جستجوی مقالات مرتبط با کلیدواژه "control strategy" در نشریات گروه "برق"

Wind power generation is making an increasingly significant contribution to global electricity production. The high penetration of wind power poses many operational and control challenges that affects the reliability and stability of power systems. In this Paper, the reported technical challenges caused by the grid integration of wind energy conversion system (WECS) and the proposed solutions methodologies represents. The wind-generating system components and architecture are investigated at the beginning of this article for analysis and stability studies purposes, then are addressed various technical challenges; each challenge is discussed individually, focusing on the bulk integration of wind energy into the power systems. Some solutions, including grids code, energy storage technologies, appropriate control strategies, and other methodologies employed to mitigate the effects of the integration, are also included. This review is ready-reckoner of essential topics for further research of wind energy and available technologies in this field. This review provides ready-reckoner of essential topics for grid integration of wind energy and available technologies in direction of overcome the related difficulties.

This paper presents a new approach to optimizing of the control strategy in parallel hybrid vehicles. By proposing a new objective function and in order to efficient management of the power split between the combustion and electrical motors, fuel consumption and the amount of emissions are minimized with considering the penalty functions. Using the ADVISOR software, as one of the most common software used for a hybrid vehicle, as well as nonlinear equations of these vehicles, a parallel hybrid vehicle in the urban driving cycle of the United States is simulated. In this paper, an extended algorithm based on the Particle Swarm Optimization (PSO) is used. In the proposed PSO algorithm, the coefficients of contraction and the mirror effect of speed are used to increase the efficiency of the method. With the new constraints proposed for the PSO algorithm, the results have been improved. Also, simulation results are compared with the results obtained from the algorithms presented in recent papers. This comparison also shows the efficiency and accuracy of the proposed algorithm in optimizing the control parameters that lead to reduced fuel consumption and emissions from the vehicle.