Real-time Energy Resource Scheduling considering a Real Portuguese Scenario

The development in power systems and the introduction of decentralized generation and Electric Vehicles (EVs), both connected to distribution networks, represents a major challenge in the planning and operation issues. This new paradigm requires a new energy resources management approach which considers not only the generation, but also the management of loads through demand response programs, energy storage units, EVs and other players in a liberalized electricity markets environment. This paper proposes a methodology to be used by Virtual Power Players (VPPs), concerning the energy resource scheduling in smart grids, considering day-ahead, hour-ahead and real-time scheduling. The case study considers a 33-bus distribution network with high penetration of distributed energy resources. The wind generation profile is based on a real Portuguese wind farm. Four scenarios are presented taking into account 0, 1, 2 and 5 periods (hours or minutes) ahead of the scheduling period in the hour-ahead and realtime scheduling.

A New Heuristic Providing an Effective Initial Solution for a Simulated Annealing approach to Energy Resource Scheduling in Smart Grids

An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.

Energia Solar Fotovoltaica como Fonte Alternativa de Produção de Energia Elétrica em Angola

Neste trabalho é efetuado o dimensionamento de sistemas fotovoltaicos para serem instalados em edificações localizadas em Angola com o objetivo de analisar a produção de energia elétrica através de sistemas fotovoltaicos. Utilizando o software PVsyst na versão 6.3.2 foram dimensionados três sistemas fotovoltaicos, dois sistemas destinados a ser instalados numa residência, um ligado à rede e o outro autónomo e por fim um sistema fotovoltaico ligado à rede para uma instalação industrial. A determinação dos custos de investimento nos três sistemas foi obtida de forma aproximada, tendo como base preços dos equipamentos no mercado Português e considerando os custos de importação de mercadorias no mercado Angolano. Para os sistemas ligados à rede é analisada a rentabilidade financeira do investimento durante o período de vida útil dos módulos fotovoltaicos considerando três cenários distintos. No primeiro cenário o valor da remuneração pela energia vendida pelo produtor é igual ao valor pago pela energia comprada. No segundo e terceiros cenário de análise económica pretende-se encontrar uma tarifa de energia que torne o investimento rentável com um período de amortização de 7 e 12 anos respetivamente.

Wireless GPS-based phase-locked synchronization system for outdoor environment.

Synchronization of data coming from different sources is of high importance in biomechanics to ensure reliable analyses. This synchronization can either be performed through hardware to obtain perfect matching of data, or post-processed digitally. Hardware synchronization can be achieved using trigger cables connecting different devices in many situations; however, this is often impractical, and sometimes impossible in outdoors situations. The aim of this paper is to describe a wireless system for outdoor use, allowing synchronization of different types of - potentially embedded and moving - devices. In this system, each synchronization device is composed of: (i) a GPS receiver (used as time reference), (ii) a radio transmitter, and (iii) a microcontroller. These components are used to provide synchronized trigger signals at the desired frequency to the measurement device connected. The synchronization devices communicate wirelessly, are very lightweight, battery-operated and thus very easy to set up. They are adaptable to every measurement device equipped with either trigger input or recording channel. The accuracy of the system was validated using an oscilloscope. The mean synchronization error was found to be 0.39 μs and pulses are generated with an accuracy of <2 μs. The system provides synchronization accuracy about two orders of magnitude better than commonly used post-processing methods, and does not suffer from any drift in trigger generation.

Power to Gas - sähköenergiasta luonnonkaasua, liiketoimintamahdollisuudet Suomessa

Uusiutuvan sähköntuotannon osuuden kasvaessa kasvaa tarve tasata sähköntuotannon ja kulutuksen vaihteluita varastoimalla sähköä. Power to Gas (PtG) - sähköenergiasta luonnonkaasua tarjoaa yhden mahdollisuuden varastoida sähköä. Sähköä käytetään veden elektrolyysiin, jossa syntynyt vety käytetään metanoinissa yhdessä hiilidioksidin kanssa muodostamaan korvaavaa luonnonkaasua. Näin syntynyttä korvaava luonnonkaasua sähköstä kutsutaan e-SNG-kaasuksi. Tässä työssä tutkitaan PtG-laitoksen investointi, käyttö- ja kunnossapitokuluja. Työssä luodaan laskentamalli, jolla lasketaan PtG-laitoksen neljälle käyttötapaukselle kannattavuuslaskelma. Käyttötapauksille lasketaan myös herkkyystarkasteluja. Kannattavuuslaskelmien perusteella päätellään PtG-laitoksen liiketoimintamahdollisuudet Suomessa. Työssä laskettujen kannattavuuslaskelmien perusteella PtG-laitoksen perustapausten liiketoimintamahdollisuudet ovat huonot. Laskettujen herkkyystarkastelujen perusteella havaittiin, että investointikulut, laitoksen ajoaika ja lisätulot hapesta ja lämmöstä ovat kannattavuuden kannalta kriittisimmät menestystekijät.

