las predicciones de gravedad, que luego se compararán con las generadas por el protocolo de triaje interno. Cualquier disparidad entre estas predicciones desencadenará la derivación del incidente a un coordinador médico, que supervisará su tratamiento. Por lo tanto, nuestra tesis, además de realizar importantes contribuciones al campo de la Investigación en Aprendizaje Automático Biomédico, también conlleva implicaciones sustanciales para mejorar la gestión de las urgencias y emergencias extrahospitalarias en el contexto de la Comunidad Valenciana. / [CA] El triatge dels incidents d'urgències i emergències extrahospitalàries representa un repte difícil, a causa de les limitacions temporals i de la incertesa. A més, els errors en aquest procés poden tindre greus conseqüències per als pacients. Per tant, qualsevol eina o estratègia innovadora que millore aquests processos ofereix un valor substancial en termes d'atenció al pacient i gestió global dels incidents. La hipòtesi en què es basa aquesta tesi és que l'Aprenentatge Automàtic, concretament l'Aprenentatge Profund, pot millorar significativament aquests processos proporcionant estimacions de la gravetat dels incidents, mitjançant l'anàlisi de milions de dades derivades de trucades d'emergència de la Comunitat Valenciana (Espanya) que abasten des de 2009 fins a 2019. Per tant, aquesta tesi aprofundeix en el disseny i desenvolupament de models basats en Aprenentatge Profund Multitasca que aprofiten dades multimodals d'incidents mèdics d'urgències i emergències extrahospitalàries. El nostre objectiu principal era predir si l'incident suposava una situació de risc vital, la demora admissible de la resposta i si era competència del sistema d'emergències o d'atenció primària. Utilitzant dades disponibles entre 2009 i 2012, es van observar millores substancials en les mètriques macro F1, amb guanys del 12.5% per a la classificació de risc vital, del 17.5% per a la demora en la resposta i del 5.1% per a la classificació per jurisdicció, en comparació amb el protocol intern de triatge de la Comunitat Valenciana. Tanmateix, els protocols de triatge i les pràctiques operatives evolucionen de forma natural amb el temps. Els models que van mostrar un rendiment excel·lent amb el conjunt de dades inicial de 2009 a 2012 no van demostrar la mateixa eficàcia quan es van avaluar amb dades posteriors que abastaven de 2014 a 2019. Aquestes últimes havien sofert modificacions en comparació amb les anteriors, que van donar lloc a variacions en les distribucions de probabilitat, caracteritzades i investigades minuciosament en aquesta tesi. Continuant amb la nostra investigació, ens vam centrar en la incorporació de tècniques d'Aprenentatge Continu als nostres desenvolupaments. Gràcies a això, vam poder mitigar substancialment els efectes adversos sobre el rendiment conseqüència dels canvis distribucionals. Els resultats indiquen que, si bé les fluctuacions de rendiment no s'eliminen completament al llarg del temps, poden mantenir-se dins d'un rang manejable. En particular, respecte a la mètrica F1, quan les variacions distribucionals són lleugeres o moderades, el comportament es manté estable, sense variar més d'un 2.5%. A més, la nostra tesi demostra la viabilitat de construir eines auxiliars que permeten als operadors interactuar amb aquests models complexos. En conseqüència, sense interrompre el flux de treball dels professionals, es fa possible proporcionar retroalimentació mitjançant prediccions de probabilitat per a cada classe d'etiqueta de gravetat i prendre les mesures pertinents. Finalment, els resultats d'aquesta tesi tenen implicacions directes en la gestió de les urgències i emergències extrahospitalàries a la Comunitat Valenciana, al integrar-se el model final resultant als centres d'atenció de telefonades. Aquest model utilitzarà les dades proporcionades pels operadors telefònics per calcular automàticament les prediccions de gravetat, que després es compararan amb les generades pel protocol de triatge intern. Qualsevol disparitat entre aquestes prediccions desencadenarà la derivació de l'incident a un coordinador mèdic, que supervisarà el seu tractament. Per tant, és evident que la nostra tesi, a més de realitzar importants contribucions al camp de la Investigació en Aprenentatge Automàtic Biomèdic, també comporta implicacions substancials per a millorar la gestió de les urgències i emergències extrahospitalàries en el context de la Comunitat Valenciana. / [EN] Triage for out-of-hospital emergency incidents represents a tough challenge, primarily due to time constraints and uncertainty. Furthermore, errors in this process can have severe consequences for patients. Therefore, any novel tool or strategy that enhances these processes can offer substantial value in terms of patient care and overall management of out-of-hospital emergency medical incidents. The hypothesis upon which this thesis is based is that Machine Learning, specifically Deep Learning, can improve these processes by providing estimations of the severity of incidents, by analyzing millions of data derived from emergency calls from the Valencian Region (Spain) spanning from 2009 to 2019. Hence, this thesis delves into designing and developing Deep Multitask