887 resultados para Large power system


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Mobile Cloud Computing promises to overcome the physical limitations of mobile devices by executing demanding mobile applications on cloud infrastructure. In practice, implementing this paradigm is difficult; network disconnection often occurs, bandwidth may be limited, and a large power draw is required from the battery, resulting in a poor user experience. This thesis presents a mobile cloud middleware solution, Context Aware Mobile Cloud Services (CAMCS), which provides cloudbased services to mobile devices, in a disconnected fashion. An integrated user experience is delivered by designing for anticipated network disconnection, and low data transfer requirements. CAMCS achieves this by means of the Cloud Personal Assistant (CPA); each user of CAMCS is assigned their own CPA, which can complete user-assigned tasks, received as descriptions from the mobile device, by using existing cloud services. Service execution is personalised to the user's situation with contextual data, and task execution results are stored with the CPA until the user can connect with his/her mobile device to obtain the results. Requirements for an integrated user experience are outlined, along with the design and implementation of CAMCS. The operation of CAMCS and CPAs with cloud-based services is presented, specifically in terms of service description, discovery, and task execution. The use of contextual awareness to personalise service discovery and service consumption to the user's situation is also presented. Resource management by CAMCS is also studied, and compared with existing solutions. Additional application models that can be provided by CAMCS are also presented. Evaluation is performed with CAMCS deployed on the Amazon EC2 cloud. The resource usage of the CAMCS Client, running on Android-based mobile devices, is also evaluated. A user study with volunteers using CAMCS on their own mobile devices is also presented. Results show that CAMCS meets the requirements outlined for an integrated user experience.

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Power systems require a reliable supply and good power quality. The impact of power supply interruptions is well acknowledged and well quantified. However, a system may perform reliably without any interruptions but may have poor power quality. Although poor power quality has cost implications for all actors in the electrical power systems, only some users are aware of its impact. Power system operators are much attuned to the impact of low power quality on their equipment and have the appropriate monitoring systems in place. However, over recent years certain industries have come increasingly vulnerable to negative cost implications of poor power quality arising from changes in their load characteristics and load sensitivities, and therefore increasingly implement power quality monitoring and mitigation solutions. This paper reviews several historical studies which investigate the cost implications of poor power quality on industry. These surveys are largely focused on outages, whilst the impact of poor power quality such as harmonics, short interruptions, voltage dips and swells, and transients is less well studied and understood. This paper examines the difficulties in quantifying the costs of poor power quality, and uses the chi-squared method to determine the consequences for industry of power quality phenomenon using a case study of over 40 manufacturing and data centres in Ireland.

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Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders (Belgium).

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Exponemos los resultados de una observación exploratoria en la que se analizan los impactos funcionales en el sistema administrativo como consecuencia de la construcción de la Central Hidroeléctrica de Belo Monte (CHB) en el municipio de Altamira (Amazonia oriental brasileña). En la perspectiva teórico-conceptual de la teoría de sistemas sociales de Niklas Luhmann, realizamos una observación del sistema administrativo local sobre sus operaciones y funciones, en base a cuatro códigos preestablecidos: toma de decisiones, contingencia, significación simbólica del proyecto y planificación. Las conclusiones permiten entrever en un aplano conceptual la utilidad de los conceptos sistémicos de Luhmann, y en el empírico, una planificación y administración pública municipal reactivas.

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Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.

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A grid-connected DFIG for wind power generation can affect power system small-signal angular stability in two ways: by changing the system load flow condition and dynamically interacting with synchronous generators (SGs). This paper presents the application of conventional method of damping torque analysis (DTA) to examine the effect of DFIG’s dynamic interactions with SGs on the small-signal angular stability. It shows that the effect is due to the dynamic variation of power exchange between the DFIG and power system and can be estimated approximately by the DTA. Consequently, if the DFIG is modelled as a constant power source when the effect of zero dynamic interactions is assumed, the impact of change of load flow brought about by the DFIG can be determined. Thus the total effect of DFIG can be estimated from the result of DTA added on that of constant power source model. Applications of the DTA method proposed in the paper are discussed. An example of multi-machine power systems with grid-connected DFIGs are presented to demonstrate and validate the DTA method proposed and conclusions obtained in the paper.

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This paper presents the first multi vector energy analysis for the interconnected energy systems of Great Britain (GB) and Ireland. Both systems share a common high penetration of wind power, but significantly different security of supply outlooks. Ireland is heavily dependent on gas imports from GB, giving significance to the interconnected aspect of the methodology in addition to the gas and power interactions analysed. A fully realistic unit commitment and economic dispatch model coupled to an energy flow model of the gas supply network is developed. Extreme weather events driving increased domestic gas demand and low wind power output were utilised to increase gas supply network stress. Decreased wind profiles had a larger impact on system security than high domestic gas demand. However, the GB energy system was resilient during high demand periods but gas network stress limited the ramping capability of localised generating units. Additionally, gas system entry node congestion in the Irish system was shown to deliver a 40% increase in short run costs for generators. Gas storage was shown to reduce the impact of high demand driven congestion delivering a reduction in total generation costs of 14% in the period studied and reducing electricity imports from GB, significantly contributing to security of supply.

