Dissertations / Theses on the topic 'Dispatcher control'

Theses focuses on the evaluation of the possible means of active and reactive power control of generating units connected to medium voltage. First part summarizes analysis of Czech Republic medium voltage distribution grid. It summarizes means of autonomous and dispatcher control of generating units with respect to European Comission directive RfG, standard ČSN EN 50549-2 and national implementation PPDS. Following parts provide description of generating unit and distribution grid models used for simulation in PSCAD. Last part focuses on evaluation of results obtained via simulating steady-state scenarios as well as continuous simulation.

Thesis (M.S.)--West Virginia University, 2003.
Title from document title page. Document formatted into pages; contains ix, 63 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 60-63).

Direct Load Control (DLC) -- the direct control of customer loads by an electric utility for the economic and reliable operation of the power system, is an important and active element of Load Management (LM). Currently attention has focussed on the integration of DLC into system operations. However, as yet, DLC is regarded as a discretionary resource to be used by the system operator based on informed judgment. The integration process has therefore, concentrated on improving the informational inputs to the operator. This dissertation extends the integration from that of a discretionary resource to a dispatchable system resource. The concept of the dynamic dispatch of DLC is formulated and defined to be an online evaluation and utilization of DLC for optimum benefit to the utility, as system conditions change. The concept envisages the use of DLC in an automated mode and coordinated with other system resources for optimum benefit. An important and integral part of the research effort is the development of a cost characterization of DLC. A closed form solution, using a dynamic programming framework, has been developed to estimate the costs of DLC dispatch. The derivation takes into account all operational constraints on the utilization of DLC -- payback characteristics, maximum on-times and minimum recovery times. The cost, defined as the difference in the fuel costs with and without DLC dispatch, were found to be dependent on the cost characteristics of the online generators and the load shape impacts of DLC dispatch. The dynamic dispatch concept is concretized by a power system operations model which incorporates DLC dispatch for fuel cost minimization and peak load shaving. The two modes are toggled by the dispatch algorithm as system conditions change. Results from the model are presented for several combinations of system conditions and DLC system parameters.
Ph. D.

Optimum power dispatch is performed in a power system to determine the most economic power dispatch condition for a certain system loading. In this thesis the main focus is on the investigation of this problem and its improved application by including both dynamic security and static security limits in its solution. The aim is to develop an efficient and practical on-line method of optimum power dispatch with due regard to the necessary security requirements. A critical review of the current practices of security and optimization in power system operation shows that they are essential elements in Energy Management System computer softwares. Since optimality and security present conflicting requirements on system operation, it is both logical and beneficial to develop an integrated approach to satisfy all the security limits in optimum dispatch. The classical approach to consider only the static security limits in optimum dispatch calculation is found to be insufficient in providi ng the essential informations on the dynamic security performance. This problem is causing increasing concern with the recent trend to load power systems more closer to their stability limits in order to achieve maximum economy. A new formulation of the security constrained optimum dispatch problem with an integrated approach to consider both dynamic and static security limits is thus proposed in this thesis. The Optimum Power Flow ( OPF ) formulation uses a Recursive Quadratic Programming algorithm applied in the compact modelling of the system. This formulation consists of a decoupling process of the active and reactive power optimizations. The investigation into on-line security control shows that insufficient attention on dynamic security in present practice could endanger the system integrity in the contingency state. This leads to the development of a new scheme to integrate both dynamic and static security assessments. Direct application of classical transient stability assessment methods using numerical integration of swing equations is found to be too slow and a new method based on reduced dynamic equivalent is investigated. The method is based on an efficient dynamic security assessment scheme which assesses the on-line operating state of the system. A dynamic security margin is defined to measure the robustness of the system when it is subjected to a selected scenario of dynamic contingency. The method also identifies the critical machine or cluster of machines that would cause transient instability, and proposes preventive control strategies to improve the dynamic security performance. This is integrated in the approach as a preventive control module. The module aims to prevent the system from reaching probable system collapse due to contingency that could cause cascading tripouts in the system. Extensive simulation tests are performed using the approach in several example networks together with validation case studies compared to full load flow and transient stability tests. The results demonstrate that the approach is fast and reliable with good potential for on-line application in stability limited power systems.

This research concerns exploiting knowledge of the user's environment (i.e., context information) to enrich a user's communication making it more personal, by ensuring that the user receives only relevant messages and calls in his/her current context, and to facilitate more opportunities for communication interactions with people that are in the same context and that share the same interests as this user. We describe in this licentiate thesis the concepts of context-addressed messaging and context-aware session control that enable users to: (1) send messages to others based on their context, rather than their network address and (2) to initiate, adapt, and terminate user's communication sessions based on this user's current context, respectively. These concepts address questions such as: how to discover, select, and switch to an optimal communication means to meet varying user, contextual, communication, and device resource requirements and preferences. A key to solving these problems is to create a representation of the user's context-dependent preferences and to process the user's context-dependent preferences which are part of context triggers. These context triggers can initiate a communication event upon a particular context update. Additionally, in order to provide the described context-aware communication functions, these mechanisms need timely access to the acquired (desired) context information. This in turn raises a plethora of other questions, such as how to discover sensors that provide the desired context information; how to acquire raw context data from these sensors; how to abstract, process, and model this data to become "understandable" to applications and system components; and how to distribute this context to applications that are running on different nodes.

 

This research is split into three different parts. The first part concerns investigating and implementing context management functions. As part of this research we propose a novel approach for context synthesis using context operators. We also propose a design architecture for context-aware middleware that mediates between the sensors and applications, and that is able to share and retrieve context from other nodes in the network. The second part of our research concerns our proposed mechanism for context-addressed messaging. To implement this mechanism we designed our own message format, called the Common Profile for Context-Addressed Messaging (CPCAM) that is able to use any high level context to compose a context-based address. Additionally, we proposed to use context-based filtering to find the correct message recipients and determine if this message is relevant to these potential message recipients in their current context, as well as to deliver this message to the recipients' preferred device that is adapted using their preferred communication means. At the end of this second part we design context-addressed messaging system operations on top of a SIP and SIMPLE-based network infrastructure. The third part of our research describes context-aware session control mechanisms using context switch and context trigger constructs. A context-switch selects an action from a set of context-dependent actions upon an incoming communication event based on the receiver's current context. In contrast, a context trigger initiates an action based on a context update and the user's preferences that are specified in this updated context. This part illustrates in several examples the context-aware session control mechanisms, i.e. the initiation of a communication session based on the match of a user's preferences and current context, as well as adaptation and (if necessary) termination of an ongoing communication session based upon the user's context-dependent preferences.

 

The research leading to this licentiate has created network and system level models necessary for implementation of a context-addressed communication system that would enable users to easily design their own personalized, context-aware communication services. The necessary constructs and properties of these models are designed and analyzed in the thesis, as well as in conference papers and other documents published in the process of doing the research for this thesis. A number of remaining open issues and challenges have been outlined as part of the future work.

 

EU FP6 MIDAS (Middleware Platform for Developing and Deploying Advanced Mobile Services)
EU FP6 MUSIC (Self-adapting Applications for Mobile Users In Ubiquitous Computing Environments)

In this dissertation, we propose a novel distributed approach to the control of generators in the electric grid. Specifically, we consider the problem of the optimal economic dispatch of generator; we present a simple, distributed algorithm, which adjusts the power-frequency set-points of generators to correct for power imbalances arising from generation and load fluctuations. In this algorithm each generator independently adjusts its real-power output based on its estimate of the aggregate power imbalance in the network; such as an estimate can be independently obtained by each generator through local measurements of the frequency deviation on the grid. Eventually, over the course of network operation, the distributed algorithm achieves the equal-marginal-cost power allocation among generators while driving the power imbalance exponentially to zero. In the absence of power losses, we prove the eventual optimality of the distributed algorithm under mild assumptions (strict convexity and positivity of cost functions) and present simulation results to compare its performance with traditional (centralized) dispatch algorithms. Furthermore, we present numerical simulation results that show that the distributed algorithm performs well even in the presence of power losses and other constraints. We argue that distributed control methods are especially attractive for electric grids with smart meters and other advanced capabilities at the end node and grids with high penetration of alternative energy generators and we identify interesting open problems for future work in this area.

The future of the electric grid requires advanced control technologies to reliably integrate high level of renewable generation and residential and small commercial distributed energy resources (DERs). Flexible loads are known as a vital component of future power systems with the potential to boost the overall system efficiency. Recent work has expanded the role of flexible and controllable energy resources, such as energy storage and dispatchable demand, to regulate power imbalances and stabilize grid frequency. This leads to the DER aggregators to develop concepts such as the virtual energy storage system (VESS). VESSs aggregate the flexible loads and energy resources and dispatch them akin to a grid-scale battery to provide flexibility to the system operator. Since the level of flexibility from aggregated DERs is uncertain and time varying, the VESSs’ dispatch can be challenging. To optimally dispatch uncertain, energy-constrained reserves, model predictive control offers a viable tool to develop an appropriate trade-off between closed-loop performance and robustness of the dispatch. To improve the system operation, flexible VESSs can be formulated probabilistically and can be realized with chance-constrained model predictive control. The large-scale deployment of flexible loads needs to carefully consider the existing regulation schemes in power systems, i.e., generator droop control. In this work first, we investigate the complex nature of system-wide frequency stability from time-delays in actuation of dispatchable loads. Then, we studied the robustness and performance trade-offs in receding horizon control with uncertain energy resources. The uncertainty studied herein is associated with estimating the capacity of and the estimated state of charge from an aggregation of DERs. The concept of uncertain flexible resources in markets leads to maximizing capacity bids or control authority which leads to dynamic capacity saturation (DCS) of flexible resources. We show there exists a sensitive trade-off between robustness of the optimized dispatch and closed-loop system performance and sacrificing some robustness in the dispatch of the uncertain energy capacity can significantly improve system performance. We proposed and formulated a risk-based chance constrained MPC (RB-CC-MPC) to co-optimize the operational risk of prematurely saturating the virtual energy storage system against deviating generators from their scheduled set-point. On a fast minutely timescale, the RB-CC-MPC coordinates energy-constrained virtual resources to minimize unscheduled participation of ramp-rate limited generators for balancing variability from renewable generation, while taking into account grid conditions. We show under the proposed method it is possible to improve the performance of the controller over conventional distributionally robust methods by more than 20%. Moreover, a hardware-in-the-loop (HIL) simulation of a cyber-physical system consisting of packetized energy management (PEM) enabled DERs, flexible VESSs and transmission grid is developed in this work. A predictive, energy-constrained dispatch of aggregated PEM-enabled DERs is formulated, implemented, and validated on the HIL cyber-physical platform. The experimental results demonstrate that the existing control schemes, such as AGC, dispatch VESSs without regard to their energy state, which leads to unexpected capacity saturation. By accounting for the energy states of VESSs, model-predictive control (MPC) can optimally dispatch conventional generators and VESSs to overcome disturbances while avoiding undesired capacity saturation. The results show the improvement in dynamics by using MPC over conventional AGC and droop for a system with energy-constrained resources.