Learning models that leverage multimodal out-of-hospital emergency medical data. Our primary objective was to predict whether the incident posed a life-threatening situation, the admissible response delay, and whether it fell under the jurisdiction of the emergency system or primary care. Using data available from 2009 to 2012, the results obtained were promising. We observed substantial improvements in macro F1-scores, with gains of 12.5% for life-threatening classification, 17.5% for response delay, and 5.1% for jurisdiction classification, compared to the in-house triage protocol of the Valencian Region. However, systems, dispatch protocols, and operational practices naturally evolve over time. Models that exhibited excellent performance with the initial dataset from 2009 to 2012 did not demonstrate the same efficacy when evaluated on data spanning from 2014 to 2019. This later dataset had undergone modifications compared to the earlier one, which led to dataset shifts, which we have meticulously characterized and investigated in this thesis. Continuing our research, we incorporated Deep Continual Learning techniques in our developments. As a result, we could substantially mitigate the adverse performance effects consequence of dataset shifts. The results indicate that, while performance fluctuations are not completely eliminated, they can be kept within a manageable range. In particular, with respect to the F1-score, when distributional variations fall within the light to moderate range, the performance remains stable, not varying by more than 2.5%. Furthermore, our thesis demonstrates the feasibility of building auxiliary tools that enable dispatchers to interact with these complex deep models. Consequently, without disrupting professionals' workflow, it becomes possible to provide feedback through probability predictions for each severity label class and take appropriate actions based on these predictions. Finally, the outcomes of this thesis hold direct implications for the management of out-of-hospital emergency medical incidents in the Valencian Region. The final model resulting from our research is slated for integration into the emergency medical dispatch centers of the Valencian Region. This model will utilize data provided by dispatchers to automatically compute severity predictions, which will then be compared with those generated by the in-house triage protocol. Any disparities between these predictions will trigger the referral of the incident to a physician coordinator, who will oversee its handling. Therefore, it is evident that our thesis, in addition to making significant contributions to the field of Biomedical Machine Learning Research, also carries substantial implications for enhancing the management of out-of-hospital emergencies in the context of the Valencian Region. / Ferri Borredà, P. (2024). Deep Continual Multimodal Multitask Models for Out-of-Hospital Emergency Medical Call Incidents Triage Support in the Presence of Dataset Shifts [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/203192

This research presents a Hybrid Particle Swarm Optimization with Bat Algorithm (HPSOBA) based approach to solve Optimal Reactive Power Dispatch (ORPD) problem. The primary objective of this project is minimization of the active power transmission losses by optimally setting the control variables within their limits and at the same time making sure that the equality and inequality constraints are not violated. Particle Swarm Optimization (PSO) and Bat Algorithm (BA) algorithms which are nature-inspired algorithms have become potential options to solving very difficult optimization problems like ORPD. Although PSO requires high computational time, it converges quickly; while BA requires less computational time and has the ability of switching automatically from exploration to exploitation when the optimality is imminent. This research integrated the respective advantages of PSO and BA algorithms to form a hybrid tool denoted as HPSOBA algorithm. HPSOBA combines the fast convergence ability of PSO with the less computation time ability of BA algorithm to get a better optimal solution by incorporating the BA’s frequency into the PSO velocity equation in order to control the pace. The HPSOBA, PSO and BA algorithms were implemented using MATLAB programming language and tested on three (3) benchmark test functions (Griewank, Rastrigin and Schwefel) and on IEEE 30- and 118-bus test systems to solve for ORPD without DG unit. A modified IEEE 30-bus test system was further used to validate the proposed hybrid algorithm to solve for optimal placement of DG unit for active power transmission line loss minimization. By comparison, HPSOBA algorithm results proved to be superior to those of the PSO and BA methods. In order to check if there will be a further improvement on the performance of the HPSOBA, the HPSOBA was further modified by embedding three new modifications to form a modified Hybrid approach denoted as MHPSOBA. This MHPSOBA was validated using IEEE 30-bus test system to solve ORPD problem and the results show that the HPSOBA algorithm outperforms the modified version (MHPSOBA). / Electrical and Mining Engineering / M. Tech. (Electrical Engineering)