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Static state estimators currently in use in power systems are prone to masking by multiple bad data. This is mainly because the power system regression model contains many leverage points; typically they have a cluster pattern. As reported recently in the statistical literature, only high breakdown point estimators are robust enough to cope with gross errors corrupting such a model. This paper deals with one such estimator, the least median of squares estimator, developed by Rousseeuw in 1984. The robustness of this method is assessed while applying it to power systems. Resampling methods are developed, and simulation results for IEEE test systems discussed. © 1991 IEEE.

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In modern society, the body health is a very important issue to everyone. With the development of the science and technology, the new and developed body health monitoring device and technology will play the key role in the daily medical activities. This paper focus on making progress in the design of the wearable vital sign system. A vital sign monitoring system has been proposed and designed. The whole detection system is composed of signal collecting subsystem, signal processing subsystem, short-range wireless communication subsystem and user interface subsystem. The signal collecting subsystem is composed of light source and photo diode, after emiting light of two different wavelength, the photo diode collects the light signal reflected by human body tissue. The signal processing subsystem is based on the analog front end AFE4490 and peripheral circuits, the collected analog signal would be filtered and converted into digital signal in this stage. After a series of processing, the signal would be transmitted to the short-range wireless communication subsystem through SPI, this subsystem is mainly based on Bluetooth 4.0 protocol and ultra-low power System on Chip(SoC) nRF51822. Finally, the signal would be transmitted to the user end. After proposing and building the system, this paper focus on the research of the key component in the system, that is, the photo detector. Based on the study of the perovskite materials, a low temperature processed photo detector has been proposed, designed and researched. The device is made up of light absorbing layer, electron transporting and hole blocking layer, hole transporting and electron blocking layer, conductive substrate layer and metal electrode layer. The light absorbing layer is the important part of whole device, and it is fabricated by perovskite materials. After accepting the light, the electron-hole pair would be produced in this layer, and due to the energy level difference, the electron and hole produced would be transmitted to metal electrode and conductive substrate electrode through electron transporting layer and hole transporting layer respectively. In this way the response current would be produced. Based on this structure, the specific fabrication procedure including substrate cleaning; PEDOT:PSS layer preparation; pervoskite layer preparation; PCBM layer preparation; C60, BCP, and Ag electrode layer preparation. After the device fabrication, a series of morphological characterization and performance testing has been done. The testing procedure including film-forming quality inspection, response current and light wavelength analysis, linearity and response time and other optical and electrical properties testing. The testing result shows that the membrane has been fabricated uniformly; the device can produce obvious response current to the incident light with the wavelength from 350nm to 800nm, and the response current could be changed along with the light wavelength. When the light wavelength keeps constant, there exists a good linear relationship between the intensity of the response current and the power of the incident light, based on which the device could be used as the photo detector to collect the light information. During the changing period of the light signal, the response time of the device is several microseconds, which is acceptable working as a photo detector in our system. The testing results show that the device has good electronic and optical properties, and the fabrication procedure is also repeatable, the properties of the devices has good uniformity, which illustrates the fabrication method and procedure could be used to build the photo detector in our wearable system. Based on a series of testing results, the paper has drawn the conclusion that the photo detector fabricated could be integrated on the flexible substrate and is also suitable for the monitoring system proposed, thus made some progress on the research of the wearable monitoring system and device. Finally, some future prospect in system design aspect and device design and fabrication aspect are proposed.

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Power system engineers face a double challenge: to operate electric power systems within narrow stability and security margins, and to maintain high reliability. There is an acute need to better understand the dynamic nature of power systems in order to be prepared for critical situations as they arise. Innovative measurement tools, such as phasor measurement units, can capture not only the slow variation of the voltages and currents but also the underlying oscillations in a power system. Such dynamic data accessibility provides us a strong motivation and a useful tool to explore dynamic-data driven applications in power systems. To fulfill this goal, this dissertation focuses on the following three areas: Developing accurate dynamic load models and updating variable parameters based on the measurement data, applying advanced nonlinear filtering concepts and technologies to real-time identification of power system models, and addressing computational issues by implementing the balanced truncation method. By obtaining more realistic system models, together with timely updated parameters and stochastic influence consideration, we can have an accurate portrait of the ongoing phenomena in an electrical power system. Hence we can further improve state estimation, stability analysis and real-time operation.

