Paper Key : IRJ************672
Author: Anand Ghidole,Shailendra Kumar Bohidar
Date Published: 15 Apr 2024
Abstract
Due to its clean and renewable nature, wind energy is becoming one of the important renewable sources of energy in the world. Through its collaboration with other renewable sources of energy, such as solar energy, the world energy crises can be solved in the future. Comparatively with the past and due to the progressive integration of the nonlinear loads in the grid, the principal role of a Wind Energy Conversion System (WECS) is not only to capture the maximum power from the wind, but also to improve the quality of power. Consequently, with the development of the wind farms which are integrated into the grid, power quality could be better improved in the future. In this work Variable speed wind generator are used which is more attractive than fixed speed systems because of their efficient energy production, improved power quality and dynamic performance during grid faults. Here we design simulation model of wind power plant using doubly fed induction generator with PI controller and pitch control system for mitigation of power quality issue. Results obtained by both system shows the output power (active and reactive) are free from harmonics and it is stable. The global transition towards sustainable energy sources has led to a significant increase in the integration of wind power into the electricity grid. While wind energy offers numerous environmental benefits, its intermittent nature and variability pose challenges to power quality within the grid. This abstract outline a comprehensive study aimed at enhancing the performance of wind power systems with a specific emphasis on addressing power quality issues. The research investigates the impact of wind power integration on the grid's power quality parameters, including voltage stability, frequency regulation, and harmonics. A detailed analysis of the existing power quality standards and regulations is conducted to identify gaps and potential areas for improvement. The study explores advanced control strategies, grid integration techniques, and energy storage solutions to mitigate power quality concerns associated with wind power fluctuations. Furthermore, the research delves into the development and implementation of intelligent monitoring and control systems to enhance the predictability and reliability of wind power generation. Advanced sensor technologies and machine learning algorithms are employed to predict wind power variations and optimize the performance of grid-connected wind farms. The integration of energy storage systems and smart grid technologies is explored to buffer the effects of intermittent wind power generation and enhance overall grid stability. The findings of this study contribute valuable insights into the effective integration of wind power systems while maintaining high power quality standards. The proposed enhancements not only address the challenges posed by the variable nature of wind energy but also pave the way for a more resilient and sustainable energy infrastructure. The research outcomes are expected to guide future developments in wind power technology, facilitating a seamless transition towards a cleaner and more reliable energy landscape