939 resultados para Active power interpolation
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Usually, ancillary services are provided by large conventional generators; however, with the growing interest in distributed generation to satisfy energy and environmental requirements, it seems reasonable to assume that these services could also be provided by distributed generators in an economical and efficient way. In this paper, a proposal for enhancement of the capacity of active power reserve for frequency control using distributed generators is presented. The goal is to minimize the payments done by the transmission system operator to conventional and distributed generators for this ancillary service and for the energy needed to satisfy loads and system losses, subject to a set of constraints. In order to perform analysis, the proposal was implemented using data of the IEEE 30-bus transmission test system. Comparisons were performed considering conventional generators without and with distributed generators installed in the system.
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In a smart grid environment, attention should be paid not only to the power supplied to satisfy loads and system losses but also to the services necessary to provide security and stability to the system: the so-called ancillary services. As they are well known the benefits that distributed generation can bring to electrical systems and to the environment, in this work the possibility that active power reserve for frequency control could be provided by distributed generators (DGs) in an efficient and economical way is explored. The proposed methodology was tested using the IEEE 34-bus distribution test system. The results show improvements in the capacity of the system for this ancillary service and decrease in system losses and payments of the distribution system operator to the DGs.
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The Solid Oxide Fuel Cell (SOFC) is a class of fuel cells that is capable of generating very high levels of power at high temperatures. SOFCs are used for stationary power generation and as Combined Heat and Power (CHP) systems. In spite of all the beneficial features of the SOFC, the propagation of ripple currents, due to nonlinear loads, is a challenging problem, as it interferes with the physical operation of the fuel cell. The purpose of this thesis is to identify the cause of ripples and attempt to eliminate or reduce the ripple propagation through the use of Active Power Filters (APF). To this end, a systematic approach to modeling the fuel cell to account for its nonlinear behavior in the presence of current ripples is presented. A model of a small fuel cell power system which consists of a fuel cell, a DC-DC converter, a single-phase inverter and a nonlinear load is developed in MATLAB/Simulink environment. The extent of ripple propagation, due to variations in load magnitude and frequency, are identified using frequency spectrum analysis. In order to reduce the effects of ripple propagation, an APF is modeled to remove ripples from the DC fuel cell current. The emphasis of this thesis is based on the idea that small fuel cell systems cannot implement large passive filters to cancel the effects of ripple propagation and hence, the compact APF topology effectively protects the fuel cell from propagating ripples and improves its electrical performance.
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Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Mecânica /Energia
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The first monolithically integrated 44 switch with power monitoring function using on-chip PIN photodiodes is reported. Using 10Gb/s signals, under active power control an IPDR of 12dB for a 1dB power penalty is achieved. © 2012 OSA.
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Considering the operation of shunt active compensators, such as active power filters, this paper proposes possible compensation strategies by means of the recent formulation of the Conservative Power Theory (CPT). The CPT current's decomposition results in several current components, which are associated with specific load characteristics (power transfer, energy storage, unbalances and/or non linearities). These current components are used for the definition of different compensation strategies, which can be selective in terms of minimizing particular disturbing effects. In order to validate the applicability of these new compensation strategies, simulation and experimental results for three-phase four-wire systems are presented. © 2011 IEEE.
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Based on the framework of the Conservative Power Theory (CPT), this paper proposes some compensation strategies for shunt current compensators. CPT current decompositions result in several current-related terms associated with specific load characteristics, such as power consumption, energy storage, unbalances and load nonlinearities. These current components are decoupled (orthogonal) from each other and are used here to define different compensation strategies, which can be selective in minimizing particular effects of disturbing loads. Compensation strategies for single- and three-phase four-wire circuits are also considered. Simulated and experimental results are described to validate the possibilities and performance of the proposed strategies. © 2013 Brazilian Society for Automatics - SBA.
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When the supply voltages are balanced and sinusoidal, load compensation can give both unity power factor (UPF) and perfect harmonic cancellation (PHC) source currents. But under distorted supply voltages, achieving both UPF and PHC currents are not possible and contradictory to each other. Hence there should be an optimal performance between these two important compensation goals. This paper presents an optimal control algorithm for load compensation under unbalanced and distorted supply voltages. In this algorithm source currents are compensated for reactive, imbalance components and harmonic distortions set by the limits. By satisfying the harmonic distortion limits and power balance, this algorithm gives the source currents which will provide the maximum achievable power factor. The detailed simulation results using MATLAB are presented to support the performance of the proposed optimal control algorithm.
