Electricity and utilities
Forecasting short-term electricity demand remains a prominent topic to utilities companies, due to the importance of future loads in the operation of utility plants, transmission systems and trading on energy markets. Fuelled by the competitiveness of today's deregulated and highly volatile electricity markets, small improvements in forecasting accuracy can account for large operational profits, far exceeding that of one million GBP in profits as an equivalent to1% improvement in accuracy on the UK market reported in the 1980s.
The Lancaster Centre for Forecasting has substantial expertise in applying both traditional statistical methods, as well as novel statistical contenders such as Triple Exponential Smoothing. Additionally we have extensive expertise with algorithms from artificial intelligence such as neural networks and k-nearest neighbours which are capable of capturing the underlying nonlinearities with temperature (in interaction with irradiance, cloud cover, precipitation, and/or wind chill) and able handle big time series data at the same time.