937 resultados para power distribution control


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IEEE International Symposium on Circuits and Systems, pp. 2258 – 2261, Seattle, EUA

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This study is based on a previous experimental work in which embedded cylindrical heaters were applied to a pultrusion machine die, and resultant energetic performance compared with that achieved with the former heating system based on planar resistances. The previous work allowed to conclude that the use of embedded resistances enhances significantly the energetic performance of pultrusion process, leading to 57% decrease of energy consumption. However, the aforementioned study was developed with basis on an existing pultrusion die, which only allowed a single relative position for the heaters. In the present work, new relative positions for the heaters were investigated in order to optimize heat distribution process and energy consumption. Finite Elements Analysis was applied as an efficient tool to identify the best relative position of the heaters into the die, taking into account the usual parameters involved in the process and the control system already tested in the previous study. The analysis was firstly developed with basis on eight cylindrical heaters located in four different location plans. In a second phase, in order to refine the results, a new approach was adopted using sixteen heaters with the same total power. Final results allow to conclude that the correct positioning of the heaters can contribute to about 10% of energy consumption reduction, decreasing the production costs and leading to a better eco-efficiency of pultrusion process.

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This work was undertaken in the municipality of Pedro de Toledo (São Paulo State, Brazil) in 1987, to clarify aspects related to the transmission levels of Schistosoma mansoni in a human population where the snail host is Biomphalaria tenagophila. Since 1980 a control programme has been undertaken in this municipality. Urban and rural populations (4,719 subjects) were submitted to faecal examinations (Kato-Katz method). The overall prevalence rate was 4.8% being higher in males (6.2%) and also in the rural zone (5.8%). The geometric mean of S. mansoni eggs was 35.1 eggs per gramme of faeces (epg). Approximately 80.0% of the carriers presented less than 100 epg and only 20 individuals (9.0%) eliminated more than half of total eggs. The highest index of potencial contamination (IPC) was in the age group of 5 to 20 years (57.6%). Two thirds of the investigated patients (207) were autochthonous of Pedro de Toledo. The geographical distribution of the carriers showed a clear aggregation of the autochthonous cases and a close association between human contact sites and breeding places of B. tenagophila. This study shows that schistosomiasis subjects were not randomly aggregated, the youngsters should be the main target in the prophylaxis, and the efficacy of the control programme.

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This paper is on an onshore variable speed wind turbine with doubly fed induction generator and under supervisory control. The control architecture is equipped with an event-based supervisor for the supervision level and fuzzy proportional integral or discrete adaptive linear quadratic as proposed controllers for the execution level. The supervisory control assesses the operational state of the variable speed wind turbine and sends the state to the execution level. Controllers operation are in the full load region to extract energy at full power from the wind while ensuring safety conditions required to inject the energy into the electric grid. A comparison between the simulations of the proposed controllers with the inclusion of the supervisory control on the variable speed wind turbine benchmark model is presented to assess advantages of these controls. (C) 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers.

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Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

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The use of a solar photovoltaic (PV) panel simulator can be a valued tool for the design and evaluation of the several components of a photovoltaic system. This simulator is based on power electronic converter controlled in such a way that will behave as a PV panel. Thus, in this paper a PV panel simulator based on a two quadrant DC/DC power converter is proposed. This topology will allow to achieve fast responses, like suddenly changes in the irradiation and temperature. To control the power converter it will be used a fast and robust sliding mode controller. Therefore, with the proposed system I-V curve simulation of a PV panel is obtained. Experimental results from a laboratory prototype are presented in order to confirm the theoretical operation.

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This paper is on a simulation for offshore wind systems in deep water under cloud scope. The system is equipped with a permanent magnet synchronous generator and a full-power three-level converter, converting the electric energy at variable frequency in one at constant frequency. The control strategies for the three-level are based on proportional integral controllers. The electric energy is injected through a HVDC transmission submarine cable into the grid. The drive train is modeled by a three-mass model taking into account the resistant stiffness torque, structure and tower in the deep water due to the moving surface elevation. Conclusions are taken on the influence of the moving surface on the energy conversion. © IFIP International Federation for Information Processing 2015.