Niagara-Welland Power Company Limited fonds, 1833, 1852, 1904-1906, 1909, n.d.

The Welland Power and Supply Canal Company Limited, established in 1893 and incorporated in 1894 with a capital stock of $500,000. The aim of the company was to harness the natural water supply of the Niagara and Welland Rivers. In 1898 the Canadian Electrical News published a report by Henry Symons, QC outlining the main project of the company. This project involves the construction of a canal from the Welland River to the brow of the mountain at Thorold, a distance of 8 miles; the construction at Thorold of a power house, and from Thorold to Lake Ontario, a raceway by which to carry water into the lake. The estimate for the machinery to generate 100,000 horse power is £125,000; for transmission line to Toronto at a voltage of 10,000….The total estimate therefore amounts to £2,452,162, or roughly speaking, $12,000,000. Source: Canadian Electrical News, August 1898, p. 172. In 1899 the company officers petitioned the federal government desiring a name change to the Niagara-Welland Power Company Limited. Officers of the company were Harry Symons, President; Charles A. Hesson, Vice-President; and M.R. O’Loughlin, James B. Sheehan, James S. Haydon, Frederick K. Foster, directors; John S. Campbell, secretary-treasurer. The company’s head offices were located in St. Catharines, with a New York (City) office on Broad Street. In 1905 and 1909 the company petitioned the federal government for additional time to construct its works, which was granted. The company had until May 16, 1915 to complete construction. John S. Campbell (1860-1950) was a graduate of the University of Toronto and Osgoode Hall. During his university years John began his military career first in "K" Company, Queens Own rifles and then later as Commanding Officer of the 19th Lincoln Regiment, from 1906 to 1910. Upon his return to St. Catharines John Campbell served as secretary in the St. Catharines Garrison Club, a social club for military men begun in 1899. After being called to the Bar, he became a partner in the firm of Campbell and McCarron and was appointed to the bench in 1916, serving until retirement in 1934. Judge Campbell served as an alderman for several terms and was the mayor of St. Catharines in 1908 and 1909. He also served as the first chairman of the St. Catharines Public Utilities in 1914. John S. Campbell was married to Elizabeth Oille, daughter of Jerome B. and Charlotte (St. John) Oille. The family home "Cruachan" was located at 32 Church St.

Hydro Electric Commission of Niagara Falls Ontario Scrapbook, 1936-1939, 1943-1951

Sir Adam Beck ( a London, Ontario manufacturer, Mayor and Conservative member of the provincial legislature) was a champion of municipal and provincial power ownership. Beck become the “Power Minister” and chairman of the Hydro-Electric Power Commission of Ontario which was the world’s first publicly owned utility. In 1925 the first unit of the Hydro Electric Power Commission’s Queenston Chippawa hydro-electric development on the Niagara River went into service. The station was renamed in 1950 as “Sir Adam Beck #1”. This marked the 25th anniversary of Beck’s death. This is one of 2 generating stations in Niagara Falls. There is also Adam Beck Plant #2. The Niagara generating stations supply one quarter of all power used in New York State and Ontario.Ontario Hydro has two water tunnels which traverse the entire City of Niagara Falls from the Village of Chippawa in the South to the Sir Adam Beck Hydro Electric Generating Stations in the North. Also they are in the process of building the third tunnel. In addition, Ontario Hydro has a 13.6 km open canal which traverses the entire City of Niagara Falls. Source: http://www.hydroone.com/OurCompany/Pages/OurHistory.aspx

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

Development Planning at the State Level in India - A Case Study with Reference to Kerala, 1957-'84

