894 resultados para welding power source control
Resumo:
We describe remarkable success in controlling dengue vectors, Aedes aegypti (L.) and Aedes albopictus (Skuse), in 6 communes with 11,675 households and 49,647 people in the northern provinces of Haiphong, Hung Yen, and Nam Dinh in Vietnam. The communes were selected for high-frequency use of large outdoor concrete tanks and wells. These were found to be the source of 49.6-98.4% of Ae. aegypti larvae, which were amenable to treatment with local Mesocyclops, mainly M. woutersi Van der Velde, M. aspericornis (Daday) and M. thermocyclopoides Harada. Knowledge, attitude, and practice surveys were performed to determine whether the communities viewed dengue and dengue hemorrhagic fever as a serious health threat; to determine their knowledge of the etiology, attitudes, and practices regarding control methods including Mesocyclops; and to determine their receptivity to various information methods. On the basis of the knowledge, attitude, and practice data, the community-based dengue control program comprised a system of local leaders, health volunteer teachers, and schoolchildren, supported by health professionals. Recycling of discards for economic gain was enhanced, where appropriate, and this, plus 37 clean-up campaigns, removed small containers unsuitable for Mesocyclops treatment. A previously successful eradication at Phan Boi village (Hung Yen province) was extended to 7 other villages forming Di Su commune (1,750 households) in the current study. Complete control was also achieved in Nghia Hiep (Hung Yen province) and in Xuan Phong (Nam Dinh province); control efficacy was greater than or equal to 99.7% in the other 3 communes (Lac Vien in Haiphong, Nghia Dong, and Xuan Kien in Nam Dinh). Although tanks and wells were the key container types of Ae. aegypti productivity, discarded materials were the source of 51% of the standing crop of Ae. albopictus. Aedes albopictus larvae were eliminated from the 3 Nam Dinh communes, and 86-98% control was achieved in the other 3 communes. Variable dengue attack rates made the clinical and serological comparison of control and untreated communes problematic, but these data indicate that clinical surveillance by itself is inadequate to monitor dengue transmission.
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The inhibitory effect of sucrose on the kinetics of thrombin-catalyzed hydrolysis of the chromogenic substrate S-2238 (D-phenylalanyl-pipecolyl-arginoyl-p-nitroanilide) is re-examined as a possible consequence of thermodynamic non-ideality-an inhibition originally attributed to the increased viscosity of reaction mixtures. However, those published results may also be rationalized in terms of the suppression of a substrate-induced isomerization of thrombin to a slightly more expanded (or more asymmetric) transition state prior to the irreversible kinetic steps that lead to substrate hydrolysis. This reinterpretation of the kinetic results solely in terms of molecular crowding does not signify the lack of an effect of viscosity on any reaction step(s) subject to diffusion control. Instead, it highlights the need for development of analytical procedures that can accommodate the concomitant operation of thermodynamic non-ideality and viscosity effects.
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The integrated control of nitrate recirculation and external carbon addition in a predenitrification biological wastewater treatment system is studied. The proposed control structure consists of four feedback control loops, which manipulate the nitrate recirculation and the carbon dosage flows in a highly coordinated manner such that the consumption of external carbon is minimised while the nitrate discharge limits (based on both grab and composite samples) are met. The control system requires the measurement of the nitrate concentrations at the end of both the anoxic and the aerobic zones. Distinct from ordinary control systems, which typically minimise the variation in the controlled variables, the proposed control system essentially maximises the diurnal variation of the effluent nitrate concentration and through this maximises the use of influent COD for denitrification, thus minimising the requirement for external carbon source. Simulation studies using a commonly accepted simulation benchmark show that the controlled system consistently achieves the designated effluent quality with minimum costs.
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With recent advances in molecular biology, it is now possible to use the trace amounts of DNA in faeces to non-invasively sample endangered species for genetic studies. A highly vulnerable population of approximately 100 great bustards (Otis tarda) exists in Morocco necessitating the use of non-invasive protocols to study their genetic structure. Here we report a reliable silica-based method to extract DNA from great bustard faeces. We found that successful extraction and amplification correlated strongly with faeces freshness and composition. We could not extract amplifiable DNA from 30% of our samples as they were dry or contained insect material. However 100% of our fresh faecal samples containing no obvious insect material worked, allowing us to assess the levels of genetic variation among 25 individuals using a 542 bp control region sequence. We were able to extract DNA from four out of five other avian species, demonstrating that faeces represents a suitable source of DNA for population genetics studies in a broad range of species.
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Sliding mode controllers for power converters usually employ hysteresis comparators to directly generate the power semiconductors switching states. This paper presents a new sliding mode modulator based on the direct implementation of the sliding mode stability condition, which for multilevel power converters shows advantages, as branch equalized switching frequencies and less distortion on the ac currents when operating near the rated converter power. The new sliding mode multilevel modulator is used to control a three-phase multilevel converter, operated as a reactive power compensator (STATCOM), implementing the stability condition in a digital signal processing system. The performance of this new sliding mode modulator is compared with a multilevel modulator based on hysteresis comparators. Simulation and experimental results are presented in order to highlight the system operation and control robustness.
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Nowadays, the cooperative intelligent transport systems are part of a largest system. Transportations are modal operations integrated in logistics and, logistics is the main process of the supply chain management. The supply chain strategic management as a simultaneous local and global value chain is a collaborative/cooperative organization of stakeholders, many times in co-opetition, to perform a service to the customers respecting the time, place, price and quality levels. The transportation, like other logistics operations must add value, which is achieved in this case through compression lead times and order fulfillments. The complex supplier's network and the distribution channels must be efficient and the integral visibility (monitoring and tracing) of supply chain is a significant source of competitive advantage. Nowadays, the competition is not discussed between companies but among supply chains. This paper aims to evidence the current and emerging manufacturing and logistics system challenges as a new field of opportunities for the automation and control systems research community. Furthermore, the paper forecasts the use of radio frequency identification (RFID) technologies integrated into an information and communication technologies (ICT) framework based on distributed artificial intelligence (DAI) supported by a multi-agent system (MAS), as the most value advantage of supply chain management (SCM) in a cooperative intelligent logistics systems. Logistical platforms (production or distribution) as nodes of added value of supplying and distribution networks are proposed as critical points of the visibility of the inventory, where these technological needs are more evident.
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The reactive power management is an important task in future power systems. The control of reactive power allows the increase of distributed energy resources penetration as well as the optimal operation of distribution networks. Currently, the control of reactive power is only controlled in large power units and in high and very high voltage substations. In this paper a reactive power control in smart grids paradigm is proposed, considering the management of distributed energy resources and of the distribution network by an aggregator namely Virtual Power Player (VPP).
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The operation of power systems in a Smart Grid (SG) context brings new opportunities to consumers as active players, in order to fully reach the SG advantages. In this context, concepts as smart homes or smart buildings are promising approaches to perform the optimization of the consumption, while reducing the electricity costs. This paper proposes an intelligent methodology to support the consumption optimization of an industrial consumer, which has a Combined Heat and Power (CHP) facility. A SCADA (Supervisory Control and Data Acquisition) system developed by the authors is used to support the implementation of the proposed methodology. An optimization algorithm implemented in the system in order to perform the determination of the optimal consumption and CHP levels in each instant, according to the Demand Response (DR) opportunities. The paper includes a case study with several scenarios of consumption and heat demand in the context of a DR event which specifies a maximum demand level for the consumer.
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As wind power generation undergoes rapid growth, new technical challenges emerge: dynamic stability and power quality. The influence of wind speed disturbances and a pitch control malfunction on the quality of the energy injected into the electric grid is studied for variable-speed wind turbines with different power-electronic converter topologies. Additionally, a new control strategy is proposed for the variable-speed operation of wind turbines with permanent magnet synchronous generators. The performance of disturbance attenuation and system robustness is ascertained. Simulation results are presented and conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.
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In this paper we present VERITAS, a tool that focus time maintenance, that is one of the most important processes in the engineering of the time during the development of KBS. The verification and validation (V&V) process is part of a wider process denominated knowledge maintenance, in which an enterprise systematically gathers, organizes, shares, and analyzes knowledge to accomplish its goals and mission. The V&V process states if the software requirements specifications have been correctly and completely fulfilled. The methodologies proposed in software engineering have showed to be inadequate for Knowledge Based Systems (KBS) validation and verification, since KBS present some particular characteristics. VERITAS is an automatic tool developed for KBS verification which is able to detect a large number of knowledge anomalies. It addresses many relevant aspects considered in real applications, like the usage of rule triggering selection mechanisms and temporal reasoning.
Resumo:
This paper is on variable-speed wind turbines with permanent magnet synchronous generator (PMSG). Three different drive train mass models and three different topologies for the power-electronic converters are considered. The three different topologies considered are respectively a matrix, a two-level and a multilevel converter. A novel control strategy, based on fractional-order controllers, is proposed for the wind turbines. Simulation results are presented to illustrate the behaviour of the wind turbines during a converter control malfunction, considering the fractional-order controllers. Finally, conclusions are duly drawn. Copyright (C) 2010 John Wiley & Sons, Ltd.
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The main aims of this work are the development and the validation of one generic algorithm to provide the optimal control of small power wind generators. That means up to 40 kW and blades with fixed pitch angle. This algorithm allows the development of controllers to fetch the wind generators at the desired operational point in variable operating conditions. The problems posed by the variable wind intensity are solved using the proposed algorithm. This is done with no explicit measure of the wind velocity, and so no special equipment or anemometer is required to compute or measure the wind velocity.
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In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.
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Power system planning, control and operation require an adequate use of existing resources as to increase system efficiency. The use of optimal solutions in power systems allows huge savings stressing the need of adequate optimization and control methods. These must be able to solve the envisaged optimization problems in time scales compatible with operational requirements. Power systems are complex, uncertain and changing environments that make the use of traditional optimization methodologies impracticable in most real situations. Computational intelligence methods present good characteristics to address this kind of problems and have already proved to be efficient for very diverse power system optimization problems. Evolutionary computation, fuzzy systems, swarm intelligence, artificial immune systems, neural networks, and hybrid approaches are presently seen as the most adequate methodologies to address several planning, control and operation problems in power systems. Future power systems, with intensive use of distributed generation and electricity market liberalization increase power systems complexity and bring huge challenges to the forefront of the power industry. Decentralized intelligence and decision making requires more effective optimization and control techniques techniques so that the involved players can make the most adequate use of existing resources in the new context. The application of computational intelligence methods to deal with several problems of future power systems is presented in this chapter. Four different applications are presented to illustrate the promises of computational intelligence, and illustrate their potentials.
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Cyber-Physical Intelligence is a new concept integrating Cyber-Physical Systems and Intelligent Systems. The paradigm is centered in incorporating intelligent behavior in cyber-physical systems, until now too oriented to the operational technological aspects. In this paper we will describe the use of Cyber-Physical Intelligence in the context of Power Systems, namely in the use of Intelligent SCADA (Supervisory Control and Data Acquisition) systems at different levels of the Power System, from the Power Generation, Transmission, and Distribution Control Centers till the customers houses.