This thesis explores how Natural User Interface (NUI) interaction and Multiple Display Technology (MDT) can be applied to an existing Freight Management System (FMS), to improve the command and control interface of the dispatch operators. Situational Awareness (SA) and Task Efficiency (TE) are identified as being the main requirements for dispatchers. Based on studies that have been performed on SA and TE in other time critical occupations such as Emergency Medical Dispatch (EMD) and Air Traffic Control (ATC), a substitute dispatch display system was designed with focus on courier driver and freight management systems and monitoring. This system aims to alleviate cognitive overheads without disrupting the flow of the existing CFMS by providing extended screen area matched with a natural input mechanism for command and control functionality. This Master’s thesis investigates which of commercial state-of-the-art interface tools is best to use in a wide Field-of-View (FOV) multiple screen display and to dicern if there is any practical impact that a proposed NUI system will have to courier dispatching. To assess the efficacy of such a hypothetical system the author has developed an experimental prototype that combines a set of three monitors in a Multi-Monitor System to create the overall display system, accompanied with two traditional and two advanced NUI direct and indirect interaction techniques (mouse, trackpad, touch screen and gesture controller). Experiments using the prototype were conducted to determine the optimum configuration for control/display interface based upon task effectiveness, bandwidth and overall user desirability of these methods in supporting behavioural requirements of dispatch workstation task handling. The author use the well-studied and robust Fitts' Law for measuring and analysing user behaviour with NUIs. Evaluation of the prototype system finds that the multi-touch system paired with the multi-monitor system was the most responsive of the interaction techniques, direct or indirect. Based on these findings, employing such an interaction system is a viable option for deployment in FMS's. However for optimal efficiency, the firmware that supports the interactivity dynamics should be re-designed so it is optimized to touch interaction. This will allow the multi-touch system to be used effectively as an affordance technology. Although the gesture interaction approach has a lot of potential as an alternative NUI device, the performance of gesture input in this experimental setting had the worst performance of all conditions. This finding was largely a result of the interface device limitation within the wide FOV display range of the multi-monitor system. Further design improvements and experimentation are proposed to alleviate this problem for the gesture tracking and for the touchscreen modalities of interaction.

Environmental concerns and long term energy security are the key drivers behind most current electric energy policies whose primary aim is to achieve a sustainable, reliable and affordable energy system. In a bid to achieve these aims many changes have been taking place in most power systems such as emergence of new low carbon generation technologies, structural changes of power system and introduction of competition and choice in electricity supply. As a result of these changes, the level of uncertainties is growing especially on generation side where the locations and available capacities of the future generators are not quite clear-cut. The transmission network needs to be flexibly and economically robust against all these uncertainties. The traditional operation of the network under preventive control mode is an inflexible practice which increases the total system cost. Corrective control operation strategy, however, can be alternatively used to boost the flexibility, to expedite the integration of the new generators and to decrease the overall cost. In this thesis, the main focus is on development of new techniques and methodologies that can be used for modelling and solving a transmission planning problem under the assumption that post-contingency corrective actions are plausible. Three different corrective actions, namely substation switching, demand response and generation re-dispatch are investigated in this thesis. An innovative multi-layer procedure deploying a genetic algorithm is proposed to calculate the required transmission capacity while substation switching is deployed correctively to eradicate the post-fault network violations. By using the proposed approach, a numerical study shows that the network investment reduces by 6.36% in the IEEE 24 bus test system. In another original study, generation re-dispatch corrective action is incorporated into the transmission planning problem. The ramp-rate constraints of generators are taken into account so that the network may be overloaded up to its short-term thermal rating while the generation re-dispatch action is undertaken. The results show that the required network investment for the modified IEEE 24 bus test system can be reduced by 23.8% if post-fault generation re-dispatch is deployed. Furthermore, a new recursive algorithm is proposed to study the effect of price responsive demands and peak-shifting on transmission planning. The results of a study case show that 7.8% of total investment can be deferred. In an additional study on demand response, a new probabilistic approach is introduced for transmission planning in a system where direct load curtailment can be used for either balancing mechanism or alleviating the network violations. In addition, the effect of uncertainties such as wind power fluctuation and CO2 emission price volatility are taken into account by using Monte Carlo simulation and Hypercube sampling techniques. Last but not least, a probabilistic model for dynamic thermal ratings of transmission lines is proposed, using past meteorological data. The seasonal correlations between wind power and thermal ratings are also calculated. £26.7 M is the expected annual benefit by using dynamic thermal ratings of part of National Grid's transmission network.

Orientador: Fernando Antonio Campos Gomide
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação
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Resumo: O transporte ferroviário tem grande participação no transporte de cargas e passageiros em todo o mundo. No Brasil a malha ferroviária sofreu um processo de abandono e deterioração no período de 1960 a 1990. A partir de 1990 a privatização da rede ferroviária nacional iniciou uma retomada de investimentos e nos últimos anos à demanda por transporte ferroviário vem crescendo significativamente. É necessário, então, que os recursos da ferrovia sejam utilizados de maneira eficiente para atender a crescente demanda, o que exige planejamento estratégico, táctico e operacional. No nível operacional uma das principais etapas e também umas das mais carentes de ferramentas computacionais é o Planejamento de Circulação de trens. O processo operacional de uma ferrovia é dinâmico, sujeito a inúmeras interferências imprevisíveis e uma ferramenta computacional para o apoio ao planejamento de circulação de trens deve fornecer soluções com tempo de processamento compatível com essa realidade. Este trabalho propõe algoritmos para o planejamento de circulação de trens em tempo real, utilizando metodologias de inteligência computacional e conjuntos nebulosos. Um algoritmo objetiva decidir localmente a preferência entre trens concorrendo pelo uso de um segmento de linha singela de modo a seguir uma referência de percurso fornecida por algum algoritmo de otimização ou por um especialista. Outro algoritmo decide, além da preferência entre trens, a velocidade de percurso dos trens para mantê-los o mais próximo possível de suas referências. O terceiro algoritmo usa elementos de busca em árvore para obter uma solução para o planejamento de circulação de trens. É feito um estudo comparativo dos algoritmos aqui propostos e de algoritmos existentes na literatura. O estudo comparativo é feito a pm1ir de instâncias pequenas de problema de planejamento de circulação e uma instância que considera dados reais de uma ferrovia brasileira. Os resultados mostram que os algoritmos propostos obtêm soluções próximas às ótimas para as instâncias pequenas e soluções satisfatórias para o caso real
Abstract: Railways plays a major role in freight and passenger transportation in the whole world. The Brazilian railway system has suffered a process of abandon and deterioration from 1960 to 1990. Since 1990 the privatization of the national railways brought new investments and in the last years the demand for railway transportation has increased significantly. Railway resources must be efficiently managed to match the increasingly transportation demand. This requires efficient strategic, tactical and operational planning. One of the main tasks at the operational planning level concerns train circulation and associated tools. Railway operation is a very dynamic process because trains are subject to many unexpected interferences. Computational tools to help trains circulation planning must provide solutions in a time range consistent with real-time needs. This work suggests algorithms for real-time train movement planning, using computational intelligence and fuzzy set theory methodology. One of the algorithms decides the preference between trains competing for a single line track at the same moment. The aim is to drive train circulation as dose as possible to reference trajectories supplied by human experts, global optimization algorithms or both. Other algorithm decides preference between trains and chose the velocity with which trains must travel to remain as dose as possible to its references. The third algorithm uses depth search algorithm to obtain a solution for train circulation problems. A comparative study considering the algorithms proposed herein and algorithms suggested in the literature. The comparative study is done using small railway system instances. Data of a major Brazilian railway is adopted to illustrate how the algorithms behave to solve larger instances. Results show that the algorithms here proposed obtain near optimal solutions for small instances and satisfactory solutions for the real case
Mestrado
Automação
Mestre em Engenharia Elétrica

Richard N Haass, actual director de Política en la Secretaría de Estado de EEUU ha dado lo que es, probablemente, la definición más integral del proceso de globalización que el mundo enfrenta. Para él, la globalización es la totalidad y velocidad de las conexiones sean estas económicas, políticas, sociales y culturales que escapan al control, e incluso al conocimiento, de los gobiernos y otras autoridades. EL siglo XXI se está caracterizando por un enlomo globalizado y altamente competitivo. En este escenario el Sistema Inteligente de Mina se presenta como una herramienta que facilita la gestión en las operaciones de las más importantes Organizaciones Mineras. Es común adjudicar el éxito empresarial tanto a la adopción de una estrategia adecuada como a la práctica de la eficiencia operativa, la segunda consiste en la aplicación de herramientas de gestión. En la búsqueda de esa eficiencia operativa, diversas empresas e instituciones se han dedicado, durante las últimas tres décadas, a desarrollar y comprobar la eficiencia de nuevos conceptos y herramientas de gestión. Así, junto con la calidad total, el mejoramiento continuo, el Just-in-time la Reingeniería y el Benchmarking el Sistema Inteligente de Mina como Concepto General puede ser una de las principales herramientas de gestión orientadas al logro de la eficiencia operativa necesaria para que la estrategia rinda sus frutos.

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Esta pesquisa tem por objetivo o desenvolvimento de uma ferramenta computacional para a solução do problema de Fluxo de Potência Ótimo Multimercado (FPOM). O problema de fluxo de potência ótimo mutimercado é decomposto em vários subproblemas, uma para cada, submercado que compõe o sistema de potência interconectado. O modelo de decomposição utilizado permite resolver o problema de FPO considerando-se os modelos de mercado desverticalizados e centralizados e os desverticalizados e descentralizados. Neste contexto, a pesquisa desenvolvida considera o novo esquema de funcionamento dos mercados de energia elétrica, no qual é vi freqüentemente desejável preservar a autonomia de cada um dos submercados que compõem o sistema de potência multimercado. O problema de FPO proposto é modelado como um problema de otimização não-linear inteiro misto, com variáveis de controle contínuas e discretas e têm ênfase no despacho econômico da geração de potência ativa e nos ajustes dos controles de tensão. Além disso, este modelo de FPO trata os subproblemas ativo e reativo simultaneamente. Para a sua solução é apresentado um algoritmo evolutivo multiobjetivo, baseado no NSGA (Nondominated Sorting Genetic Algorithm), pois características do problema abordado dificultam a sua solução através das técnicas baseadas em programação matemática e justificam a escolha da metaheurística multiobjetivo.
This research is aimed at developing a computational tool for the solution of the Multimarket Optimal Power Flow (MOPF) problem. The multimarket optimal power flow problem is decomposed in various subproblems, one for each submarket that is part of the interconnected power system. The decomposition model used here allows solving the OPF problem considering the deregulated and centralized, and the deregulated and decentralized market models. In this context, the developed research takes into account the new functioning scheme of the electric power markets, viii where it is frequently desirable to preserve the autonomy of each one of those submarkets that compose the multimarket power system. The proposed OPF problem is modeled as a mixed integer non-linear optimization problem with continuous and discrete control variables, emphasizing the economic dispatch of the active power generation and the voltage control adjustments. In addition, this model of OPF deals simultaneously with the active and reactive subproblems. For its solution, a multiobjective evolutionary algorithm based on the NSGA (Nondominated Sorting Genetic Algorithm) is presented. The characteristics of the problem make difficult the utilization of techniques based on mathematical programming, justifying the adoption of a multiobjective metaheuristic.

