Energy Consumption Prediction


Energy Consumption Prediction

Energy consumption prediction is a quantitative analytical model processing historical data from clients and external factors, such as the weather or calendar, in order to make a precise estimate of future hourly energy consumption.

The share of energy costs in global GDP is approximately 10% and comprises a significant portion of variable costs incurred by companies in many industries. With an active approach to prediction, procurement and optimisation, companies may directly address these costs and reduce them.


In combining client historical data and the knowledge of external factors, such as weather conditions or exceptional occurrences, it is possible to make use of mathematical and statistical models and make a precise estimate of the future energy requirements. In implementing this solution, we use a data warehouse for storing information, analytical software for statistical analysis and an application with a user interface customised to reflect the client’s needs, thanks to which the client may model and visualise potential future results.

Thanks to the prediction of energy consumption, we assisted a major railway company in decreasing sanctions for a deviation by 99%.


Deloitte adapts the quantitative analytical consumption model to each client. The models may be implemented either in the client’s system or provided in the form of an automated message. Once the model is active, it may be easily adjusted to reflect the client’s or the business’s requirements as they develop.


Tervel Šopov

Tervel Šopov


Tervel is a consulting director responsible for AI&Data Strategy, Data Science and Machine learning market offerings in Deloitte Central Europe. Tervel has worked in the space of analytics, data and A... More