Showing 25–36 of 256 results
Adaptive PI Control of Dynamic Voltage Restorer Using Fuzzy Logic
PI controller is verرایگان!
PI controller is very common in the control of DVRs. However, one disadvantage of this conventional controller is the fact that by using fixed gains, the controller may not provide the required control performance, when there are variations in the system parameters or operating conditions. To overcome this problem, an adaptive PI controller using fuzzy logic is proposed. The controller is composed of fuzzy controller and PI controller. According to the error and error rate of the control system and fuzzy control rules, the fuzzy controller can online adjust the two parameters of the PI controller in order to be adapted to any variations in the operating conditions. The simulation results have proved that the proposed control method greatly improves the performance of the DVR compared to the conventional PI controller.
Advanced Control Architectures for Intelligent Microgrids – Part II: Power Quality, Energy Storage, and AC/DC MicroGrids
This paper summarizeرایگان!
This paper summarizes the main problems and solutions of power quality in Microgrids, distributed energy storage systems, and AC/DC hybrid Microgrids. First, power quality enhancement of grid-interactive Microgrids is presented. Then, cooperative control for enhance voltage harmonics and unbalances in Microgrids is reviewed. After, the use of static synchronous compensator (STATCOM) in grid-connected Microgrids is introduced in order to improve voltage sags/swells and unbalances. Finally, the coordinated control of distributed storage systems and AC/DC hybrid microgrids is explained.
An Accurate Power Control Strategy for Power-Electronics-Interfaced Distributed Generation Units Operating in a Low-Voltage Multibus Microgrid
In this paper, a powرایگان!
In this paper, a power control strategy is proposed for a low-voltage microgrid, where the mainly resistive line impedance, the unequal impedance among distributed generation (DG) units, and the microgrid load locations make the conventional frequency and voltage droop method unpractical. The proposed power control strategy contains a virtual inductor at the interfacing inverter output and an accurate power control and sharing algorithm with consideration of both impedance voltage drop effect and DG local load effect. Specifically, the virtual inductance can effectively prevent the coupling between the real and reactive powers by introducing a predominantly inductive impedance even in a lowvoltage network with resistive line impedances. On the other hand, based on the predominantly inductive impedance, the proposed accurate reactive power sharing algorithm functions by estimating the impedance voltage drops and significantly improves the reactive power control and sharing accuracy. Finally, considering the different locations of loads in a multibus microgrid, the reactive power control accuracy is further improved by employing an online estimated reactive power offset to compensate the effects of DG local load power demands. The proposed power control strategy has been tested in simulation and experimentally on a low-voltage microgrid prototype.
An Adaptive Control Strategy for DSTATCOM Applications in an Electric Ship Power System
Distribution static compensator (DSTATCOM) is a shunt compensation device that is generally used to solve power quality problems in distribution systems. In an all-electric ship power system, power quality issues arise due to high-energy demand loads such as pulse loads. This paper presents the application of a DSTATCOM to improve the power quality in a ship power system during and after pulse loads. The control strategy of the DSTATCOM plays an important role in maintaining the voltage at the point of common coupling. A novel adaptive control strategy for the DSTATCOM based on artificial immune system (AIS) is presented in this paper. The optimal parameters of the controller are first obtained by using the particle swarm optimization algorithm. This provides a sort of innate immunity (robustness) to common system disturbances. For unknown and random system disturbances, the controller parameters are modified online ,thus providing adaptive immunity to the control system. The performance of the DSTATCOM and the AIS-based adaptive control strategy is first investigated in MATLAB-/Simulink-based simulation platform. It is verified through a real-time ship power system implementation on a real-time digital simulator and the control algorithm on a digital signal processor
An Adaptive Controller for Power System Stability Improvement and Power Flow Control by Means of a Thyristor Switched Series Capacitor (TSSC)
In this paper, a conرایگان!
In this paper, a controller for a thyristor switched series capacitor (TSSC) is presented. The controller aims to stabilize the power system by damping interarea power oscillations and by improving the transient stability of the system. In addition to this, a power flow control feature is included in the controller. The power oscillation damping controller is designed based on a nonlinear control law, while the transient stability improvement feature works in open loop. The damping controller is adaptive and estimates the power system parameters according to a simplified generic model of a two-area power system. It is designed for systems where one poorly damped dominant mode of power oscillation exists. In the paper, a verification of the controller by means of digital simulations of one two-area, four-machine power system, and one 23-machine power system is presented. The results show that the controller improves the stability of both test systems significantly in a number of fault cases at different levels of interarea power flow.
An energy efficient approach to extend network life time of wireless sensor networks
The energy consumptiرایگان!
The energy consumption in wireless sensor networks is a significant matter and there are many ways to conserve energy. The use of mobile sensors is of great relevance to minimize the total energy dissipation in communication and overhead control packets. In a WSN, sensor nodes deliver sensed data back to the sink via multi hopping. The sensor nodes near the sink will usually consume more battery power than others; consequently, these nodes will quickly drain out their battery energy and decrease in the network lifetime of the WSN. The presence of mobilesinks causes increased energy reduction in their proximity, due to more relay load under multi hop communication. Moreover, node deployment technique can also be used to improve the life time of the network. Performance comparisons have been done by simulations between different routing protocols and our approach show efficient results.