Non-centralized control schemes for large-scale systems, including energy networks, are more flexible, scalable, and reliable than the centralized counterpart. These benefrts are obtained by having a set of local control!ers, each of which is responsible for a partition of the system, instead of one central entity that controls the whole system. Furthermore,in sorne cases, employing a non­ centralized control structure might be necessary due to the intractability problem of the centralized method.Thus, this thesis is devoted to the study of non-centralized optimization-based control approaches for large-scale energy systems. Mainly,this thesis focuses on the communication and cooperation processes of local controllers, which are integral parts of such schemes. Throughout this thesis,the model predictíve control framework is applied to solve the economic dispatch problem of large-scale energy systems. In a non-centralized architecture, local controllers must cooperatively solve the economic dispatch problem, which is formulated as a convex optimization problem with edge-based coupling constraints, at each time step.Therefore, first, the augmented Lagrangian approach is deployed to decompose the problem and to design two distributed optimization methods, which are iterative and require the local controllers to exchange information with each other at each iteration. lt is then shown that the sequence produced by these methods converges to an optima!solution when sorne cond tions, which include how the controllers must communicate and cooperate, are satisfied. However, in practice, the communication process might not always be perfect,i.e.,the required communication assumption does not hold. In the case of communication link failures, the distributed methods might not be able to compute a solution.Therefore,an information exchange protocol that is based on consensus is designed to overcome this problem. Furthermore, the proposed distributed methods are also further·extended such that they work over random communication networks and asynchronous updates, i.e.,when not all controllers always perform the updates . Under this setup, the convergence and the convergence rate of the algorithms are shown. Additionally, the implementation of these distributed methods to an MPC-based economic dispatch is also presented. The discussion includes the techniques that can be used to reduce the number of iterat ions and the performance of the methods in a numerical study. Considering that the aforementioned methods are comrnunication-intensive, an alternative non-centralized scheme, which provides a trade-off between comrnunication intensity and suboptirnality,is proposed.The scheme consists of repartitioning the network online with the aim of obtaining self-sufficient subsystems, forming coalitions for subsystems that are not self-sufficient,and decomposing the economic dispatch problem of the system into coalition-based subproblems. In this scheme, each subsystem only communicates to the others that belong to the sarne coalition;thus, reducing communication. Especially when all subsystems are self-sufficient, exchanging information is not needed. Finally,a cooperation problem during the implementation of the decisions is discussed. Specifically, sorne subsystems do not cornply with the computed decisions to gain better performance at the cost of deteriorating the performance of the other subsystems.A resilient scheme that can cope with this problem is formulated.lt consists of a stochastic method to robustify the decisions against such adversaria! behavior and an identification and mitigation method that is based on hypothesis testing using Bayesian inference.The proposed scheme, in general,can mitigate the effect of non-
Los esquemas de control no centralizados aplicados a sistemas a gran escala, entre los que se incluyen las redes energéticas, son más flexibles, escalables y fiables que sus equivalentes centralizados. Dichos beneficios pueden obtenerse empleando un conjunto de controladores locales, donde cada uno de ellos es responsable de una parte del sistema, en lugar de una entidad central que controle la totalidad del sistema.Asimismo,el uso de una estructura de control no centralizada podría ser, en algunos casos, necesario, dado el problema de intratabilidad del método centralizado. Por consiguiente, la presente tesis trata sobre el estudio de enfoques de control no centralizados basados en optimización para redes energéticas a gran escala. Principalmente, esta tesis se centra en los procesos de comunicación y cooperación llevados a cabo por los controladores locales , que constituyen partes esenciales de dichos esquemas . A lo largo de esta tesis, el control predictivo basado en modelos se usa para resolver el problema de expedir energia en redes energéticas a gran escala desde un punto de vista económico. En arquitecturas no centralizadas, los controladores locales deben resolver dicho problema de forma cooperativa, el cual se formula como un problema de optimización convexo con restricciones de acoplamiento en los enlaces entre nodos, que debe ser resuelto en cada instante de tiempo. Para ello, el método de Lagrangiano aumentado se utiliza inicialmente para descomponer el problema y diseñar dos métodos de optimización distribuidos , que son iterativos y requieren que los controladores locales intercambien información entre ellos en cada iteración . A continuación, se muestra que la secuencia generada por estos métodos converge a la solución óptima a condición de que se cumplan ciertas condiciones,incluyendo cómo los controladores deben comunicarse y cooperar. Sin embargo, en la práctica,la comunicación no siempre es perfecta, es decir,el supuesto de comunicación requerido no se cumple. En el caso de fallos en los enlaces de comunicación, los métodos distribuidos podrían no ser capaces de proporcionar una solución. Para paliar este problema, se diseña un protocolo de información basado en consenso.l'v1ás aún, los métodos de optimización distribuidos se extienden a fin de que sean capaces de trabajar en redes con comunicaciones aleatorias y actualizaciones asíncronas, es decir,redes en que no todos los controladores realicen las actualizaciones . En esta configuración se muestran la convergencia y el orden de convergencia de dichos algoritmos. Se muestra, además, la implementación de estos métodos en el control predictivo económico basado en modelos para redes energéticas. La discusión incluye las técnicas que pueden usarse para reducir el número de iteraciones, así como el desempeño de los métodos, a través de un estudio numérico. Teniendo en cuenta que los métodos anteriormente mencionados requieren una comunicación intensa,se propone otro esquema no centralizado que proporciona un compromiso entre intensidad de comunicación y suboptimalidad . Dicha estrategia consiste en volver a particionar en línea el sistema con el objetivo de obtener subsistemas autosuficientes,formando coaliciones de subsistemas que no lo sean por separado,y descomponiendo el problema económico de expedición de energía en subproblemas de tipo coalicional. En este esquema ,cada subsistema se comunica únicamente con aquellos otros subsistemas que pertenezcan a la misma coalición, reduciendo asi el tráfico de comunicación. En particular, cuando todos los subsistemas son autosuficientes, el intercambio de información ya no es necesario. Finalmente,se considera el problema de la cooperación durante la implementación de las decisiones Específicamente, algunos subsistemas no acatan las decisiones tomadas con el fin de lograr un desempeño propio superior a expensas de empeorar el desempeño de otros subsistemas. Es por esto que, con el fin de lidiar con este problema, se propone un esquema resiliente, el cual consiste en un método estocástico para hacer las decisiones más robustas frente a tal comportamiento adverso, y un método de identificación y mitigación basado en evaluación de hipótesis usando inferencia bayesiana. En general, el esquema propuesto logra mitigar el efecto de los subsistemas incumplidores sobre el resto, y en un caso concreto, también permite identificar los subsistemas adversos.
Els esquemes de control no centralitzats aplicats a sistemes a gran escala, entre els quals s’inclouen les xarxes energètiques, són més flexibles, escalables i fiables que els seus equivalents centralitzats. Aquests beneficis es poden obtenir fent servir un conjunt de controladors locals, en què cadascun d’ells és responsable d’una part del sistema, en lloc d’una entitat central que controli la totalitat del sistema. Així mateix, l’ús d’una estructura de control no centralitzada podria ser, en alguns casos, necessari, donat el problema d’intractabilitat del mètode centralitzat. Per tant, la present tesi tracta sobre l’estudi d’enfocaments de control no centralitzats basats en optimització per a xarxes energètiques a gran escala. Principalment, aquesta tesi se centra en els processos de comunicació i cooperació duts a terme pels controladors locals, que constitueixen parts essencials d’aquests esquemes. Al llarg d’aquesta tesi, el control predictiu basat en models s’utilitza per a resoldre el problema d’expedició d’energia en xarxes energètiques a gran escala des d’un punt de vista econòmic. En arquitectures no centralitzades, els controladors locals han de resoldre aquest problema de forma cooperativa, formulat com un problema d’optimització convex amb restriccions d’acoblament en els enllaços entre nodes i que ha de ser resolt a cada instant de temps. A tal efecte, el mètode de Lagrangià augmentat s’utilitza inicialment per a descomposar el problema i dissenyar dos mètodes d’optimització distribuïts, que són iteratius i requereixen que els controladors locals intercanviïn informació entre ells a cada iteració. A continuació, es mostra que la seqüència generada per aquests mètodes convergeix a la solució òptima si es compleixen certes condicions, incloent la manera en què els controladors s’han de comunicar i cooperar. No obstant això, a la pràctica, la comunicació no és sempre perfecta, és a dir, el supòsit de comunicació perfecta no es compleix. En el cas de fallades en els enllaços de comunicació, els mètodes distribuïts podrien no ser capaços de proporcionar una solució. Per a resoldre aquest problema, es dissenya un protocol d’informació basat en consens. A més, els mètodes d’optimització distribuïts s’amplien per tal que siguin capaços de treballar en xarxes amb comunicacions aleatòries i actualitzacions asíncrones, és a dir, xarxes en què no tots els controladors realitzin les actualitzacions. En aquestes configuracions es mostren la convergència i l’ordre de convergència d’aquests algoritmes. A més, es mostra també la implementació d’aquests mètodes en el control predictiu econòmic basat en models per a xarxes energètiques. La discussió inclou les tècniques que es poden emprar per a reduir el nombre d’iteracions, així com el rendiment dels mètodes, fent servir un estudi numèric. Tenint en compte que els mètodes anteriorment esmentats requereixen una comunicació intensa, es proposa un altre esquema no centralitzat que proporciona un compromís entre intensitat de comunicació i suboptimalitat. Aquesta estratègia consisteix en tornar a particionar el sistema en línia amb l’objectiu d’obtenir subsistemes autosuficients, formant coalicions de subsistemes que no ho siguin per separat, i descomposant el problema econòmic d’expedició d’energia en subproblemes de tipus coalicional. En aquest esquema, cada subsistema es comunica únicament amb aquells altre subsistemes que pertanyin a la mateixa coalició, reduint així el trànsit de comunicació. En particular, quan tots els sistemes són autosuficients, l’intercanvi d’informació deixa de ser necessari. Finalment, es considera el problema de la cooperació durant la implementació de les decisions. Específicament, alguns subsistemes no acaten les decisions preses amb la finalitat de millorar el propi rendiment a costa de disminuir el d’altres subsistemes. És per això que, a fi de solucionar aquest problema, es proposa un esquema resilient, el qual consisteix en un mètode estocàstic per fer les decisions més robustes davant d’aquest comportament advers, i un mètode d’identificació i mitigació basat en evaluar hipòtesis utilitzant inferència bayesiana. En general, l’esquema proposat aconsegueix mitigar l’efecte que els subsistemes no obedients exerceixen sobre la resta, i en un cas concert, també permet identificar els subsistemes adversos.
ABSTRAKSI (Indfonesian) Skema kendali yang tidak tersentralisasi untuk sistem berskala besar, seperti sistem aringan energi, lebih fleksibel, skalabel, dan reliabel dibandingkan dengan skema tersentralisasi. Keuntungan ini diperoleh dari terdapatnya satu set pengendali lokal, yang hanya bertanggung jawab terhadap satu partisi dari sistem tersebut, daripada jika hanya terdapat satu entitas yang mengendalikan seluruh sistem. Bahkan dalam beberapa sistem, penerapan struktur kendali yang tidak tersentralisasi menjadi keharusan karena adanya permasalahan intraktabilitas dari metode tersentralisasi. Oleh karena itu, disertasi ini bertujuan untuk melakukan studi pada metode kendali berdasarkan optimisasi dengan struktur yang tidak tersentralisasi untuk sistem energi berskala besar. Khususnya, disertasi ini memfokuskan pada proses komunikasi dan kooperasi pengendali‐pengendali lokal, yang merupakan bagian integral dalam skema yang dimaksud. Pada disertasi ini, sistem kontrol prediktif (model predictive control (MPC)) diterapkan untuk menyelesaikan optimisasi economic dispatch pada sistem energi berskala besar. Dalam arsitektur yang tidak tersentralisasi, pengendali‐pengendali lokal harus menyelesaikan permasalahan economic dispatch secara kooperatif. Permasalahan economic dispatch ini diformulasikan sebagai optimisasi yang konveks dan memiliki konstrain terkopling. Oleh karena itu, pendekatan Lagrange yang teraugmentasi diterapkan untuk mendekomposisi permasalahan optimisasi terkait. Pendekatan ini juga digunakan untuk merancang dua metode optimisasi terdistribusi, yang iteratif dan mengharuskan pengendali‐pengendali lokal bertukar informasi satu sama lain pada setiap iterasi. Sekuensi yang dihasilkan dari kedua metode tersebut akan terkonvergensi pada suatu solusi yang optimal apabila beberapa kondisi, yang meliputi bagaimana pengendali harus berkomunikasi dan berkooperasi, terpenuhi. Namun, pada praktiknya, proses komunikasi yang terjadi mungkin tidak selalu sempurna, dalam hal ini asumsi pada proses komunikasi yang dibutuhkan tidak terpenuhi. Pada kasus kegagalan jaringan komunikasi, metode terdistribusi yang dirancang mungkin tidak dapat menemukan solusinya. Oleh karena itu, suatu protokol untuk pertukaran informasi yang berdasarkan pada konsensus dirancang untuk mengatasi permasalahan ini. Selanjutnya, dua metode terdistribusi yang telah dirancang juga dikembangkan lebih jauh sehingga metode‐metode tersebut dapat bekerja pada jaringan komunikasi stokastik dengan proses yang asinkron, yaitu proses dimana tidak semua pengendali selalu melakukan pembaruan. Dalam hal ini, konvergensi dan laju konvergensi dari metode yang dirancang dipertunjukkan. Selain itu, implementasi dari metode terdistribusi pada sistem economic dispatch berbasis MPC juga dibahas. Diskusi pada bagian ini mencakup beberapa teknik yang dapat digunakan untuk mengurangi jumlah iterasi dan performa dari metode‐metode yang dirancang pada suatu studi numerik. Dengan pertimbangan bahwa metode‐metode yang disebut sebelumnya membutuhkan komunikasi yang intensif, maka sebuah skema alternatif, yang memberikan trade‐off antara intensitas komunikasi dan suboptimalitas, juga dirancang. Skema ini terdiri dari repartisi sistem online yang bertujuan untuk mendapatkan subsistemsubsistem yang swasembada, pembentukan koalisi untuk subsistem‐subsistem yang tidak swasembada, dan dekomposisi permasalahan economic dispatch menjadi subproblem berbasis koalisi. Dalam skema ini, tiap subsistem hanya perlu berkomunikasi dengan subsistem‐subsistem lain yang berada pada koalisi yang sama; sehingga mengurangi aliran komunikasi. Jika semua subsistem yang terbentuk swasembada, maka pertukaran informasi tidak dibutuhkan sama sekali. Pada akhirnya, disertasi ini juga membahas mengenai suatu permasalahan koperasi dalam masa implementasi keputusan (solusi). Pada permasalahan kooperasi ini, terdapat beberapa subsistem yang tidak menuruti keputusan (solusi), misalnya dengan tujuan untuk mendapatkan kinerja yang lebih baik dan di saat yang bersamaan memperburuk kinerja subsistem lainnya. Maka, sebuah skema resilien yang dapat mengatasi permasalahan ini dirumuskan. Skema tersebut terdiri dari sebuah metode stokastik untuk merobustifikasi keputusan terhadap perilaku adversari dan sebuah metode identifikasi dan mitigasi yang berdasarkan pada pengujian hipotesis dengan menggunakan inferensi Bayes. Skema yang diusulkan, secara umum, dapat memitigasi pengaruh subsistem yang tidak patuh pada subsistem reguler, dan pada kasus tertentu, juga dapat mengidentifikasi subsistem yang menjadi adversari.