This thesis entitled “Development planning at the state level in india a case study with reference to kerala1957-84.Planning in India is a concurrent subject with the Centre and the States having well-defined domains of jurisdiction with regard to planning functions and sources of resource mobilisation.The genesis of the lack of academic interest in state level planning is in the widely held belief that in the extent scheme of Centre-State economic relations, the states have little scope for initiative in planning.Both at the theoretical and empirical levels, Kerala has attached very great importance to planning.It has been the localeof wide and deep discussions on the various dimensions of planning.In Kerala's development process, the leading sector consists of social services such as education and public healthOne point that needs special emphasis in this regard is that the high demand for education in Kerala cannot be attributed to the Keralites' ‘unique urge‘ for education. Rather, it is related to the very high level of unemployment in the state (Kerala has the highest level of unemployment in the country.In resource allocation under the Five Year Plans, Kerala attached the highest weightage to power generation, hydro-electric projects being the major source of power in the state. Nearly one-fourth of the plan resources has been claimed by hydro-electric projects.In the agricultural sector, Kera1a's level of productive use of electric power is one of the lowest.As is evident.from above, planning in Kerala has not enabled us to solve the basic problems of the state. More 'scientific' planning in the sense of applying mre sophisticated planning techniques is obviously not the answer. It, on the contrary, consists of more fundamental changes some of which can be brought about through an effective use of measures well within the power of the State Government.

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

Reinforcement Learning solution for Unit Commitment Problem through pursuit method

Unit commitment is an optimization task in electric power generation control sector. It involves scheduling the ON/OFF status of the generating units to meet the load demand with minimum generation cost satisfying the different constraints existing in the system. Numerical solutions developed are limited for small systems and heuristic methodologies find difficulty in handling stochastic cost functions associated with practical systems. This paper models Unit Commitment as a multi stage decision task and Reinforcement Learning solution is formulated through one efficient exploration strategy: Pursuit method. The correctness and efficiency of the developed solutions are verified for standard test systems

Szenarien zur zukünftigen Stromversorgung, kostenoptimierte Variationen zur Versorgung Europas und seiner Nachbarn mit Strom aus erneuerbaren Energien

