This dissertation proposes a novel control technique for power density maximization of the brushless DC (BLDC) generator which is a nonsinusoidal power supply system. In a generator of given rating, the weight and size of the system affect the fuel consumption directly, therefore power density is one of the most important issues in a stand-alone generator. Conventional rectification methods cannot achieve the maximum power possible because of a distorted or unsuitable current waveform. The optimal current waveform for maximizing power density and minimizing machine size and weight in a nonsinusoidal power supply system has been proposed theoretically and verified by simulation and experimental work. Also, various attributes of practical interest are analyzed and simulated to investigate the impact on real systems.

Water supply system planning is concerned about the design of water supply infrastructure for distributing water from sources to users. Population growth, economic development and diminishing freshwater supplies are posing growing challenges for water supply system planning in many urban areas. Besides the need to exploit alternative water sources to the conventional surface and groundwater supplies, such as reclaimed water, a systematic point of view has to be taken for the efficient management of all potential water resources, so that issues of water supply, storage, treatment and reuse are not considered separately, but rather in the context of their interactions. The focus of this dissertation is to develop mathematical models and optimization algorithms for water supply system planning, where the interaction of different system components is explicitly considered. A deterministic nonlinear programming model is proposed at first to decide pipe and pump sizes in a regional water supply system for satisfying given potable and non-potable user demands over a certain planning horizon. A branch-and-bound algorithm based on the reformulation-linearization technique is then developed for solving the model to global optimality. To handle uncertainty in the planning process, a stochastic programming (SP) model and a robust optimization (RO) model are successively proposed to deal with random water supply and demand and the risk of facility failure, respectively. Both models attempt to make the decision of building some additional treatment and recharge facilities for recycling wastewater on-the-site. While the objective of the SP model is to minimize the total system design and expected operation cost, the RO model tries to achieve a favorable trade-off between system cost and system robustness, where the system robustness is defined in terms of meeting given user demands against the worst-case failure mode. The Benders decomposition method is then applied for solving both models by exploiting their special structure.

Įmonių praeities pasiekimai yra menkaverčiai dėl dabartinės rizikos veiksnių, rinkos nepastovumo, ekonominio neapibrėžtumo. Šiuolaikinių įmonių dominavimas rinkoje remiasi logistine sistema, gebančia prisitaikyti prie aplinkos pokyčių, gebančia balansuoti tarp „sveiko proto“ ir greito, operatyvaus reagavimo laiku į besikeičiančią pasaulinę verslo aplinką. Tai įpareigojo įmones ieškoti naujų veiklos efektyvumo didinimo būdų ir paskatino verslą atsigręžti į aprūpinimą bei aprūpinimo sistemų valdymą. Šiuo metu aprūpinimo valdymo problemų sprendimas yra vienas iš dažniausiai nagrinėjamų klausimų įmonėse ir organizacijose. Šio darbo tikslas: išnagrinėti mokslinius šaltinius aprūpinimo tema ir išsiaiškinti aprūpinimo reikšmę šiuolaikiniam verslui. Darbe buvo atlikta UAB „Sander Baltic“ aprūpinimo sistemos analizė, norint suformuluoti ir pateikti projektinį sprendimą įmonės aprūpinimo sistemos veiklos tobulinimui. Magistrinis darbas susideda iš trijų dalių. Pirmoje darbo dalyje yra nagrinėjama aprūpinimo reikšmė ir vaidmuo šiuolaikiniame versle. Aptarta aprūpinimo samprata, aprūpinimo sistemų taikymo ypatumai bei problemos. Antroje dalyje pateikiama UAB „Sander Baltic“ aprūpinimo sistemos analizė. Įmonės veiklos specifika yra labai svarbus aspektas numatant tolesnes aprūpinimo sistemos tobulinimo kryptis, kurios yra pateikiamos trečiojoje darbo dalyje. Pastarojoje dalyje taip pat yra analizuojami atlikto tyrimo rezultatai, vertinantys esamą aprūpinimo sistemą ir nurodantys jos... [toliau žr. visą tekstą] / Achievements of the past became of low value in the context of nowadays risk factors, instability of the market, economical indeterminacy. Domination of the companies in the market is now based upon the logistics system capable of adapting to external changes, capable of balancing between rational thinking and timely rapid response to the changing environment of the global trade. This obliged the companies to search for new ways of increasing efficiency and encouraged them to spotlight the supply and supply system management. Solving the problems related to supply management is one of the biggest concerns of the companies and organizations nowadays. The goal of this work: to analyze the scientific articles dealing with the supply topic and to determine the significance of supply to the modern trade. The supply system analysis of company “Sander Baltic” Ltd. has been performed with goal to formulate and propose project solution of company’s supply system improvement. Master degree thesis consists of three parts. In the first part of the work importance and role of the supply in modern trade is analyzed. Conception of supply, peculiarities and problems of supply systems are discussed. The supply system analysis of company “Sander Baltic” Ltd. is presented in the second part of the work. Peculiarity of the company work is very important aspect in scheduling directions of supply system improvement which are presented in the third part of the work. Results of the research... [to full text]

Cyber Physical System (CPS) is a system where cyber and physical components work in a complex co-ordination to provide better performance. By exploiting the communication infrastructure among the sensors, actuators, and control systems, attackers may compromise the security of a CPS. In this dissertation, security measures for different types of attacks/ faults in two CPSs, water supply system (WSS) and smart grid system, are presented. In this context, I also present my study on energy management in Smart Grid. The techniques for detecting attacks/faults in both WSS and Smart grid system adopt Kalman Filter (KF) and χ2 detector. The χ2 -detector can detect myriad of system fault- s/attacks such as Denial of Service (DoS) attack, short term and long term random attacks. However, the study shows that the χ2 -detector is unable to detect the intelligent False Data Injection attack (FDI). To overcome this limitation, I present a Euclidean detector for smart grid which can effectively detect such injection attacks. Along with detecting attack/faults I also present the isolation of the attacked/faulty nodes for smart grid. For isolation the Gen- eralized Observer Scheme (GOS) implementing Kalman Filter is used. As GOS is effective in isolating attacks/faults on a single sensor, it is unable to isolate simultaneous attacks/faults on multiple sensors. To address this issue, an Iterative Observer Scheme (IOS) is presented which is able to detect attack on multiple sensors. Since network is an integral part of the future CPSs, I also present a scheme for pre- serving privacy in the future Internet architecture, namely MobilityFirst architecture. The proposed scheme, called Anonymity in MobilityFirst (AMF), utilizes the three-tiered ap- proach to effectively exploit the inherent properties of MF Network such as Globally Unique Flat Identifier (GUID) and Global Name Resolution Service (GNRS) to provide anonymity to the users. While employing new proposed schemes in exchanging of keys between different tiers of routers to alleviate trust issues, the proposed scheme uses multiple routers in each tier to avoid collaboration amongst the routers in the three tiers to expose the end users.