Orientador: José Roberto Sanches Mantovani
Banca: Rubén Augusto Romero Lázaro
Banca: Carlos Roberto Minussi
Banca: Geraldo Roberto Martins da Costa
Banca: Antônio César Baleeiro Alves
Resumo: Esta pesquisa tem por objetivo o desenvolvimento de uma ferramenta computacional para a solução do problema de Fluxo de Potência Ótimo Multimercado (FPOM). O problema de fluxo de potência ótimo mutimercado é decomposto em vários subproblemas, uma para cada, submercado que compõe o sistema de potência interconectado. O modelo de decomposição utilizado permite resolver o problema de FPO considerando-se os modelos de mercado desverticalizados e centralizados e os desverticalizados e descentralizados. Neste contexto, a pesquisa desenvolvida considera o novo esquema de funcionamento dos mercados de energia elétrica, no qual é vi freqüentemente desejável preservar a autonomia de cada um dos submercados que compõem o sistema de potência multimercado. O problema de FPO proposto é modelado como um problema de otimização não-linear inteiro misto, com variáveis de controle contínuas e discretas e têm ênfase no despacho econômico da geração de potência ativa e nos ajustes dos controles de tensão. Além disso, este modelo de FPO trata os subproblemas ativo e reativo simultaneamente. Para a sua solução é apresentado um algoritmo evolutivo multiobjetivo, baseado no NSGA (Nondominated Sorting Genetic Algorithm), pois características do problema abordado dificultam a sua solução através das técnicas baseadas em programação matemática e justificam a escolha da metaheurística multiobjetivo.
Abstract: This research is aimed at developing a computational tool for the solution of the Multimarket Optimal Power Flow (MOPF) problem. The multimarket optimal power flow problem is decomposed in various subproblems, one for each submarket that is part of the interconnected power system. The decomposition model used here allows solving the OPF problem considering the deregulated and centralized, and the deregulated and decentralized market models. In this context, the developed research takes into account the new functioning scheme of the electric power markets, viii where it is frequently desirable to preserve the autonomy of each one of those submarkets that compose the multimarket power system. The proposed OPF problem is modeled as a mixed integer non-linear optimization problem with continuous and discrete control variables, emphasizing the economic dispatch of the active power generation and the voltage control adjustments. In addition, this model of OPF deals simultaneously with the active and reactive subproblems. For its solution, a multiobjective evolutionary algorithm based on the NSGA (Nondominated Sorting Genetic Algorithm) is presented. The characteristics of the problem make difficult the utilization of techniques based on mathematical programming, justifying the adoption of a multiobjective metaheuristic.
Doutor

Foi observado que para execução do planejamento diário, no qual há o envolvimento de diversas equipes como operação, perfuração e atividade de apoio, despende-se muito tempo para determinação dos alvos de produção. Em contrapartida, a maior parte das minas de grande porte utilizam sistemas de gerenciamento de equipamentos que são capazes de fornecer dados para tratamento e transformação em informação que poderiam auxiliar nesse planejamento, no entanto na maioria dos casos esses dados são pouco conhecidos e utilizados. Este estudo faz a estimativa de indicadores de desempenho de lavra, oriundos do banco de dados do sistema de Despacho, que podem ser utilizados no planejamento diário (tipo Line-Up aplicado na mina do Sossego, em Canaã dos Carajás - Pará). Metodologicamente, para atingir o proposto, foram realizadas as etapas de análise do Banco de Dados (BD) do sistema de Despacho, descrição do Line-Up da mina do Sossego, análise do contexto operacional entre os dois sistemas: Line-Up e Despacho, estimativa dos indicadores e definição de um cálculo de aderência ao Line-Up. Esse estudo demostra que a partir da coleta e sistematização dos dados é possível tornar as informações contidas no BD do Despacho mais conhecidas e utilizadas na programação diária, permitindo que a utilização dessas informações auxilie na gestão do planejamento de curto prazo, reduzindo o tempo de execução da programação diária e tornando o processo de avaliação da aderência ao Line-Up mais rápido e menos subjetivo. Os dados utilizados para esse estudo são do banco de dados do sistema de despacho da Mina do Sossego (local de exemplo de aplicação).
Daily planning execution, which calls for several teams such as operation, drilling and support to be engaged, has been observed to be a rather time-consuming activity in order for production targets to be determined. On the other hand, most of large-size mine sites make use of equipment management systems capable of providing data to be treated and eventually made into information that may assist such planning efforts. However, such data are mostly scarcely known and used. This paper provides the estimation of mine performance indicators stemming from Dispatch system database that may come in handy for daily planning efforts (Line-Up type, applied to Sossego mine site, in Canaã dos Carajás, state of Pará, Brazil). Methodologically speaking, in order for proposed outcomes to be attained, Dispatch system database has been analyzed, Sossego mine site Line-Up has been described, operational context underlying both systems, Line-Up and Dispatch, has been analyzed, indicators have been estimated, and a Line-Up adherence calculation has been defined. The present paper indicates that, based on data gathering and systematization, information from Dispatch database can be made well known and used during daily scheduling efforts, thus allowing for such information to assist short-term plan management, daily scheduling performance timeframe to be cut down on, and Line-Up adherence assessment process to be faster and less subjective. Data used for this paper come from Sossego mine site dispatch system database (example of local application).

