Error-Based Wind Power Prediction Technique Based on Generalized Factors Analysis with Improved Power System Reliability

Abstract

As a green energy source, the use of wind has been rapidly growing in recent years. Whereas wind has complex and stochastic nature hence precise wind power predictions are essential for economic operation of the wind energy systems. For utilities, the rapid variations in wind power can generate serious problem of reliability reduction. The forecasting of wind power changes allows a utility to plan the connection and disconnection of wind power generation based on forecasting wind power generation and predicted load. In this paper, an environment friendly wind power prediction technique of variable-speed wind power system is proposed. The technique is employed from the prediction algorithm to create a prediction model to get accurate power. It is authenticated on the producer power curve of the variable-speed wind system. Additionally, the technique is used in average monthly wind power prediction and the outcomes show a huge improvement in prediction accuracy using the proposed method. Further, the likely value of rated wind speed for installed wind power system in Vishakhapatnam, Bhopal, Ahmedabad, Thiruvananthapuram, Bangalore, India, are also discussed. The empirical outcomes are compared with different wind forecast models and based on the root mean square error (RMSE), the proposed model gives the perfection in prediction accuracy compared to Gaussian Processes and Numerical Weather Prediction, Wind power prediction without adjustment, Wind power prediction with adjustment, support vector machine methods. Further, the developed model is used to evaluate the annual reliability indices by convolving the predicted generation with predicted load in the selected station.

KEYWORDS:

• Generalized factor analysis
• Meteorological parameters
• Smart grid
• Wind power forecasting

Additional information

Notes on contributors

Iram Akhtar

Iram Akhtar received the BTech degree in electrical engineering from BBDNITM, Lucknow in 2010 and the MTech degree in power electronics and drives from Madan Mohan Malaviya University of Technology (formerly Madan Mohan Malaviya Engineering College), Gorakhpur in 2012. She obtained PhD degree in electrical engineering at Jamia Millia Islamia (A Central University), New Delhi, India. Her current research interest includes the renewable energy sources (solar and wind), microgrid, grid integration of renewable energy sources, electrical machines and electrical drives. [email protected]; [email protected]; [email protected]

Sheeraz Kirmani

Sheeraz Kirmani joined the Department of Electrical Engineering, Jamia Millia Islamia in July 2012. Earlier he has worked as a lecturer with the Department of Energy and Environment, TERI University, New Delhi, India. He completed his BTech in electrical engineering from Aligarh Muslim University, Aligarh (A central university) in 2005, MTech in energy studies from the Indian Institute of Technology Delhi. In 2007, PhD from Jamia Millia Islamia (A central university), New Delhi, India in 2014 in the area of distributed solar power generation. He has published/presented many papers in various peer-reviewed international journals and conferences. He visited Open University, Milton Keynes, United Kingdom under the UKIERI grant. His current research interest includes new and renewable energy sources (solar and wind), resource assessment, smart grids, distributed generation, grid integration of renewable energy sources, application of intelligent techniques to electrical power systems, smart grid, and reactive power compensation. He is a life member of ICTP. Email: [email protected]; [email protected]