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The insertion of distributed generation units in the electric power systems have contributed to the popularization of microgrid concepts. With the microgrids, several potential benefits can be achieved in regard to power quality and supply reliability. However, several technical challenges related to the control and operation of microgrids, which are associated with high insertion of generation systems based on static converters, must be overcame. Among the opportunities in the context of microgrids, there is the islanded operation of microgrids temporarily disconnected from the electric power systems and also the autonomous operation of geographically isolated microgrids. The frequency in large power systems is traditionally controlled by the generation units based on traditional synchronous generator. The insertion of distributed generation units based on static power converters may bring difficulties to the frequency control in microgrids, due to the reduction of the equivalent inertia of conventional synchronous generators present in islanded and isolated microgrids. In this context, it becomes necessary the proposition of new operational and control strategies for microgrids control, taking into account the presence of distributed generation units based on full-rated converter. This paper proposes an operational and control strategy for the islanded operation of a winddiesel microgrid with high insertion level of wind generation. The microgrid adopted in this study comprises of a wind energy conversion system with synchronous generator based on full rated converter, a diesel generator (DIG) and a dump load. Due to the high insertion level of wind generation, the wind unit operates in Vf mode and the diesel generator operates in PQ mode. The diesel generator and the dump load are used to regulate the DC-link voltage of the wind generation unit. The proposed control allows the islanded operation of the microgrid only with wind generation, wind-only mode (WO), and with wind-diesel generation, wind-diesel mode (WD). For the wind-only mode, with 100% of penetration level of wind generation, it is proposed a DC-link voltage control loop based on the use of a DC dump load. For the winddiesel mode, it is proposed a DC-link voltage control loop added to the diesel generator, which is connected to the AC side of the microgrid, in coordinated action with the dump load. The proposed operational and control strategy does not require the use of batteries and aims to maximize the energy production from wind generation, ensuring the uninterrupted operation of the microgrid. The results have showed that the operational and control strategy allowed the stable operation of the islanded microgrid and that the DC-link voltage control loop added to the diesel generator and the dump load proved to be effective during the typical variations of wind speed and load.

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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015.

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Combinatorial optimization is a complex engineering subject. Although formulation often depends on the nature of problems that differs from their setup, design, constraints, and implications, establishing a unifying framework is essential. This dissertation investigates the unique features of three important optimization problems that can span from small-scale design automation to large-scale power system planning: (1) Feeder remote terminal unit (FRTU) planning strategy by considering the cybersecurity of secondary distribution network in electrical distribution grid, (2) physical-level synthesis for microfluidic lab-on-a-chip, and (3) discrete gate sizing in very-large-scale integration (VLSI) circuit. First, an optimization technique by cross entropy is proposed to handle FRTU deployment in primary network considering cybersecurity of secondary distribution network. While it is constrained by monetary budget on the number of deployed FRTUs, the proposed algorithm identi?es pivotal locations of a distribution feeder to install the FRTUs in different time horizons. Then, multi-scale optimization techniques are proposed for digital micro?uidic lab-on-a-chip physical level synthesis. The proposed techniques handle the variation-aware lab-on-a-chip placement and routing co-design while satisfying all constraints, and considering contamination and defect. Last, the first fully polynomial time approximation scheme (FPTAS) is proposed for the delay driven discrete gate sizing problem, which explores the theoretical view since the existing works are heuristics with no performance guarantee. The intellectual contribution of the proposed methods establishes a novel paradigm bridging the gaps between professional communities.

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Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

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Power system policies are broadly on track to escalate the use of renewable energy resources in electric power generation. Integration of dispersed generation to the utility network not only intensifies the benefits of renewable generation but also introduces further advantages such as power quality enhancement and freedom of power generation for the consumers. However, issues arise from the integration of distributed generators to the existing utility grid are as significant as its benefits. The issues are aggravated as the number of grid-connected distributed generators increases. Therefore, power quality demands become stricter to ensure a safe and proper advancement towards the emerging smart grid. In this regard, system protection is the area that is highly affected as the grid-connected distributed generation share in electricity generation increases. Islanding detection, amongst all protection issues, is the most important concern for a power system with high penetration of distributed sources. Islanding occurs when a portion of the distribution network which includes one or more distributed generation units and local loads is disconnected from the remaining portion of the grid. Upon formation of a power island, it remains energized due to the presence of one or more distributed sources. This thesis introduces a new islanding detection technique based on an enhanced multi-layer scheme that shows superior performance over the existing techniques. It provides improved solutions for safety and protection of power systems and distributed sources that are capable of operating in grid-connected mode. The proposed active method offers negligible non-detection zone. It is applicable to micro-grids with a number of distributed generation sources without sacrificing the dynamic response of the system. In addition, the information obtained from the proposed scheme allows for smooth transition to stand-alone operation if required. The proposed technique paves the path towards a comprehensive protection solution for future power networks. The proposed method is converter-resident and all power conversion systems that are operating based on power electronics converters can benefit from this method. The theoretical analysis is presented, and extensive simulation results confirm the validity of the analytical work.