Stochastic time series forecasting of electricity costs in an NHS acute care hospital building, for use in whole life cycle costing Available to Purchase

Through a case study, this paper reports on a research project to develop a risk integrated methodology for forecasting the cost of electricity in a National Health Service (NHS) acute care hospital building. The paper is formed of two strands. Strand one presents a rationale for selecting an appropriate time series forecasting method and strand two looks at the implementation of probabilistic modelling of the forecasts generated in strand one. The results of the research revealed that the Holt‐Winters multiplicative forecasting method produced the most reliable forecasts. The probabilistic modelling of the forecasts revealed that after a pair‐wise comparison between data collected at the hospital used as the case study and data collected from NHS acute care trusts nationwide, the forecasts were most likely to belong to the Weibull distribution. The results could then be used as inputs into a whole life cycle cost model or as a stand‐alone forecasting technique for predicting future electricity costs for use in the NHS Trust Financial Proforma returns.