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / As interrupÃÃes no fornecimento de energia elÃtrica provocam diversos prejuÃzos econÃmicos Ãs concessionÃrias e aos seus clientes cuja extensÃo està associada, principalmente, à freqÃÃncia e duraÃÃo do evento e ao tipo de consumidor. Para as concessionÃrias de distribuiÃÃo de energia elÃtrica, que sÃo fiscalizadas pelos ÃrgÃos reguladores e pela sociedade, o grande desafio à a diminuiÃÃo do tempo das interrupÃÃes e, conseqÃentemente, das perdas econÃmicas por elas ocasionadas. Este trabalho apresenta a concepÃÃo e aplicaÃÃo de uma metodologia de anÃlise de desempenho econÃmico dos serviÃos de atendimento emergencial ao consumidor de energia elÃtrica, considerando os impactos econÃmico-financeiros para a distribuidora e para os consumidores de se utilizar um sistema de gestÃo operacional que otimize os parÃmetros que medem este desempenho. No estudo de caso, efetuado sobre o sistema de atendimento emergencial (SAE) da Companhia de Eletricidade do Cearà â COELCE, tem-se como parÃmetro principal de desempenho a duraÃÃo equivalente da interrupÃÃo (DEC), definida pela AgÃncia Nacional de Energia ElÃtrica - ANEEL. Partindo-se do uso de um sistema computacional de gestÃo otimizadora, desenvolvido na Universidade Federal do Cearà (Sistema SAEDE), o qual otimiza o despacho e a alocaÃÃo das equipes de campo responsÃveis pelos serviÃos de reparo na rede elÃtrica, aplicou-se a metodologia proposta no intuito de verificar se haveria benefÃcios justificÃveis para investimentos em sistemas de gestÃo operacional do SAE tanto para a distribuidora quanto para os consumidores. Os principais resultados obtidos atravÃs da aplicaÃÃo da metodologia ao SAE da COELCE apontou que a utilizaÃÃo do Sistema SAEDE contribui para reduzir custos aos usuÃrios devidos Ãs falhas na entrega de energia pela Companhia e, tambÃm, diminui custos a ela imputados quando ocorrem distÃrbios na rede elÃtrica. / Interruptions in electrical supply system normally cause several economic damages both to supplier companies and to their customers which are hard to be estimated. The extension of these damages is a function of the frequency and duration of the blackout and it varies according to the consumerâs characteristics. In Brazil, electrical supplier companies are regulated by federal and state agencies on behalf of the consumers and their major challenge is to reduce breakdown time and consequent economic losses. This work presents the conception and application of a methodology to make the economic performance assessment of customerâs emergency attendance services, according to the parameters and standards set by the Federal Regulatory Agency (ANEEL) and focusing both the supplier and consumers costs related to system breakdown. The proposed methodology was applied to the case of a electrical distribution company in Ceara State, in the northeastern Brazil, to which an optimized operational management system (SAEDE System) was built. SAEDE System is a computational tool that was developed to optimize the dispatch and the staffing of the emergency attendance teams who are employed to repair electrical fails in the regional system. The proposed methodology was applied to search the benefits of investments derived from using SAEDE System in customerâs emergency attendance services of electrical supply Company in Ceara State. Main results of the study point out that the application of SAEDE System contributes to reduce both customerâs costs as well as company costs related to electrical system breakdown in the study area.

O presente trabalho de pesquisa enfoca a problemática da previsão de demandas com vistas à operação dos sistemas de abastecimento de água em tempo real, utilizando-se dados de consumo horários de água das cidades de São Carlos e Araraquara, SP, para que se identifique o modelo que produza os melhores ajustes. Foram estudadas as redes neurais artificiais Perceptron de Múltiplas Camadas (RNAs MLP), a Rede Neural Dinâmica (DAN2) e duas RNAs híbridas, sendo que estas últimas consistem em associar previsão por séries de Fourier com a RNA MLP e a DAN2, sendo denominadas respectivamente RNA-H e DAN2-H. As entradas fornecidas para os modelos de previsão foram escolhidas com base na revisão bibliográfica e por meio de análise de correlação, considerando os dados de consumo e as variáveis meteorológicas, tais como temperatura, umidade relativa do ar e ocorrência de chuva. Os melhores modelos de previsão utilizaram a DAN2, a qual se mostrou de manuseio mais fácil em relação às redes neurais de múltiplas camadas, pois dispensa o processo de tentativas e erros para se determinar a melhor arquitetura para os dados fornecidos ao modelo. Os melhores modelos de previsão para a próxima hora produziram um erro médio absoluto de 2,25 L/s (DAN2-H) para um subssetor de Araraquara, representado cerca de 8% do consumo médio, e 2,3 L/s (DAN2) para um setor de São Carlos, equivalente a 4% do consumo médio. / The present work focuses the problem of water demand forecasting for real time operation of WSS. The study was conducted using hourly consumption data from water distribution system from the cities of São Carlos, Araraquara, SP, to identify the model that fits better. It were studied the artificial neural network Multilayer Perceptron (ANN MLP), the Dynamic Neural Network (DAN2) and two hybrid ANN. The hybrid ANN is an association of the water demand prevision by series of Fourier with the ANN MLP and DAN2, which were called respectively ANN-H and DAN2-H. The inputs provided to the forecasting models were chosen based on literature review and correlation analysis, considering consumption data and meteorological variables, such as temperature, air relative humidity and rain occurrence. The best forecasting models were based on DAN2, which showed easy handling compared to other neural network with multiple layers, because it dispenses the trial and error procedure to find the best architecture for a given data. The best forecasting model for the next hour produced an absolute medium error of 2.25 L/s (DAN2-H) for a subsector from Araraquara, representing about 8% of the average consumption, and 2.30 L/s (DAN2) for a sector from São Carlos, which correspond to 4% of its average consumption.

