ENERGY & UTILITIES

Predictive Analytics Use Cases

Predictive Analytics in the Energy & Utilities sector

Energy Transition is bringing massive disruption into Energy & Utility sectors. Predictive Analytics has become a unique competitive differentiator to improve operation performance, Energy trading & purchase and Customer engagement.

Energy transition, deregulation and technologies

Energy transition, deregulation and technologies are massively disrupting energy and utility sectors:

• Energy transition brings new volatile and versatile renewable sources of energy, and also new mobile and versatile sources of consumption.
• Open markets and regulations have multiplied and segmented the value chain in multiple players.
• Industries, smart cities or residential consumers of enegy develops more and more control and efficiency in their usage of energy.

All these elements require the grid to become much smarter and more flexible to be able to cope with versatile demand, at the most affordable price.

To optimize this flexibility and to take the benefits of the data collected by the Internet of things, Smartgrids have to enable automated predictive analytics.

Automated Forecasts allow to anticipate and pilot in real-time the energy network with best efficiency.

They also enable preventive maintenance for an even more reliable utility service delivery.

Increasing customer satisfaction and loyalty

In addition, added value services need to be deployed to allow customers to monitor, control, adjust and optimize their own consumption (eg. demand/response and load shifting).

Each customer profile has also its own needs and specificities. Energy companies shall understand these customer specificities to profile them and target specific new service offering to each of them. This is allowing to increase customer satisfaction & loyalty while limiting the churn of customers to competition.

Convalis Prediction platforms has automated predictive analytics. It generates automatically and daily, these forecasts, predictions and profiling services.

Smart Grid example

Source: The Economist 2010

Forecasting fluctuations in consumption and production

Energy Infrastructure include fast growing renewable energies productions which are highly volatile resources (solar, wind).

Producers can plan production and storage of energies with hydroelectricity, or batteries). Predictive analytics is key to optimize the value that they can extract for such energy pools on the markets.

Energy transport and distribution networks are huge investment, with a long life time. The new volatility of consumption and production is impacting the balance and the aging of these infrastructure. Furthermore, special environment and external conditions (weather) are impacting even further these systems.

Convalis Prediction automated consumption and production forecasts and its machine learning tool enable our customers to:

• Guarantee the technical balance of infrastructure (and reduce Imbalance adjustment costs)
• Enable selective predictive maintenance
• Build reliable service level agreements with customers & suppliers

Example: Convalis Prediction accurate forecast of next day consumption can save 40+M€ of purchase of electricity annually on EU national electricity markets.