Atualmente, a geração eólica é a forma de geração de energia elétrica de maior crescimento no mundo. Não obstante, dependendo da forma em que é gerenciado este tipo de geração, pode causar impactos significativos no sistema de energia elétrica. Este trabalho estuda o comportamento da geração eólica nos sistemas de potência do ponto de vista dos aerogeradores e dos parques eólicos. É realizada uma modelagem dos principais componentes dos sistemas de geração eólica, particularmente dos aerogeradores de velocidade variável equipados com geradores de indução de dupla alimentação, com o intuito de aplicar estratégias de controle para a operação dos mesmos e estudar as suas características de funcionamento. São propostos métodos para a regulação da potência ativa gerada por estes aerogeradores e para a regulação da potência ativa gerada por parques eólicos compostos por vários aerogeradores de velocidade variável, com o objetivo de permitir um maior índice de penetração da geração eólica nos sistemas de energia elétrica. Usando a modelagem elaborada, são efetuadas rigorosas simulações computacionais do comportamento destas instalações eólicas funcionando com os métodos de regulação propostos. Os resultados obtidos nestas simulações mostram que o impacto da geração eólica pode ser consideravelmente diminuído, logrando atribuições semelhantes aos produtores de energia convencionais. Observa-se que estes métodos permitiriam flexibilizar a operação dos sistemas de geração eólica, possibilitando gerenciamentos mais adequados aos novos requerimentos exigidos pelos operadores dos sistemas de energia.
Nowadays, the wind power generation is the fastest growing electric power source in the world. Nevertheless, depending on the management of this kind of generation, it may cause significant impact in the power system. In this work, a modeling of the main components of wind power generation was performed, particularly of variable speed wind turbines with doubly fed induction generators, aiming to apply control strategies for its operation and to study its functional characteristics. Methods to regulate the active power generated by variable speed wind turbines, and to regulate the active power of wind farms composed of several of this turbines, are proposed with the objective to allow an increase in the level of penetration of wind generation in the power systems. Using the elaborated modeling, rigorous computational simulations of operation of these types of power stations, operating with the proposed methods, were accomplished. The obtained results in these simulations shows that it is possible to considerably minimize the wind power generation impacts, obtaining attributions similarly to conventional energy producers. It is observed that the proposed methods allows an operational flexibility of wind power generation, enabling a better management according to the new requirement of the power system operators.

Orientadores: Carlos Alberto de Castro Junior, Alexandre de Assis Mota
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação
Made available in DSpace on 2018-08-11T20:26:47Z (GMT). No. of bitstreams: 1 AriaArias_David_M.pdf: 982619 bytes, checksum: 902edfe03a42ce4e64a22f698a4267cf (MD5) Previous issue date: 2008
Resumo: O presente trabalho apresenta um modelo para o planejamento da operação de sistemas de potência visando maximizar a margem de estabilidade de tensão ao mesmo tempo em que minimizam-se os custos da produção da energia (despacho econômico). O objetivo é obter uma solução para o planejamento da operação da rede que leve em conta não só aspectos técnicos, mas também econômicos. Para que esse objetivo possa ser atingido, esse problema é formulado como um problema da programação bilevel (BLPP) ou em dois níveis. O modelo bilevel permite definir funções objetivo distintas para maximizar a margem da estabilidade de tensão e, ao mesmo tempo, conseguir um despacho econômico ótimo, permitindo a imposição de diferentes restrições para as variáveis internas e externas do problema. Uma vez que o BLPP apresenta-se como um problema matemático complexo, ele é reduzido a um problema de otimização de um só nível (single-level), substituindo-se o problema de otimização interno pelas condições de ótimalidade de Karush-Kuhn-Tucker (KKT). Foram realizados testes e simulações em diferentes sistemas elétricos, sendo que os resultados obtidos atestam a validade da metodologia proposta. Além disso, a formulação e o método de solução do BLPP apresentados neste trabalho são mais simples que outros encontrados na literatura, tornando essa metodologia bastante flexível para a utilização e investigação de outras funções objetivo, variáveis e parâmetros de controle.
Abstract: This work presents a model for power systems operation planning that aims to maximize the voltage stability margin and also the economic dispatch. The objective is to obtain a solution for the network operation planning that takes into account both technical and economical aspects. In order to reach this goal, this problem is formulated as a bilevel programming problem (BLPP). The bilevel model allows to define distinct objective functions for maximizing the voltage stability margin looking, simultaneously, for an optimum economic dispatch, and permitting the imposition of different constraints to the variables of the inner and outer problems. Since the BLPP is a complex mathematical problem, it is reduced to a single-level optimization problem by replacing the inner optimization problem by its Karush-Kuhn-Tucker optimality conditions. Simulations and tests were carried out for different electric networks, and the results show that the proposed methodology is valid. Moreover, the BLPP formulation and its solution method are simpler than other formulations found in the literature, making the methodology very flexible to accommodate other objective functions, variables and control parameters.
Mestrado
Energia Eletrica
Mestre em Engenharia Elétrica

Le contexte économique actuel montre que la représentation et l'analyse des données dans l'espace 3D croît de plus en plus dans les Systèmes d'Information Géographique (SIG). Le nombre d'applications SIG est en constante augmentation dans de nombreux secteurs d'activités comme par exemple la Défense, l'Aménagement du Territoire ou la Sécurité Civile. Cependant, nous voyons l'émergence d'une forte demande pour l'analyse 3D dans les SIG. Ces développements nécessitent une standardisation des structures de données et d'échanges. Cette démarche est réalisée par l'Open Geospatial Consortium (OGC) et l'organisation internationale de normalisation (ISO). Une norme récente (ISO 19107:2003) décrit les objets complexes à prendre en compte et les traitements qu’il est possible de leur appliquer. Elle cherche à mettre en place l’interopérabilité des échanges et des analyses de données géométriques et topologiques dans les SIG. Actuellement aucune implémentation informatique complète de cette norme n’a été encore réalisée, compte tenu de son niveau d'abstraction. Une version simplifiée a toutefois été développée pour des objets uniquement 2D (ISO 19137:2007). Ce travail de thèse propose la modélisation et l’analyse d'objets complexes dans un espace tridimensionnel, et les traitements associés pour réaliser une première bibliothèque de fonctionnalités conforme à la norme ISO 19107. De plus, cette norme est actuellement portée en révision au sein du consortium OGC (Open Geospatial Consortium, www.opengeospatial.org) avec une nécessité de correction et d’évolution. Les travaux menés jusqu'à présent ont permis d’apporter une contribution pertinente avec l'ajout de nouvelles primitives géométriques, l'harmonisation de primitives par l'usage de courbes et surfaces paramétriques rationnelles. Les travaux sur cette norme ont permis également l’élaboration d'une application au sein de la société GEOMATYS, rendant possible la modélisation et l'analyse 3D d'un trafic aérien reposant sur des données SIG
In the current economic context, the representation and the analysis of 3D data is growing more and more in the field of Geographic Information Systems (GIS). The number of GIS applications is constantly increasing in many industries, such as Defense, Regional Development and Civil Security. However, we can point out the emergence of an important request for 3D analysis in GIS. These developments require a standardization of data and exchange structures. This is carried out by Open Geospatial Consortium (OGC) and International Organization for Standardization (ISO). A recent standard (ISO 19107:2003) describes the complex objects to be taken into consideration and the associated treatments that can be used. It aims to develop interoperable exchange and analysis of geometric and topological data in GIS. Currently, no complete implementation on a computer of this standard has been done yet, regarding the level of abstraction sought. However, a simplified version was exclusively developed for 2D objects (ISO 19137:2007). This thesis proposes the modeling and the analysis of complex objects in three dimensional space, with their associated treatments. The objective is to create a first library whose the features are conform to ISO19107. Moreover, this standard is currently under review within the OGC Consortium (Open Geospatial Consortium) with a need for correction and evolution. The work done until now have enabled us to make a meaningful contribution with the addition of new geometrical primitives, the harmonization of primitives through the use of rational parametric curves and surfaces. The works on this standard also allowed the development of an application within the GEOMATYS company, making possible the 3D modeling and analysis for traffic simulation based on GIS data

The contents of this thesis are the introduction to mesh grids, the method of dispatch control of these grids and the description of technology used in mesh grids distribution nodes in the city of Brno. This thesis also describes low voltage switchgears used in these types of grids. The development of dispatch control in ECD company is also mentioned. The development describes the grid dispatch control methods prior to implementing the OMS system and the changes which followed after the implementation. The process improvements of the new system resulting from this thesis can be found in this thesis as well. The improvements are incorporated in the OMS system and are used for more efficient dispatch control of the low voltage mesh grids. There is a more detailed analysis of the mesh grid Brno – Bohunice in the practical part of this thesis. The practical part contains analyses of mesh grids stabilized conditions measurements and analyses of mesh grids fault conditions measurements. The analyses assess the power load in transformers, minimal and maximal phase current and maximal power load at the time they were observed. The analysis of the measured data is accompanied by the assessment of differences in current phase measurements and differences in voltage phase and combined measurements. The result, based on the analysis and collection of the data, is a proposition of adding switchgears for the support of the dispatch control of the mesh grid Brno – Bohunice. In the summary of the thesis there is a comparison of the result of the factual and theoretical analysis. An experimental model of the mesh grid Brno – Bohunice was created in PS CAD software as a part of the theoretical analysis.

The aim of this thesis is to familiarize readers with the terms and conditions relating to Intrastat and Ex Post Control of Data. The first part deals with obligations under the data collection. There are defined terms such as Intrastat, information provider, reference period, obligation to information provider and competence of government.The text is supplemented by examples that help better understand the topic. This section ends with an example that shows the overall procedure for reporting and transmission of data Intrastat. In the second part of the thesis I deal with Ex Post Control of Data which are carried out by the Customs Administration of the Czech republic. Both parts are supplemented by a number of interesting facts as information provider, number of reported data or inspections. In conclusion I am trying to identify errors and deficiencies in data collection and Ex Post Control of Data and to propose some measures that will lead to improvements in processes relating to Intrastat.

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.

碩士
國立臺灣海洋大學
電機工程學系
99
The influence of the innovation of information technology as well as the global economic trend.Enhancing the competitiveness and efficiency of industry are common objectives of the reform. The U.K. started to deregulate its state-owned power industry in 1989,and the U.K’s experience has subsequently been simulated and adopted in many other country. In today,the trend toward the deregulation of the electricity supply industry has already become a worldwide phenomenon.However,not all of their experienceshave been successful and without no problem.Thus,the assessment method can be applied to check the design of electricity deregulation and to avoid the loopholes on the road to deregulation. The purpose of the study is therefore to compare, analyze and collate the relevant data and actuality work in item. Building a complete model and try to solve the topic “The Best of ISO personnel and planning”to observe possible of changes in the future. Keywords:System Operation,Power Industry Deregulation,Optimization

碩士
正修科技大學
電機工程研究所
97
This thesis presents a Particle Swarm Optimization with Random Particles and Fine Tuning Mechanism(PSO-RPFT) for solving the economic dispatch and pollution control. The proposed method will introduce two operators, “Random Particles” and “Fine Tuning” into the PSO algorithm for increasing the search ability. The process of “Random Particles” will add the proper random particle into the whole particles when the solution is searched in the each generation. The producer of “Fine Tuning” will regulate the “Gbest” position if the generation will be searched on the late period of PSO algorithm. The purpose of “Fine Tuning” during the tuning mechanism can be employed in the algorithm to make the search method more efficient at the end of search, and the success rate of the searching global optimum could be increased. Effectiveness of the PSO-RPFT is proved on several example systems with non-convex functions and compared to that of Particle Swarm Optimization(PSO), Simulated Annealing(SA), Genetic Algorithm(GA), and Evolutionary Programming(EP). By considering convergent time and convergent solution, results can be shown that the proposed method is more effective than other evolutionary algorithms. At last, the proposed method is applied in interactive procedure of cost/pollution and pollution trade. This approach developed will be provided a better tool for power dispatch to meet the load growth and promoted the competed ability of company.

碩士
國立臺灣科技大學
電機工程系
91
Abstract The voltage/reactive power control problem in electrical system is an important issue of utility system operation and management. There are many research papers on the optimal exploration of voltage/reactive power control problem to keep the bus voltage violation within the allowable deviation zone of standard voltage and to minimize the line losses. This dissertation presents a approach to reduce the electrical network into a simple proposed model applying radial equivalent independent method ( REI method ). Based on reduced equivalent model, a feasible solution for scheduling standard voltage and transformer tap/var control using genetic algorithm is developed. The objective of this proposed solution is properly to monitor the load-center bus and substation buses keeping the voltage violation within the deviation zone of expectation values and to minimize the necessary control operation frequency of the transformer tap changer and reactive power regulating equipment. Although the major contributions of this dissertation is intended for application in the system voltage operation and supervision control, it would also be useful in planning studies. Simulation results supporting the validity of the proposed solution in Taipower substations are presented.

碩士
國立成功大學
電機工程學系碩博士班
91
Automatic generation control (AGC) of a power system consists of load frequency control (LFC), economic dispatch and reserved capacity monitoring. The purposes of AGC are to optimize the power generation, to make the power system stable, and to reduce the cost. LFC is to make fast response to the demand requirement of a power system by dispatching the proper generator output. The study discussed the mechanism of frequency variation in the Taiwan power system and the suitable control strategy to speed up the generator response. We developed a mathematic model for the combined cycle unit gas turbine in Hsin-Ta power station and thereby decided the gain of feed-forward load controller. Finally, the proposed control method was verified by the actual unit power generation data from the field tests.

The frequent occurrences of natural and technological disasters have incurred grave loss of life and damage to property. For mitigating the miserable aftermaths, multi-robot teleoperation systems have been developed and deployed to cooperate with human rescuers in post-earthquake scenarios, and to sample, monitor and clean pollutants in marine environments. With a bidirectional communication channel, human users can deliver commands/requests to guide the motions of the remote robots, and can receive visual/audio feedback to supervise the status of the remote environment, throughout multi-robot teleoperation. Furthermore, the remote robots can send force feedback to human operators to improve their situational awareness and task performance. This way, a closed-loop multi-robot teleoperation system becomes bilateral in which coordinated robots physically interact and exchange energy with human users, and hence needs to be rendered passive for safe human-robot interaction. Beyond guaranteeing closed-loop passivity, the control of a bilateral multi-robot teleoperation system faces two challenging problems: preserving the communication connectivity of the remote robots; and dispatching the teleoperation authority to multiple human users. Because wireless transmission of radio/acoustic signals between the remote robots is constrained by their distances, bilateral multi-robot teleoperation control must coordinate the motions of the remote robots appropriately so as to maintain their communication network connected. Further, multiple human users can send possibly conflicting teleoperation commands to the remote robots, a distributed authority dispatch algorithm is thus needed for the remote robot network to recognize and follow the most urgent user commands at runtime. This thesis develops an energy shaping strategy to preserve the connectivity of the remote robots, and to dispatch control authority over the remote robots to human users, during bilateral multi-robot teleoperation. Chapter 1 introduces the application background of multi-robot teleoperation as well as the state-of-the-art development in related research areas. In Chapter 2, a dynamic interconnection and damping strategy is proposed to reduce and constrain the position error between the local and remote robots to any prescribed bound during bilateral teleoperation. Chapter 3 derives a gradient plus damping control from a bounded potential function and then unifies it into an indirect coupling framework to preserve all communication links of an autonomous multi-robot system with time-varying delays and bounded actuation. On these bases, Chapter 4 develops a dynamic feedforward-feedback passivation strategy to preserve all communication links and thus the connectivity of the tree network of the remote robots while rendering the bilateral multi-robot teleoperation close loop passive. Specifically, by blending the sliding variable in Chapter 2 with the bounded potential function in Chapter 3, the dynamic passivation strategy decomposes the dynamics of the remote robots into a power-preserving interconnection of two subsystems, and regulates the energy behaviour of each subsystem to preserve the tree communication connectivity of the remote robots. To handle time-varying communication delays, the strategy further transforms the communication channels between the local and remote robots into a dynamic controller for passivating bilateral teleoperation. Superior to existing controls, the strategy using a bounded potential function can circumvent numerical instability, reduce noise sensitivity and facilitate future extensions to accommodate robot actuator saturation. On the other side, Chapter 5 designs a distributed and exponentially convergent winners-take-all authority dispatch algorithm that activates the teleoperation of only human users with the most urgent requests in real time. After formulating the problem as a constrained quadratic program, we employ an exact penalty function method to construct a distributed primal-dual dynamical system that can solve the problem at an exponential rate. Because the equilibrium of the system changes with user requests, we then interconnect the dynamical system with physical robot dynamics in a power-preserving way, and passivate closed-loop multi-robot teleoperation using multiple storage functions from a switched system perspective. Finally, Chapter 6 provides some conclusive remarks and two problems regarding connectivity preservation and authority dispatch for future study.
Graduate

碩士
國立臺灣師範大學
科技應用與人力資源發展學系人力資源碩士在職進修專班
98
The main purpose of this study is to investigate the prediction of dispatched workers’ locus of control, organizational identification, and job satisfaction on their career success. We also discuss the mediating effects of job satisfaction and organizational identification between locus of control and career success. This study uses a questionnaire to conduct empirical research. The dispatched workers from the “B” dispatched employment company are the target population. A total of 168 questionnaires were sent out, and 120 returned were valid, with 81.08% response rate. The results and conclusions are as follows: 1 Internal control has significant positive influence on job satisfaction. 2 Internal control has significant positive influence on organizational identification 3 Job satisfaction has significant positive influence on career success 4 Organizational identification has significant positive influence on career success 5 Job satisfaction has a partial mediating effect between internal control and career success. 6 Organizational identification has a partial mediating effect between internal control and career success.

Introduction Colour codes are used extensively in railways to convey specific information governing movement of trains and equipment on the track. One such task is the railway traffic control display that uses colour coded video display terminals (VDTs) to convey information of the signal status, train movements and track status to the railway dispatcher. Because individuals with colour vision deficiencies (colour-defectives) may have problems with these colour-related tasks, questions were raised about the suitability of colour vision defectives to work as railway dispatchers. In order to answer that, a VDT based Dispatch Colour Vision Test based on the actual railway traffic display was developed previously. Purpose The main purpose of this thesis is to establish the pass/fail scores and repeatability of the VDT based Dispatch Colour Vision Test that resulted from the previous work. Secondly, the study will also examine whether clinical colour vision tests can predict the performance on the practical task. Methods The Dispatch colour vision test was divided into three parts based on the colour sets that the dispatcher had to recognize. The testing computer system used the the same RGB colour settings, graphics card and monitor as in railway dispatch centres. Subjects viewed the display colours and entered their responses by using a mouse. One hundred colour-normals and fifty two colour-defectives participated in the initial session. The test was repeated approximately after 10 days. Ninety three colour-normals (93%) and 44 (85%) colour-defectives participated in the second session. The total number of errors and time to complete the test was recorded. Results Pass/Fail on the VDT Dispatch colour vision test was based on colour-normal errors. Ignoring orange-red errors, two errors were allowed in the first session and one error was allowed in the second session. Based on this criterion, 42% of colour vision defectives could perform as well as colour normal subjects. The kappa coefficient of agreement between the sessions for the colour-defectives was 0.85. Detailed analysis between the colour differences and the errors showed only a weak correlation between the two. However, the general trend was that colour-defectives made more errors on colours that were near or along the same lines of confusions and the colours were nearly equal in luminance. Nevertheless, the interaction between luminance and location with respect to the lines of confusion was not easy to interpret. The time to complete the task for the colour-defectives who passed the test took 14% longer than colour-normals and colour-defectives who failed took 30% longer than colour-normals. All groups showed a similar learning effect with an 18% reduction in mean times to complete the task at the second session. There was no significant correlation between the number of errors and time to complete or the clinical tests and completion times for any of the groups. Clinical colour vision tests have limited value in predicting performance of colour-defectives on the Dispatch test. Logistic analysis results showed that the Farnsworth D-15 along with the Nagel was the best predictor of the VDT Dispatch colour test pass/fail results. However, these results were similar to using the Farnsworth D-15 test alone. Ninety-five percent of the individuals who failed the Farnsworth D-15 also failed the Dispatch test. However, approximately 25% of the individuals who passed the Farnsworth D-15 failed the VDT Dispatch colour test which is an unacceptable false negative rate. These results indicate the Farnsworth D-15 can only be used to predict who is likely to fail the dispatch test. Conclusions Forty two percent of colour vision defectives could perform as well as colour-normals in identifying VDT railway display colours and time to complete the task. Clinical colour vision tests were inadequate predictors of performance in practical task, overall. However, the Farnsworth D-15 was a very good predictor of who would fail the VDT Dispatch test. Hence a practical VDT Dispatch test may be needed to test individuals who would want to work as railway dispatchers.