The subject of the submitted thesis is analysis of the present state of forwarding in a manufacturing-oriented firm and a concept of reduction in logistics costs by implementation of system just-in time or outsourcing.

The building sector has great potential for energy savings since it is responsible for nearly a third of the global energy use. As oil, coal and natural gas continues to hold a big share of the energy mix it is important to work towards introducing more renewable energy alternatives. For an energy supply system, it is common to use a multi-energy system to increase efficiency. By increasing efficiency and the use of renewable energies, the total energy consumption can be lowered, and emissions can be reduced.   The purpose of this thesis was to design a multi-energy supply system for a high-rise building in Germany with low emissions. This was executed by constructing a simplified design used as a reference, also referred to as option 1, and two other designs with different energy sources, called design 1 and design 2. The design layout was constructed in collaboration with Transsolar. Design 1 is using a compression chiller and is presented as three different variants, option 2, 3 and 4. The three options were created to evaluate the pros and cons of a larger cold water storage tank and sizing of the compression chiller. Design 2, option 5, is using an absorption chiller and this option was created to investigate the opportunity to use district heating. Simulations were made of the designs with the simulation tool TRNSYS and presented in graph form. Values provided from the simulations were then used to calculate emissions, investment costs and net present value over a period of 40 years. For the net present value, three different variants were presented. One without carbon costs taken into consideration, one with low carbon costs and one with high carbon costs. The result was evaluated, and comparisons were made to suggest the most sustainable option for the building.   The result of design 1, which has a natural gas boiler for peak heating demand and a compression chiller as cold energy source, shows that the chiller produces a higher capacity compared to the installed value during the summer and a lower value during the winter. The norm capacity of the chiller in design 1 was 175 kW when combined with a larger cold water storage and 410 kW with no cold water storage. Comparison of those options showed that it is economical to install a cold water storage since the investment cost of the chiller is lowered. However, it also showed that a higher capacity of the chiller lowered the need for the gas boiler, because of the parallel heating and cooling characteristic of the chiller, which reduces emissions. Another option was made with a larger cold water storage implemented and an over dimensioned capacity of 340 kW for the chiller to reduce the gas needed for heating. For the option with the 175 kW compression chiller the gas boiler needed to supply 15% of the heating load of the building, while the option with the 340 kW compression chiller needed 3% of the buildings heating load to be provided by the gas boiler. This decrease in the gas boiler dependency reduced the emissions for heating from 52 ton/year to 41 ton/year, while still having comparable cost over time with low carbon costs and lower cost with high carbon costs. Therefore, the option with an over dimensioned chiller with an implemented big cold water storage is the favourable one, since it has the lowest emissions of the options of design 1 and is economically justifiable.   