An Enhanced DC Preexcitation With Effective Flux-Linkage Control for the High-Power Induction Motor Drive System
This paper proposedرایگان!
This paper proposed an enhanced dc preexcitation for a variable-voltage variable-frequency-controlled induction motor drive system. Voltage vectors were adjusted according to the reactive component of the motor current, which promptly established the effective value of the motor flux linkage at the preexcitation stage and restrained its trajectory strictly as a round circle all through the starting process. The enhanced dc preexcitation control led to more negligible flux-linkage distortion, less torque vibration, and significantly smaller inrush current. Experiments on a 380-VAC/315-kW adjustable speed drive system validated the effectiveness of the proposed method.
An improved PSO-based charging strategy of electric vehicles in electrical distribution grid
Driven by the desireرایگان!
Driven by the desire to reduce environmental impacts and achieve energy independence, electric vehicles (EVs) are poised to receive mass acceptance from the general public. However, simultaneously connecting to electric distribution grid and charging with large number of EVs bring the necessity of optimizing the charging and discharging behaviors of EVs, due to the security and economy issue of the grid operation. To address this issue, we propose a novel EV charging model in this paper. The model concerns with following aspects, including optimal power flow (OPF), statistic characteristics of EVs, EV owners’ degree of satisfaction (DoS), and the power grid cost. An improved particle swarm optimization (PSO) algorithmis proposed for the model optimization. To evaluate our proposed optimal EV charging strategy, a 10-bus power distribution system simulation is performed for performance investigation. Simulation resultsshow that the proposed strategy can reduce the operational cost of the power grid considerately, while meeting the EV owner’s driving requirement. Also, better performance on the global search capability and optimal result of the improved particle swarm optimization algorithm is verified.
An improved PSO-based charging strategy of electric vehicles in electrical distribution grid
Driven by the desireرایگان!
Driven by the desire to reduce environmental impacts and achieve energy independence, electric vehicles (EVs) are poised to receive mass acceptance from the general public. However, simultaneously connecting to electric distribution grid and charging with large number of EVs bring the necessity of optimizing the charging and discharging behaviors of EVs, due to the security and economy issue of the grid operation. To address this issue, we propose a novel EV charging model in this paper. The model concerns with following aspects, including optimal power flow (OPF), statistic characteristics of EVs, EV owners’ degree of satisfaction (DoS), and the power grid cost. An improved particle swarm optimization (PSO) algorithm is proposed for the model optimization. To evaluate our proposed optimal EV charging strategy, a 10-bus power distribution system simulation is performed for performance investigation. Simulation results show that the proposed strategy can reduce the operational cost of the power grid considerately, while meeting the EV owner’s driving requirement. Also, better performance on the global search capability and optimal result of the improved particle swarm optimization algorithm is verified.
An SVM-Based Solution for Fault Detection in Wind Turbines
Research into faultرایگان!
Research into fault diagnosis in machines with a wide range of variable loads and speeds, such as wind turbines, is of great industrial interest. Analysis of the power signals emitted by wind turbines for the diagnosis of mechanical faults in their mechanical transmission chain is insufficient. A successful diagnosis requires the inclusion of accelerometers to evaluate vibrations. This work presents a multi-sensory system for fault diagnosis in wind turbines, combined with a data-mining solution for the classification of the operational state of the turbine. The selected sensors are accelerometers, in which vibration signals are processed using angular resampling techniques and electrical, torque and speed measurements. Support vector machines (SVMs) are selected for the classification task, including two traditional and two promising new kernels. This multi-sensory system has been validated on a test-bed that simulates the real conditions of wind turbines with two fault typologies: misalignment and imbalance. Comparison of SVM performance with the results of artificial neural networks (ANNs) shows that linear kernel SVM outperforms other kernels and ANNs in terms of accuracy, training and tuning times. The suitability and superior performance of linear SVM is also experimentally analyzed, to conclude that this data acquisition technique generates linearly separable datasets.
Analysis of performance losses of thermal power plants in Germany e A System Dynamics model approach using data from regional climate modelling
The majority of therرایگان!
The majority of thermal power plants of more than 300 MW use river water for cooling purposes. Increasing water and air temperatures due to climate change can significantly impact the efficiency and the power production of these power plants. In this paper we analyse these impacts by modelling selected German thermal power plant units and their respective cooling systems through dynamic simulation taking into account legal thresholds for heat discharges to river water together with climate data projections (SRES scenarios A1B, A2, and B1). Possible output and efficiency reductions in the future (2011e2040 and 2041e2070) are quantified for thermal power plants with once-through (OTC) and losed-circuit (CCC) cooling systems under current legislative framework. The model validation showed that the chosen System Dynamics approach is appropriate to analyse impacts of climate change on thermal power units. The model results indicate lowest impacts for units with CCC systems: The mean trend for CCC for the A1B scenario (2011e2070) is expected to be 0.10 MW/a and 0.33 MW/a for an OTC system. On a daily basis, the power output of all considered OTC units is reduced down to 66.4% of the nominal capacity, for a single unit even down to 32%.