Sowohl die Ressourcenproblematik als auch die drohenden Ausmaße der Klimaänderung lassen einen Umstieg auf andere Energiequellen langfristig unausweichlich erscheinen und mittelfristig als dringend geboten. Unabhängig von der Frage, auf welchem Niveau sich der Energiebedarf stabilisieren lässt, bleibt dabei zu klären, welche Möglichkeiten sich aus technischer und wirtschaftlicher Sicht in Zukunft zur Deckung unseres Energiebedarfs anbieten. Eine aussichtsreiche Option besteht in der Nutzung regenerativer Energien in ihrer ganzen Vielfalt. Die Arbeit "Szenarien zur zukünftigen Stromversorgung, kostenoptimierte Variationen zur Versorgung Europas und seiner Nachbarn mit Strom aus erneuerbaren Energien" konzentriert sich mit der Stromversorgung auf einen Teilaspekt der Energieversorgung, der zunehmend an Wichtigkeit gewinnt und als ein Schlüssel zur nachhaltigen Energieversorgung interpretiert werden kann. Die Stromversorgung ist heute weltweit für etwa die Hälfte des anthropogenen CO2-Ausstoßes verantwortlich. In dieser Arbeit wurden anhand verschiedener Szenarien Möglichkeiten einer weitgehend CO2–neutralen Stromversorgung für Europa und seine nähere Umgebung untersucht, wobei das Szenariogebiet etwa 1,1 Mrd. Einwohner und einen Stromverbrauch von knapp 4000 TWh/a umfasst. Dabei wurde untersucht, wie die Stromversorgung aufgebaut sein sollte, damit sie möglichst kostengünstig verwirklicht werden kann. Diese Frage wurde beispielsweise für Szenarien untersucht, in denen ausschließlich heute marktverfügbare Techniken berücksichtigt wurden. Auch der Einfluss der Nutzung einiger neuer Technologien, die bisher noch in Entwicklung sind, auf die optimale Gestaltung der Stromversorgung, wurde anhand einiger Beispiele untersucht. Die Konzeption der zukünftigen Stromversorgung sollte dabei nach Möglichkeit objektiven Kriterien gehorchen, die auch die Vergleichbarkeit verschiedener Versorgungsansätze gewährleisten. Dafür wurde ein Optimierungsansatz gewählt, mit dessen Hilfe sowohl bei der Konfiguration als auch beim rechnerischen Betrieb des Stromversorgungssystems weitgehend auf subjektive Entscheidungsprozesse verzichtet werden kann. Die Optimierung hatte zum Ziel, für die definierte möglichst realitätsnahe Versorgungsaufgabe den idealen Kraftwerks- und Leitungspark zu bestimmen, der eine kostenoptimale Stromversorgung gewährleistet. Als Erzeugungsoptionen werden dabei u.a. die Nutzung Regenerativer Energien durch Wasserkraftwerke, Windenergiekonverter, Fallwindkraftwerke, Biomassekraftwerke sowie solare und geothermische Kraftwerke berücksichtigt. Abhängig von den gewählten Randbedingungen ergaben sich dabei unterschiedliche Szenarien. Das Ziel der Arbeit war, mit Hilfe unterschiedlicher Szenarien eine breite Basis als Entscheidungsgrundlage für zukünftige politische Weichenstellungen zu schaffen. Die Szenarien zeigen Optionen für eine zukünftige Gestaltung der Stromversorgung auf, machen Auswirkungen verschiedener – auch politischer – Rahmenbedingungen deutlich und stellen so die geforderte Entscheidungsgrundlage bereit. Als Grundlage für die Erstellung der Szenarien mussten die verschiedenen Potentiale erneuerbarer Energien in hoher zeitlicher und räumlicher Auflösung ermittelt werden, mit denen es erstmals möglich war, die Fragen einer großräumigen regenerativen Stromversorgung ohne ungesicherte Annahmen anhand einer verlässlichen Datengrundlage anzugehen. Auch die Charakteristika der verschiedensten Energiewandlungs- und Transportsysteme mussten studiert werden und sind wie deren Kosten und die verschiedenen Potentiale in der vorliegenden Arbeit ausführlich diskutiert. Als Ausgangsszenario und Bezugspunkt dient ein konservatives Grundszenario. Hierbei handelt es sich um ein Szenario für eine Stromversorgung unter ausschließlicher Nutzung erneuerbarer Energien, die wiederum ausschließlich auf heute bereits entwickelte Technologien zurückgreift und dabei für alle Komponenten die heutigen Kosten zugrundelegt. Dieses Grundszenario ist dementsprechend auch als eine Art konservative Worst-Case-Abschätzung für unsere Zukunftsoptionen bei der regenerativen Stromversorgung zu verstehen. Als Ergebnis der Optimierung basiert die Stromversorgung beim Grundszenario zum größten Teil auf der Stromproduktion aus Windkraft. Biomasse und schon heute bestehende Wasserkraft übernehmen den überwiegenden Teil der Backup-Aufgaben innerhalb des – mit leistungsstarker HGÜ (Hochspannungs–Gleichstrom–Übertragung) verknüpften – Stromversorgungsgebiets. Die Stromgestehungskosten liegen mit 4,65 €ct / kWh sehr nahe am heute Üblichen. Sie liegen niedriger als die heutigen Preisen an der Strombörse. In allen Szenarien – außer relativ teuren, restriktiv ”dezentralen” unter Ausschluss großräumig länderübergreifenden Stromtransports – spielt der Stromtransport eine wichtige Rolle. Er wird genutzt, um Ausgleichseffekte bei der dargebotsabhängigen Stromproduktion aus erneuerbaren Quellen zu realisieren, gute kostengünstige Potentiale nutzbar zu machen und um die Speicherwasserkraft sowie die dezentral genutzte Biomasse mit ihrer Speicherfähigkeit für großräumige Backup-Aufgaben zu erschließen. Damit erweist sich der Stromtransport als einer der Schlüssel zu einer kostengünstigen Stromversorgung. Dies wiederum kann als Handlungsempfehlung bei politischen Weichenstellungen interpretiert werden, die demnach gezielt auf internationale Kooperation im Bereich der Nutzung erneuerbarer Energien setzen und insbesondere den großräumigen Stromtransport mit einbeziehen sollten. Die Szenarien stellen detaillierte und verlässliche Grundlagen für wichtige politische und technologische Zukunftsentscheidungen zur Verfügung. Sie zeigen, dass bei internationaler Kooperation selbst bei konservativen Annahmen eine rein regenerative Stromversorgung möglich ist, die wirtschaftlich ohne Probleme zu realisieren wäre und verweisen den Handlungsbedarf in den Bereich der Politik. Eine wesentliche Aufgabe der Politik läge darin, die internationale Kooperation zu organisieren und Instrumente für eine Umgestaltung der Stromversorgung zu entwickeln. Dabei kann davon ausgegangen werden, dass nicht nur ein sinnvoller Weg zu einer CO2–neutralen Stromversorgung beschritten würde, sondern sich darüber hinaus ausgezeichnete Entwicklungsperspektiven für die ärmeren Nachbarstaaten der EU und Europas eröffnen.

