Thanks to electronic counters, a huge amount of energy consumption data (load curves) is now available and mostly unexplored. Hence, the key challenge of many energy companies is nowadays that of extracting from such data previously unknown and useful knowledge in order to gain insigths into their business, get a deeper understanding of how their customers use energy and, thus, to improve both the quality and the efficiency of their services – e.g., through customer tailored contract offers, or energy comsumption prediction aimed at shielding energy companies from power shortage/surplus.
From the collaboration among Enel, Exeura and Politecnico di Torino originates SHAPE, a business analytics platform for customer profiling and fraud detection.
Customer Analytics e Fraud Detection
The transition from supplier-centric to customer-centric framework carried out by Enel after the liberalization of the electricity market needs not only an efficient and effective metering system, but also new business strategies and innovative services for the customer, retailer and distribution network.
For this purpose, Enel recently started the Research and Development project “SHAPE” in collaboration with Politecnico di Torino (scientific partner) and Exeura (industrial partner). The aim of the project is the development of a web-based enterprise platform for Business Analytics focused on the daily load curves sourced from the Enel electronic meters. Using ad hoc developed advanced time series analysis techniques, the SHAPE platform enables:
The knowledge of the typical patterns of the aggregated energy consumption/production brings benefits like identification of new business opportunities and improvement of pricing schemes. The economic benefit of understanding customer loads decreases investment costs by reducing the planning margin. Moreover, the acquired knowledge enables energy fraud detection along with a better estimation of economic losses resulting from interruptions of service. The summary information on the consumptions is useful for more effective management of the electricity distribution network in synergy with existing initiatives in the field of smart grids.
Task: Customer profiling and fraud detection