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When China launched an anti-satellite (ASAT) weapon in January 2007 to destroy one of its inactive weather satellites, most reactions from academics and U.S. space experts focused on a potential military “space race” between the United States and China. Overlooked, however, is China’s growing role as global competitor on the non-military side of space. China’s space program goes far beyond military counterspace applications and manifests manned space aspirations, including lunar exploration. Its pursuit of both commercial and scientific international space ventures constitutes a small, yet growing, percentage of the global space launch and related satellite service industry. It also highlights China’s willingness to cooperate with nations far away from Asia for political and strategic purposes. These partnerships may constitute a challenge to the United States and enhance China’s “soft power” among key American allies and even in some regions traditionally dominated by U.S. influence (e.g., Latin America and Africa). Thus, an appropriate U.S. response may not lie in a “hard power” counterspace effort but instead in a revival of U.S. space outreach of the past, as well as implementation of more business-friendly export control policies.

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Demand response is assumed as an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets and of the increasing use of renewable-based energy sources. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed in this paper aims the minimization of the operation costs in a distribution network operated by a virtual power player that manages the available energy resources focusing on hour ahead re-scheduling. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs. Real time pricing is also applied. The proposed model is especially useful when actual and day ahead wind forecast differ significantly. Its application is illustrated in this paper implementing the characteristics of a real resources conditions scenario in a 33 bus distribution network with 32 consumers and 66 distributed generators.

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This paper proposes a wind speed forecasting model that contributes to the development and implementation of adequate methodologies for Energy Resource Man-agement in a distribution power network, with intensive use of wind based power generation. The proposed fore-casting methodology aims to support the operation in the scope of the intraday resources scheduling model, name-ly with a time horizon of 10 minutes. A case study using a real database from the meteoro-logical station installed in the GECAD renewable energy lab was used. A new wind speed forecasting model has been implemented and it estimated accuracy was evalu-ated and compared with a previous developed forecast-ing model. Using as input attributes the information of the wind speed concerning the previous 3 hours enables to obtain results with high accuracy for the wind short-term forecasting.

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The integration of growing amounts of distributed generation in power systems, namely at distribution networks level, has been fostered by energy policies in several countries around the world, including in Europe. This intensive integration of distributed, non-dispatchable, and natural sources based generation (including wind power) has caused several changes in the operation and planning of power systems and of electricity markets. Sometimes the available non-dispatchable generation is higher than the demand. This generation must be used; otherwise it is wasted if not stored or used to supply additional demand. New policies and market rules, as well as new players, are needed in order to competitively integrate all the resources. The methodology proposed in this paper aims at the maximization of the social welfare in a distribution network operated by a virtual power player that aggregates and manages the available energy resources. When facing a situation of excessive non-dispatchable generation, including wind power, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. This method is especially useful when actual and day-ahead resources forecast differ significantly. The distribution network characteristics and concerns are addressed by including the network constraints in the optimization model. The proposed methodology has been implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20.310 consumers and 548 distributed generators, some of them non-dispatchable and with must take contracts. The implemented scenario corresponds to a real day in Portuguese power system.

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This paper proposes a PSO based approach to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The statistical failure and repair data of distribution components is the main basis of the proposed methodology that uses a fuzzyprobabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A Modified Discrete PSO optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

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This paper presents a decision support tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy resource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

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The use of renewables have been increased I several countries around the world, namely in Europe. The wind power is generally the larger renewable resource with very specific characteristics in what concerns its variability and the inherent impacts in the power systems and electricity markets operation. This paper focuses on the Portuguese context of renewables use, including wind power. The work here presented includes the use of a real time pricing methodology developed by the authors aiming the reduction of electricity consumption in the moments of unexpected low wind power. A more specific example of application of real time pricing is demonstrated for the minimization of the operation costs in a distribution network. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs.