Document Type

Theses, Masters


Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence


Electrical and electronic engineering

Publication Details

Masters Dissertation, Heriot - Watt University


This research aimed to examine the percentage error in forecasting of wind energy using datasets from a small wind farm in Ireland. Furthermore, the study aimed to compare this calculated data to the national forecasting percentage errors. Internationally, the electrical sector and society are undergoing a revolution in terms of 'green economy'. This paradigm shift towards renewable energy technologies is recognised as a priority, with diminution of finite fossil fuels at its core. Renewable energy as a sector has provided significant financial stimulation to global economies in recent years. Moreover, wind energy has provided significant amounts of clean electricity throughout the world. However, due to its very nature, wind energy presents uncertainties which lead to errors in forecasting, which this study aimed to analyse. It is believed that accurate wind energy forecasting will allow establishment of an appropriate generation mix in future electrical networks. Thus, forecasting and percentage error is essential to wind energy integration, especially as installed capacity is estimated to increase substantially in the coming years. Using datasets based on various time series, this research collated, calculated and analysed the percentage error between predicted and actual wind energy output from a small wind farm (micro level) and at a national level (macro level). The findings of the research were that at the micro level there was a percentage error of -0.36% and at the macro level a percentage error of 5.7% over a twelve month period. The data in this study gives great insight into wind energy forecasting and the research discusses the effects of percentage errors in the renewable energy sector as wind capacity increases.