Design 2 has one of lowest investment cost and the lowest emissions which was 61% lower than the reference design and 19% lower than design 1. With higher carbon costs option 5 is the cheapest, otherwise it is relatively similar to the other options. Hence, Design 2 is the system that is suggested to use for the building. / Byggnadssektorn står för nästan en tredjedel av den globala energianvändningen och har därför stor potential till energibesparing. Eftersom en stor del av energimixen består av olja, kol och naturgas är det viktigt att sträva mot att introducera mer hållbara energikällor. För ett energisystem är det vanligt att använda sig av mer än en energikälla för att öka effektiviteten. Med ökad effektivitet i kombination med förnyelsebara energikällor kan den totala energikonsumtionen, samt utsläppen, minska.   Målet var att designa ett energisystem med fler än en energikälla och låga utsläpp för ett höghus i Tyskland. För att göra det konstruerades en förenklad design, också kallad option 1, som användes som en referensdesign samt två andra designer, kallade design 1 och design 2, med olika energikällor. Designförslagen togs fram i samarbete med Transsolar. Design 1 använder sig av en kompressionskylmaskin och har tre olika varianter, option 2, 3 och 4, som gjordes för att utvärdera för- och nackdelar med en stor kallvattentank för energilagring och för att bestämma storleken på kompressionskylmaskinen. Design 2, option 5, använder sig av en absorptionskylmaskin och skapades för att undersöka möjligheten att använda sig av fjärrvärme. Simuleringar gjordes för design 1 och 2 med hjälp av simuleringsverktyget TRNSYS där resultatet presenterades i grafer. Värdena tagna från simuleringarna användes till att beräkna utsläpp, investeringskostnad och nuvärdet för den totala kostnaden över 40 år. Nuvärdet beräknades utan att ta emissionskostnader i åtanke, med en lägre emissionskostnad samt med högre emissionskostnad. Resultatet utvärderades och jämfördes för att kunna framföra ett förslag om vilket av alternativet som passar byggnaden bäst.   Resultatet från design 1, som har en naturgaspanna för att försörja toppvärmebehovet och en kompressionskylare för kylbehovet, visar att kompressionskylaren uppnår en högre kapacitet jdän den installerade kapacitet under sommaren och lägre kapacitet under vintern. För varianten med en större kallvattentank kunde kylarmaskinens kapacitet bestämmas till 175 kW medan den behövde en kapacitet på 410 kW för varianten med en liten kallvattentank. Vid jämförelse av de två varianterna visas att kostnaderna minskades för alternativet med kallvattentanken eftersom den krävde en lägre kapacitet för kompressionskylaren. Däremot visades det att utsläppen minskar vid användning av en större kylmaskin eftersom det minskar värmebehovet från gaspannan eftersom kylaren kyler och värmer parallellt när den är i drift. Den tredje varianten som både använder en stor kallvattentank samt en överdimensionerad kylare på 340 kW skapades för att minska gasanvändningen. Alternativet med en kylare på 175 kW behövde att 15% av värmebehovet kom från gaspannan, medan kylaren på 340 kW behövde att 3% av värmebehovet kom från gaspannan. Reduceringen av gasanvändningen sänkte utsläppen från 52 ton CO2-ekv./år till 41 ton CO2-ekv./år, med en jämförbar kostnad över tid med ingen eller låg emissionskostnad och lägre kostnad över tid med hög emissionskostnad. Alternativet med en stor kallvattentank och överdimensionerad kompressionskylare är därför det mest passande alternativet av design 1 eftersom den har lägst utsläpp medan den är ekonomiskt försvarbar.   Design 2 har en av de lägsta investeringskostnaderna och har lägst utsläpp som är 61% lägre än referensdesignen och 19% lägre än design 1. Med högre emissionskostnader är design 2 billigast, annars har den jämförbara kostnader. Därmed föreslås att byggnaden ska använda design 2.