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A Three-Phase Nine-Switch Converter (NSC) topology for Doubly Fed Induction Generator in wind energy generation is proposed in this paper. This converter topology was used in various applications such as Hybrid Electric Vehicles and Uninterruptable Power Supplies. In this paper, Nine-Switch Converter is introduced in Doubly Fed Induction Generator in renewable energy application for the first time. It replaces the conventional Back-to-Back Pulse Width Modulated voltage source converter (VSC) which composed of twelve switches in many DFIG applications. Reduction in number of switches is the most beneficial in terms of cost and power switching losses. The operation principle of Nine-Switch Converter using SPWM method is discussed. The resulting NSC performance of rotor side current control, active power and reactive control are compared with Back-to Back voltage source converter performance. DC link voltage regulation using front end converter is also presented. Finally the simulation results of DFIG performances using NSC and Back-to-Back VSC are analyzed and compared.
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This paper proposes a method of sharing power/energy between multiple sources and multiple loads using an integrated magnetic circuit as a junction between sources and sinks. It also presents a particular use of the magnetic circuit as an ac power supply, delivering sinusoidal voltage to load irrespective of the presence of the grid, taking only active power from the grid. The proposed magnetic circuit is a three-energy-port unit, viz.: 1) power/energy from grid; 2) power energy from battery-inverter unit; and 3) power/energy delivery to the load in its particular application as quality ac power supply (QPS). The product provides sinusoidal regulated output voltage, input power-factor correction, electrical isolation between the sources and loads, low battery voltage, and control simplicity. Unlike conventional series-shunt-compensated uninterruptible power supply topologies with low battery voltage, the isolation is provided using a single magnetic circuit that results in a smaller size and lower cost. The circuit operating principles and analysis, as well as simulation and experimental results, are presented for this QPS.
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In this paper, a method of tracking the peak power in a wind energy conversion system (WECS) is proposed, which is independent of the turbine parameters and air density. The algorithm searches for the peak power by varying the speed in the desired direction. The generator is operated in the speed control mode with the speed reference being dynamically modified in accordance with the magnitude and direction of change of active power. The peak power points in the P-omega curve correspond to dP/domega = 0. This fact is made use of in the optimum point search algorithm. The generator considered is a wound rotor induction machine whose stator is connected directly to the grid and the rotor is fed through back-to-back pulse-width-modulation (PWM) converters. Stator flux-oriented vector control is applied to control the active and reactive current loops independently. The turbine characteristics are generated by a dc motor fed from a commercial dc drive. All of the control loops are executed by a single-chip digital signal processor (DSP) controller TMS320F240. Experimental results show that the performance of the control algorithm compares well with the conventional torque control method.
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A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.
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An energy storage system (ESS) installed in a power system can effectively damp power system oscillations through controlling exchange of either active or reactive power between the ESS and power system. This paper investigates the robustness of damping control implemented by the ESS to the variations of power system operating conditions. It proposes a new analytical method based on the well-known equal-area criterion and small-signal stability analysis. By using the proposed method, it is concluded in the paper that damping control implemented by the ESS through controlling its active power exchange with the power system is robust to the changes of power system operating conditions. While if the ESS damping control is realized by controlling its reactive power exchange with the power system, effectiveness of damping control changes with variations of power system operating condition. In the paper, an example power system installed with a battery ESS (BESS) is presented. Simulation results confirm the analytical conclusions made in the paper about the robustness of ESS damping control. Laboratory experiment of a physical power system installed with a 35kJ/7kW SMES (Superconducting Magnetic Energy Storage) was carried out to evaluate theoretical study. Results are given in the paper, which demonstrate that effectiveness of SMES damping control realized through regulating active power is robust to changes of load conditions of the physical power system.
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A three-phase four-wire shunt active power filter for harmonic mitigation and reactive power compensation in power systems supplying nonlinear loads is presented. Three adaptive linear neurons are used to tackle the desired three-phase filter current templates. Another feedforward three-layer neural network is adopted to control the output filter compensating currents online. This is accomplished by producing the appropriate switching patterns of the converter's legs IGBTs. Adequate tracking of the filter current references is obtained by this method. The active filter injects the current required to compensate for the harmonic and reactive components of the line currents, Simulation results of the proposed active filter indicate a remarkable improvement in the source current waveforms. This is reflected in the enhancement of the unified power quality index defined. Also, the filter has exhibited quite a high dynamic response for step variations in the load current, assuring its potential for real-time applications
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The increasing penetration of wind generation on the Island of Ireland has been accompanied by close investigation of low-frequency pulsations contained within active power flow. A primary concern is excitation of low-frequency oscillation modes already present on the system, particularly the 0.75 Hz mode as a consequence of interconnection between the Northern and Southern power system networks. In order to determine whether the prevalence of wind generation has a negative effect (excites modes) or positive impact (damping of modes) on the power system, oscillations must be measured and characterised. Using time – frequency methods, this paper presents work that has been conducted to extract features from low-frequency active power pulsations to determine the composition of oscillatory modes which may impact on dynamic stability. The paper proposes a combined wavelet-Prony method to extract modal components and determine damping factors. The method is exemplified using real data obtained from wind farm measurements.