碩士
義守大學
電機工程研究所
85
A cogeneration system can simultaneously provide with heat and electricity, increase the energy efficiency, decrease the transmission loss, and upgrade the system reliability. From the load management viewpoints, a suitable strategy for the control and operation of a cogeneration system is playing an important role nowadays. However, for those cogeneration systems with multi-fuels, multi-boilers and multi-generators, an optimal decision regarding the increase of the amount of generation and decrease of the heat cost has not been well investigated. A research project on this topic is thus motivated. In this study, the neural network approach combining with the optimization technique will be proposed to the economic operation of cogeneration and the related boilers. The cogeneration plant data including the steam generators and boiler systems will be first collected and stored in the database. By curve fitting methods, these data will be served to find appropriate mathematical models of the generator and boiler performance curves. This is followed by an optimization-based approach activated to reach optimal decisions for steering neural networks in search of boiler heat prediction and economic generation dispatch. A cross-validation technique will be also employed to validate the effectiveness of the trained neural networks. To validate the effectiveness of the proposed method, the approach will be applied to the economic operation of cogeneration systems of Chinese Petroleum Company (CPC), where the current system has four steam generator sets and four boilers in a cogeneration plant. The proposed method has been compared with current strategy used in CPC operation based on the operation cost and efficiency. The test results demonstrated the effectiveness of the method for the applications.

This research focuses on improving the efficiency of power market operations by providing system operators additional tools for managing the costs of supplying and delivering electricity. A transmission topology control (TC) framework for production cost reduction based on a shift factor (SF) representation of branch and breaker flows is proposed. The framework models topology changes endogenously while maintaining linearity in the overall Mixed Integer Linear Programming (MILP) formulation. This work develops the DC lossless, and loss-adjusted TC formulations that can be used in a Day Ahead or intra-day market framework as well as an AC-based model that can be used in operational settings. Practical implementation choices for the Shift Factor formulation are discussed as well as the locational marginal prices (LMPs) under the TC MIP setting and their relation to LMPs without TC. Compared to the standard B-theta alternative used so far in TC research, the shift factor framework has significant computational complexity advantages, particularly when a tractably small switchable set is optimized under a representative set of contingency constraints. These claims are supported and elaborated by numerical results.

碩士
國立勤益科技大學
電機工程系
99
Under the circumstances of petroleum resources in dwindling and the trend of consciousness of environmental protection rising up, clean, non-contaminated and inexhaustible energy source is in urgent need. Thus, the development and application of the renewable energy become one of the most important studies that every country is engaging in as well as putting it the primary energy policy in consideration in recently years. The integration of renewable energy into an independent power system shall be populated in the near future. For this, the main purpose of the thesis is to develop a dispatch and monitoring-control system of the hybrid renewable energy based micro grid, which includes a wind turbine and solar cell; in the mean time, a highly mobilized and widely applicable micro turbine was adopted as well. Further, an operation strategy for the purpose of back-up power supply is derived. The renewable energies are optimally dispatched in the normal condition. In case the utility is in abnormal or interrupted, the overall hybrid power system is ensured to keep the power loading in demand, so the operation can be run steadily. The constructed dispatch and monitoring-control system of the integrated hybrid power system is able to operate in grid-connected mode or independent operation mode. In grid-connected mode, the renewable energy is adapted as primary power supply of loading. When the power generated by renewable energy is larger than the demand, it can be feedback to the power company. If the loading demand increases or external environmental factor results in insufficient output power, the micro turbines shall be adopted for the backup in power supply for the balance management of power system. It can be a useful reference for the overall design and operation in planning and integrating the hybrid power system derived from renewable energy.

碩士
國立中山大學
電機工程學系研究所
90
In recent years, the insufficient supply of electricity on ruch hours has not simply led to negative impact on hi-tech industries, but also impeded the normal operation of industries, such as factories, medical centers, hotel business, public administration organization, schools and so on. The most important thing we have to do is to come up with a solution to such a dilemma. This thesis is to propose a better way and suggestion for the places with high frequent operation of medium, large size air conditioner units, which achieves to make efficient use of energy. Generally speaking, such kind users lack sufficient knowledge concerning chillers equipments, pipe system, automatic control circuit, energy saving equipment. In addition, air conditioner industries do not care about such awareness of technology research of power demand, energy saving, and under power limited pressure. Therefore, this thesis also attempts to find a solution to the problems. Moreover, this thesis mainly makes use of graphic control software to assess actual various parameters with load capacity control, efficiency consume energy, and economic dispatch, and then to get into units system load monitor model management. Hopefully, such model and analysis of the experiment could be regarded as an efficient technique applied into actual units distribution monitor, and furthermore, would provide parallel medium, large air conditioner chiller units with not simply deeper discussion but also more efficient solution to the goal of energy saving.

碩士
國立臺灣科技大學
電機工程系
95
Due to the rapid increasing of energy price, the importance of electricity supervisory control and demand side management will get more and more attention. For the university campus, traditional electricity management systems only takes the whole campus as a single user. The individual department doesn’t have incentives to encourage its self energy reduction. Besides, the electricity bill sharing mechanism usually doesn’t take the over-demand charge into consideration. In this thesis, an optimal power demand dispatch method based on the market-oriented programming technique is developed. And its application platform based on a campus power supervisory control system is also presented. The research consists of establishing an integrated electricity power supervisory control system, modeling of power usage pattern for campus departments, and development of the optimal demand dispatch method. Through this research, the feasibility of switching campus power management system from central control to distributed control is also investigated. In the future, when the utility company deploys the demand response management, the optimal demand dispatch method can also be applied to multi-user demand dispatch applications.

abstract: The prevalence of renewable generation will increase in the next several decades and offset conventional generation more and more. Yet this increase is not coming without challenges. Solar, wind, and even some water resources are intermittent and unpredictable, and thereby create scheduling challenges due to their inherent “uncontrolled” nature. To effectively manage these distributed renewable assets, new control algorithms must be developed for applications including energy management, bridge power, and system stability. This can be completed through a centralized control center though efforts are being made to parallel the control architecture with the organization of the renewable assets themselves—namely, distributed controls. Building energy management systems are being employed to control localized energy generation, storage, and use to reduce disruption on the net utility load. One such example is VOLTTRONTM, an agent-based platform for building energy control in real time. In this thesis, algorithms developed in VOLTTRON simulate a home energy management system that consists of a solar PV array, a lithium-ion battery bank, and the grid. Dispatch strategies are implemented to reduce energy charges from overall consumption ($/kWh) and demand charges ($/kW). Dispatch strategies for implementing storage devices are tuned on a month-to-month basis to provide a meaningful economic advantage under simulated scenarios to explore algorithm sensitivity to changing external factors. VOLTTRON agents provide automated real-time optimization of dispatch strategies to efficiently manage energy supply and demand, lower consumer costs associated with energy usage, and reduce load on the utility grid.
Dissertation/Thesis
Masters Thesis Engineering 2015

Uruguay is a pioneer in the use of renewable sources of energy and can usually satisfy its total demand from renewable sources. Control and optimization of the system is complicated by half of the installed power - wind and solar sources - be- ing non-controllable with high uncertainty and variability. In this work we present a novel optimization technique for efficient use of the production facilities. The dy- namical system is stochastic, and we deal with its non-Markovian dynamics through a Lagrangian relaxation. Continuous-time optimal control and value function are found from the solution to a sequence of Hamilton-Jacobi-Bellman partial differential equations associated with the system. We introduce a monotone scheme to avoid spurious oscillations in the numerical solution and apply the technique to a number of examples taken from the Uruguayan grid. We use parallelization and change of variables to reduce the computational times. Finally, we study the usefulness of extra system storage capacity offered by batteries.

碩士
國立中正大學
電機工程研究所
107
This thesis develops an underfrequency control strategy for island power systems. First, the proposed control strategy uses the frequency nadir forecasting module to analyze the frequency stability under largest diesel generator tripping (N-1) contingency events. If predicted frequency nadir is too low, four frequency support methods are then analyzed and used for solving potential frequency stability problem. They include generator re-dispatch (GR), the use of battery energy storage system (BESS), direct load control (DLC), and emergency demand response program (EDRP). In terms of the GR method, the optimal diesel generator dispatch is obtained, with sufficient frequency stability and minimal fuel cost and start-up cost. In the BESS method, the optimal instantaneous power output from BESS is obtained based on its frequency support capability. With the DLC and EDRP method, the optimal contract-based load-shedding and load-reduction to provide frequency support are obtained, respectively. Then, the operating costs and capacity requirements of each method to support frequency are analyzed. The research methods and simulation results are very useful to the low-frequency protection of actual power systems.

碩士
國立臺北科技大學
電資碩士班
96
This thesis is to take the Keelung Area Dispatch Control System for the improvement object about re-establishment and design of a stand-alone simulation dispatch system. It provided for the direction of improvement for portability and modular aspect in the SCADA system ; In the software , the establishment method requires simplification and harmonization of standards rather than using artificially ways to create that no simplification and standards.So we use the separation principles and TRIZ''s contradiction matrix about 39 to improve ,and seek to improve the degradation characteristics of factor analysis with the 40 principles of the invention can improve , implement the methods and key ingredients. However, the key elements and methods will convert into an executable and effective in the SCADA. In the drawing, it will induct the dendritic structure in the search way ,and let’s to be possible to pursue fast the dispatch’s drawing so much , the equipment and the display status in the establishment will not have the redundant situation , and make the dispatch’s drawing simplification and perspicuity. After the fact confirms, the drawing uniformity causes the overall drawing to be more complete, and takes YiFu substation for a confirmation example. We will connect from SCADA to RTU in YiFu substation , the improvement effect is emarkable ,and we may promote above 95% in the key technologies , our goal can help to maintain and establish these work in the future.

碩士
國立彰化師範大學
工業教育與技術學系
104
In this research, the technology teaching oriented green energy is merged into fossil fuel energy for better power supply transmission system. Power monitoring and intelligent power deployment control are also introduced in this distributed generation system. The system utilizes LabVIEW to design a monitoring and control system including power transmission monitoring, consumption monitoring, power analysis and intelligent control; furthermore, the intelligent power control is deployed for integrating green power into system. LabVIEW that is a graphical language with possessing advantages of simple operation and easy understanding is used to design the functions of monitoring, control and analysis for power generation, transmission and consuming status among different situations including if using transformer and under different load. The completing of this research, the method, theory and practical technique of green power monitoring and intelligent power deployment are understood, constructed, and training demonstration with evaluation is proceeded for learning effectiveness.

博士
國立中正大學
電機工程研究所
88
This dissertation proposes a new voltage control model using fuzzy sets and a new Hopfield neural network model based approach for the economic dispatch problem of power systems. First, as the voltage profile of electric power systems could be constantly affected, either by the variations of load or by the changes of network configuration, a real time control taken by the utility is required to fast alleviate the problems caused by the perturbations. In the proposed method, linguistic variables are applied to measure the proximity of a given quantity to a certain condition to be satisfied. Both bus voltage violation level and controlling ability of controlling devices are first translated into fuzzy set notations, then through fuzzy operations it could fast find the answer for the realistic question. The proposed approach is simple and straightforward, which defines the membership functions of the linguistic variables ingeniously, so that the merits of fuzzy technique are brought into play. Simulation results reveal that this method is quite effective and feasible to real-time voltage control of power systems. Secondly, this dissertation presents a new Hopfield model based approach for the economic dispatch problem of power systems. To solve the economic dispatch problem using the Hopfield model, an energy function composing power mismatch, total fuel cost and transmission line losses is defined. Each term of the energy function is multiplied by a weighting factor representing the relative importance of that term. Instead of applying the conventional sigmoidal neuron model, we employ a linear input-output model for the neuron. An analytic method is explored to find the corresponding weighting factors of the formulated energy function. The corresponding weighting factors are either appropriately selected or directly estimated according to the specified power mismatch. Which, however, are determined by trial and error in the conventional Hopfield method. To minimize the value of the energy function, the computational procedures including a series of adjusting the weighting factor associated with the transmission line losses and updating the unit generations and power losses are carried out. Because the weighting factors are governed by some relationships developed, adjustment of the weighting factor is much simpler and more effective in steadily achieving solutions than adjustment of the -multiplier in the lambda-iteration method for economic dispatch problems. Computational results reveal that the proposed approach can find accurate solutions more simply and fast compared with the conventional lambda-iteration method. Finally, this dissertation presents a new approach to economic dispatch problems using Hopfield model with the generalized generation shift distribution (GGSD) factor. The transmission loss is approximately expressed in terms of generating powers and the GGSD factor. Based on the above expressions, and by applying a linear model to describe the input-output relationship for the neuron, one can explore an analytic Hopfield method to economic dispatch problems. Two example systems exemplified the application of the proposed method. Computational results reveal that the proposed method has very fast computational solution speed and good solution accuracy. It can be applied to real-time economic dispatching.

碩士
國立中正大學
電機工程研究所
92
Moving forward from 20th century to 21st century, various industries around the world are promoting automation actively, from product design, manufacturing, production control, marketing, even office. The term “automation” implies high efficiency, mechanization, and even the symbol for advancement. Automation promoted by industries led to soar of productivity, assurance of product quality, effective control over production cost, and sustainable business of the company. In the trend of automation, power industry is definitely a par of it. The economic prosperity of the country, and continuous improvement of the living standard, the power demand has been on the rise. To respond to such high demand, Taiwan Power Company continued to add more generators, improve the power transmission and distribution system, and expand substations. The result of an enormous power system is difficulty in controlling the traditional dispatch operation. To improve the power system operation, Taiwan Power Company followed the global trend of automation, namely promoting the automation of power dispatch and control, using computer-aided control to solve the problems. Taiwan Power Company not only utilized equipment resources of the power system effectively but also achieved economic dispatch, minimization of power line loss, and improvement on power quality. In the past, the way of control streetlights in the cities of Taiwan was using the timer switch from the substation by concentrating control（about 75%）, in remote districts was using light activated switch control by sunlight illumination（about 25%）.Owing to the roads extended fast, lead to the amounts of streetlights were increasing quickly. But, Taipower who was responsible for the control on streetlights, on the contrary abridged manpower year by year for the policy of the transformation run by the local people. Checking and patrolling manpower was increasingly insufficient, and the equipments of control the streetlights outdated. Sometimes to cause the streetlights bright in the day but dark in the night. The results were that people lived inconvenient, power lost for no reason and a traffic accident happened, to endanger the public life and property. As the automation of power dispatch and control becomes a global trend. The research report is based on the completed organizational POWER SCADA (Supervisory Control and Data Acquisition) system for automated control on streetlights. From control center read the time parameter automatically instead of timer switch by using computer programs, and improve the equipments of control streetlights. Expecting to change the bad phenomenon radically on controlling streetlights, provide a stable lighting environment for people, and reduce the power line loss.

碩士
國立臺灣科技大學
電機工程系
92
This research uses PSS/E program to analyze the load surging process during the summer peak time period of 12:30~14:00. Before the dispatcher is going to operate the reactive equipment according to load increment, it’s necessary to evaluate the difference among the actual capacitor effect, line charging and line loss, and the difference is regarded as an operative index. In practice, reactive elements have dynamic capacitor effect, as the program can only analyze for a specific time point, but not simulate the accumulative effect that the dispatch time would act on the system voltage profile, so the incremental SC effect resulted from each operation should be modified to the least extent. Finally, combining the operative index and dispatch time effect, we then use dynamic programming tabular method to find the most adequate strategy for each time fraction as the dispatcher’s reference. Before the third extra-high voltage (EHV) transmission line was interconnected to Taipower system, each year during the summer peak period a large amount of power flow was transferred from central and south areas to north area via the other two EHV transmission lines, which would cause the system voltage profile seriously low. However, the system voltage profile is too high after the third EHV transmission line is in service. But if an N-2 contingency happens, the system voltage profile is still too low. Dynamic programming method can not only solve the low voltage profile problem, but solve the high voltage profile problem by the duality. It’s the main contribution of this research that can be adopted as the strategy reference for the dispatchers while controlling the trunk lines voltages and can also be very helpful for system planning engineers.

碩士
國立臺灣科技大學
電機工程系
96
For experiences of real-time voltage control in the power system, the dispatchers would utilize ways of putting in appropriate reactive power compensating devices and adjusting taps of the transformers to achieve expected voltage quality and to reduce the line loss of the systems. However, it will neglect frequent operations of on-and-off of those devices and may even cause further damage. The purpose of this research is to provide dispatchers with complete strategies to control system voltage in a right and fast manner. Firstly, the method of Linear Programming is applied to map out the taps that set by OLTCs of the transformers for the initial state. These strategies focus on prompt offering the dispatchers accurate and efficient methods to adjust system voltages. By way of doing so, the voltage can also be maintained within tolerance of equipment for the duration of dynamic operations, and so as to achieve the reduction of line loss. In this research, software PSS/E is used to simulate steady state of Taipower system, and then the methods are practically developed with Taipower system. Comparing both results, it can be seen that the methods would carry lower the numbers of operations of on-and-off of devices and reduce line loss of 0.09%. The result is proved to be helpful and valuable for the dispatchers with better alternatives of accurate, fast and safe operations.

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.
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Optimal transmission switching (OTS) enables us to remove selected transmission lines from service as a cost reduction method. A mixed integer programming (MIP) model has been proposed to solve the OTS problem based on the direct current optimal power flow (DCOPF) approximation. Previous studies indicated computational issues regarding the OTS problem and the need for a more accurate model. In order to resolve computational issues, especially in large real systems, the MIP model has been followed by some heuristics to find good, near optimal, solutions in a reasonable time. The line removal recommendations based on DCOPF approximations may result in poor choices to remove from service. We assess the quality of line removal recommendations that rely on DCOPF-based heuristics, by estimating actual cost reduction with the exact alternating current optimal power flow (ACOPF) model, using the IEEE 118-bus test system. We also define an ACOPF-based line-ranking procedure and compare the quality of its recommendations to those of a previously published DCOPF-based procedure. For the 118-bus system, the DCOPF-based line ranking produces poor quality results, especially when demand and congestion are very high, while the ACOPF-based heuristic produces very good quality recommendations for line removals, at the expense of much longer computation times. There is a need for approximations to the ACOPF that are accurate enough to produce good results for OTS heuristics, but fast enough for practical use for OTS decisions.

Variable generator output levels from renewable energies is an important technical obstacle to the transition from fossil fuels to renewable resources. Super grids and smart grids are among the most effective solutions to mitigate generation variability. In a super grid, electric utilities within an interconnected system can share generation and reserve units so that they can produce electricity at a lower overall cost. Smart grids, in particular demand response programs, enable flexible loads such as plug-in electric vehicles and HVAC systems to consume electricity preferntially in a grid-friendly way that assists the grid operator to maintain the power balance. These solutions, in conjunction with energy storage systems, can facilitate renewable integration. This study aims to provide an understanding of the achievable benefits from integrating demand response into wholesale and retail electricity markets, in particular in the presence of significant amounts of variable generation. Among the options for control methods for demand response, market-based approaches provide a relatively efficient use of load flexibility, without restricting consumers' autonomy or invading their privacy. In this regard, a model of demand response integration into bulk electric grids is presented to study the interaction between variable renewables and demand response in the double auction environment, on an hourly basis. The cost benefit analysis shows that there exists an upper limit of renewable integration, and that additional solutions such as super grids and/or energy storage systems are required to go beyond this threshold. The idea of operating an interconnection in an unified (centralized) manner is also explored. The traditional approach to the unit commitment problem is to determine the dispatch schedule of generation units to minimize the operation cost. However, in the presence of price-sensitive loads (market-based demand response), the maximization of economic surplus is a preferred objective to the minimization of cost. Accordingly, a surplus-maximizing hour-ahead scheduling problem is formulated, and is then tested on a system that represents a 20-area reduced model of the North America Western Interconnection for the planning year 2024. The simulation results show that the proposed scheduling method reduces the total operational costs substantially, taking advantage of renewable generation diversity. The value of demand response is more pronounced when ancillary services (e.g. real-time power balancing and voltage/frequency regulation) are also included along with basic temporal load shifting. Relating to this, a smart charging strategy for plug-in electric vehicles is developed that enables them to participate in a 5-minute retail electricity market. The cost reduction associated with implementation of this charging strategy is compared to uncontrolled charging. In addition, an optimal operation method for thermostatically controlled loads is developed that reduces energy costs and prevents grid congestion, while maintaining the room temperature in the comfort range set by the consumer. The proposed model also includes loads in the energy imbalance market. The simulation results show that market-based demand response can contribute to a significant cost saving at the sub-hourly level (e.g. HVAC optimal operation), but not at the super-hourly level. Therefore, we conclude that demand response programs and super grids are complementary approaches to overcoming renewable generation variation across a range of temporal and spatial scales.
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