Energy efficiency is currently a hot topic on all regional, national, and global stages. Accurate measurements on how energy is being used over a period of time can improve performance of the drinking water utility substantially and reduce energy consumption. Nevertheless, the drinking water industry does not have a specific benchmarking practice to evaluate its energy performance of the system. Therefore, there are no standards to compare energy use between water utilities that have a variety of system characteristics. The goal of this research is to develop quantitative approach to select energy benchmarking parameters of the water system, so the drinking water utilities can use those parameters to improve their energy efficiency. In addition to a typical benchmarking of drinking water utilities, the energy benchmarking can specifically compare energy efficiency of a utility with other utilities nationwide. The research developed a regression model based on the statistical representation of the energy use and descriptive characteristics of the drinking water utilities data throughout the U.S. Methodologies to eliminate singularity and multicollinearity from collinear survey dataset are discussed. The all possible regressions were chosen as parameters selection methodology to identify a subset of most significant parameters, i.e. system characteristics, that can mathematically correspond to energy use across different utilities. As a result, the energy benchmarking would be able to calculate the predicted total energy use of the system from given system characteristics. / Master of Science

The integration of Artificial Intelligence (AI) into water supply systems (WSSs) has revolutionized real-time monitoring, automated operational control, and predictive decision-making analytics. However, AI also introduces security vulnerabilities, such as data poisoning. In this context, data poisoning could involve the malicious manipulation of critical data, including water quality parameters, flow rates, and chemical composition levels. The consequences of such threats are significant, potentially jeopardizing public safety and health due to decisions being made based on poisoned data. This thesis aims to exploit these vulnerabilities in data-driven applications within WSSs. Proposing Water Generative Adversarial Networks, H2OGAN, a time-series GAN-based model designed to synthesize water data. H2OGAN produces water data based on the characteristics within the expected constraints of water data cardinality. This generative model serves multiple purposes, including data augmentation, anomaly detection, risk assessment, cost-effectiveness, predictive model optimization, and understanding complex patterns within water systems. Experiments are conducted in AI and Cyber for Water and Agriculture (ACWA) Lab, a cyber-physical water testbed that generates datasets replicating both operational and adversarial scenarios in WSSs. Identifying adversarial scenarios is particularly importance due to their potential to compromise water security. The datasets consist of 10 physical incidents, including normal conditions, sensor anomalies, and malicious attacks. A recurrent neural network (RNN) model, i.e., gated recurrent unit (GRU), is used to classify and capture the temporal dynamics those events. Subsequently, experiments with real-world data from Alexandria Renew Enterprises (AlexRenew), a wastewater treatment plant in Alexandria, Virginia, are conducted to assess the effectiveness of H2OGAN in real-world applications. / Master of Science / Today, a significant portion of the global population struggles with access to essential services: 25% lack clean water, 50% lack sanitation services, and 30% lack hygiene facilities. In response, AI is being leveraged to tackle these deficiencies within water supply systems. Investments in AI are expected to reach an estimated $6.3 billion by 2030, with potential savings of 20% to 30% in operational expenditures by optimizing chemical usage in water treatment. The flexibility and efficiency of AI applications have fueled optimism about their potential to revolutionize water management. As the era of Industry 4.0 progresses, the role of AI in transforming critical infrastructures, including water supply systems, becomes increasingly vital. However, this technological integration brings with it heightened vulnerabilities. The water sector, recognized as one of the 16 critical infrastructures by the Cybersecurity and Infrastructure Security Agency (CISA), has seen a notable increase in cyberattack incidents. These attacks underscore the urgent need for sophisticated AI-driven security solutions to protect these essential systems against potential compromises that could pose significant public health risks. Addressing these challenges, this thesis introduces H2OGAN, a time-series GAN-based model developed to generate and analyze realistic water data within the expected constraints of water parameter characteristics. H2OGAN supports various functions including data augmentation, anomaly detection, risk assessment, and predictive model optimization, thereby enhancing the security and efficiency of water supply systems. Extensive testing is conducted in ACWA Lab, a cyber-physical testbed that replicates both operational and adversarial scenarios. These experiments utilize a RNN model, specifically a GRU, to classify and analyze the dynamics of various scenarios including normal operations, sensor anomalies, and malicious attacks. Further real-world validation is carried out at AlexRenew, a wastewater treatment facility in Alexandria, Virginia, confirming the effectiveness of H2OGAN in practical applications. This research not only advances the understanding of AI in water management but also emphasizes the critical need for robust security measures to protect against the evolving landscape of cyber threats.