Economics of Hybrid Photovoltaic Power Plants

The global power supply stability is faced to several severe and fundamental threats, in particular steadily increasing power demand, diminishing and degrading fossil and nuclear energy resources, very harmful greenhouse gas emissions, significant energy injustice and a structurally misbalanced ecological footprint. Photovoltaic (PV) power systems are analysed in various aspects focusing on economic and technical considerations of supplemental and substitutional power supply to the constraint conventional power system. To infer the most relevant system approach for PV power plants several solar resources available for PV systems are compared. By combining the different solar resources and respective economics, two major PV systems are identified to be very competitive in almost all regions in the world. The experience curve concept is used as a key technique for the development of scenario assumptions on economic projections for the decade of the 2010s. Main drivers for cost reductions in PV systems are learning and production growth rate, thus several relevant aspects are discussed such as research and development investments, technical PV market potential, different PV technologies and the energetic sustainability of PV. Three major market segments for PV systems are identified: off-grid PV solutions, decentralised small scale on-grid PV systems (several kWp) and large scale PV power plants (tens of MWp). Mainly by application of ‘grid-parity’ and ‘fuel-parity’ concepts per country, local market and conventional power plant basis, the global economic market potential for all major PV system segments is derived. PV power plant hybridization potential of all relevant power technologies and the global power plant structure are analyzed regarding technical, economical and geographical feasibility. Key success criteria for hybrid PV power plants are discussed and comprehensively analysed for all adequate power plant technologies, i.e. oil, gas and coal fired power plants, wind power, solar thermal power (STEG) and hydro power plants. For the 2010s, detailed global demand curves are derived for hybrid PV-Fossil power plants on a per power plant, per country and per fuel type basis. The fundamental technical and economic potentials for hybrid PV-STEG, hybrid PV-Wind and hybrid PV-Hydro power plants are considered. The global resource availability for PV and wind power plants is excellent, thus knowing the competitive or complementary characteristic of hybrid PV-Wind power plants on a local basis is identified as being of utmost relevance. The complementarity of hybrid PV-Wind power plants is confirmed. As a result of that almost no reduction of the global economic PV market potential need to be expected and more complex power system designs on basis of hybrid PV-Wind power plants are feasible. The final target of implementing renewable power technologies into the global power system is a nearly 100% renewable power supply. Besides balancing facilities, storage options are needed, in particular for seasonal power storage. Renewable power methane (RPM) offers respective options. A comprehensive global and local analysis is performed for analysing a hybrid PV-Wind-RPM combined cycle gas turbine power system. Such a power system design might be competitive and could offer solutions for nearly all current energy system constraints including the heating and transportation sector and even the chemical industry. Summing up, hybrid PV power plants become very attractive and PV power systems will very likely evolve together with wind power to the major and final source of energy for mankind.

Advanced Nuclear Energy Systems: Heat Transfer Issues and Trends

Almost 450 nuclear power plants are currently operating throughout the world and supplying about 17% of the world’s electricity. These plants perform safely, reliably, and have no free-release of byproducts to the environment. Given the current rate of growth in electricity demand and the ever growing concerns for the environment, the US consumer will favor energy sources that can satisfy the need for electricity and other energy-intensive products (1) on a sustainable basis with minimal environmental impact, (2) with enhanced reliability and safety and (3) competitive economics. Given that advances are made to fully apply the potential benefits of nuclear energy systems, the next generation of nuclear systems can provide a vital part of a long-term, diversified energy supply. The Department of Energy has begun research on such a new generation of nuclear energy systems that can be made available to the market by 2030 or earlier, and that can offer significant advances toward these challenging goals [1]. These future nuclear power systems will require advances in materials, reactor physics as well as heat transfer to realize their full potential. In this paper, a summary of these advanced nuclear power systems is presented along with a short synopsis of the important heat transfer issues. Given the nature of research and the dynamics of these conceptual designs, key aspects of the physics will be provided, with details left for the presentation.

