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A Statistical Analysis Model of Wind Power Generation Forecasting for the Western Region of India
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  • Sulagna Mahata ,
  • Piyush Harsh ,
  • Vineet Shekher ,
  • Pankaj Rai
Sulagna Mahata
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Piyush Harsh
BIT Sindri, BIT Sindri

Corresponding Author:[email protected]

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Vineet Shekher
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Pankaj Rai
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Abstract

Wind energy has witnessed an upswing, with the improvement in current technology and cost-effective electricity production but due to uncertain wind behaviour and weather trends, it is essential to forecast wind energy. The paper presents the Autoregressive Integrated Moving Average model, a statistical analysis model, to forecast future power generation values, for the Kutch region of Gujarat, India. The historical wind power generation data and weather parameters have been taken into consideration for the predictive analysis of future trends in power generation. Wind power generation is dependent on various weather factors like wind speed, wind direction, temperature, humidity, air density, etc. The historical data obtained from Central Electricity Authority (CEA), India, and weather data collected from regional weather stations have been made into use for the forecast. A summary of the results is shown using the performance metrics for model evaluation, indicating that the model can forecast wind power generation with higher accuracy.