Wind Power: Predicting UK's Energy Generation
Forecasting UK's offshore and onshore wind power
Project Details
Industry
Energy
Client
Energy tech company
Technologies
Project Overview
This project tackles the challenge of forecasting wind power generation in the UK, encompassing both offshore and onshore wind farms to support the country's clean energy transition.
Wind energy plays a critical role in this transition by offering a clean and abundant alternative to fossil fuels, with the UK emerging as a leader in wind energy adoption.
UK Wind Energy Landscape
The UK has emerged as a leader in wind energy adoption, boasting over 14GW of installed capacity and a staggering 23GW planned for the future. However, one key hurdle remains: accurately predicting wind power output.
Wind Energy
Sustainable power source with variable output
The Challenge of Wind Power Prediction
The very nature of wind makes it notoriously difficult to predict. Wind power generation fluctuates constantly due to a complex interplay of factors:
Weather Patterns
Complex and rapidly changing weather systems affect wind speed and direction across the region.
Geographical Location
Different coastal and inland locations experience distinct wind patterns requiring local modeling.
Temporal Factors
Time of day, season, and longer-term climate patterns all influence wind generation capability.
This unpredictability poses a significant challenge for grid management and ensuring a stable and reliable energy supply, making accurate forecasting critical for the energy sector.
Our Solution
Our project addresses this challenge by developing an advanced machine learning model specifically designed for day-ahead wind power forecasting. This innovative model goes beyond existing solutions, like those used by Elexon, by incorporating a bias-correcting linear model.
Technical Approach
- 1Multi-variable data integration from weather and historical generation
- 2Advanced time series modeling with specialized neural networks
- 3Bias-correcting linear model to improve accuracy
- 4Regional models for onshore and offshore wind farms
Performance Improvement
Accuracy improvement over Elexon's forecasting system