Localización de faltas en sistemas de distribución de energía eléctrica usando métodos basados en el modelo y métodos basados en el conocimiento

La calidad de energía eléctrica incluye la calidad del suministro y la calidad de la atención al cliente. La calidad del suministro a su vez se considera que la conforman dos partes, la forma de onda y la continuidad. En esta tesis se aborda la continuidad del suministro a través de la localización de faltas. Este problema se encuentra relativamente resuelto en los sistemas de transmisión, donde por las características homogéneas de la línea, la medición en ambos terminales y la disponibilidad de diversos equipos, se puede localizar el sitio de falta con una precisión relativamente alta. En sistemas de distribución, sin embargo, la localización de faltas es un problema complejo y aún no resuelto. La complejidad es debida principalmente a la presencia de conductores no homogéneos, cargas intermedias, derivaciones laterales y desbalances en el sistema y la carga. Además, normalmente, en estos sistemas sólo se cuenta con medidas en la subestación, y un modelo simplificado del circuito. Los principales esfuerzos en la localización han estado orientados al desarrollo de métodos que utilicen el fundamental de la tensión y de la corriente en la subestación, para estimar la reactancia hasta la falta. Como la obtención de la reactancia permite cuantificar la distancia al sitio de falta a partir del uso del modelo, el Método se considera Basado en el Modelo (MBM). Sin embargo, algunas de sus desventajas están asociadas a la necesidad de un buen modelo del sistema y a la posibilidad de localizar varios sitios donde puede haber ocurrido la falta, esto es, se puede presentar múltiple estimación del sitio de falta. Como aporte, en esta tesis se presenta un análisis y prueba comparativa entre varios de los MBM frecuentemente referenciados. Adicionalmente se complementa la solución con métodos que utilizan otro tipo de información, como la obtenida de las bases históricas de faltas con registros de tensión y corriente medidos en la subestación (no se limita solamente al fundamental). Como herramienta de extracción de información de estos registros, se utilizan y prueban dos técnicas de clasificación (LAMDA y SVM). Éstas relacionan las características obtenidas de la señal, con la zona bajo falta y se denominan en este documento como Métodos de Clasificación Basados en el Conocimiento (MCBC). La información que usan los MCBC se obtiene de los registros de tensión y de corriente medidos en la subestación de distribución, antes, durante y después de la falta. Los registros se procesan para obtener los siguientes descriptores: a) la magnitud de la variación de tensión ( dV ), b) la variación de la magnitud de corriente ( dI ), c) la variación de la potencia ( dS ), d) la reactancia de falta ( Xf ), e) la frecuencia del transitorio ( f ), y f) el valor propio máximo de la matriz de correlación de corrientes (Sv), cada uno de los cuales ha sido seleccionado por facilitar la localización de la falta. A partir de estos descriptores, se proponen diferentes conjuntos de entrenamiento y validación de los MCBC, y mediante una metodología que muestra la posibilidad de hallar relaciones entre estos conjuntos y las zonas en las cuales se presenta la falta, se seleccionan los de mejor comportamiento. Los resultados de aplicación, demuestran que con la combinación de los MCBC con los MBM, se puede reducir el problema de la múltiple estimación del sitio de falta. El MCBC determina la zona de falta, mientras que el MBM encuentra la distancia desde el punto de medida hasta la falta, la integración en un esquema híbrido toma las mejores características de cada método. En este documento, lo que se conoce como híbrido es la combinación de los MBM y los MCBC, de una forma complementaria. Finalmente y para comprobar los aportes de esta tesis, se propone y prueba un esquema de integración híbrida para localización de faltas en dos sistemas de distribución diferentes. Tanto los métodos que usan los parámetros del sistema y se fundamentan en la estimación de la impedancia (MBM), como aquellos que usan como información los descriptores y se fundamentan en técnicas de clasificación (MCBC), muestran su validez para resolver el problema de localización de faltas. Ambas metodologías propuestas tienen ventajas y desventajas, pero según la teoría de integración de métodos presentada, se alcanza una alta complementariedad, que permite la formulación de híbridos que mejoran los resultados, reduciendo o evitando el problema de la múltiple estimación de la falta.