Originally published in KDNuggets, September, 2019.
The energy sector is under constant development, and more of significant inventions and innovations are yet to come. The energy use has always been involved in other industries like agriculture, manufacturing, transportation, and many others. Thus these industries tend to enlarge the amount of energy they consume every day. Energy seems to be very demanding in terms of new technologies application and development of new energy sources.
The rapid development of the energy sector and utilities directly influences social development. People are now facing challenges of smart energy management and consuming, application of renewable energy sources and environmental protection. Smart technologies play a crucial role in the resolution on these matters. In this article, we will consider the most vivid data science use cases in the industry of energy and utilities.
Failure probability modeling
Failure probability modeling has won its place in the energy industry. The efficiency of the machine learning algorithms in the failure prediction is without a doubt.
Active application of probability modeling helps to increase performance, predict occasional failures in the functioning and as a result to reduce maintenance costs. The energy companies invest vast amounts of money into maintenance and proper functioning of their machines and devices. Unexpected failures in their operations result in considerable financial losses. Moreover, for people who rely on these companies as their energy source the situation gets critical. As a result, general reliability and image of the energy provider may suffer.
The output of the failure probability model application is an essential part of the decision making process for the companies. It gives a marvelous opportunity to be one step ahead for the company management.
Outage detection and prediction
Despite the efforts made by the companies belonging to the energy industry, the power outage still takes place, leaving a considerable number of people without power. In this respect, people tend to regard the blackouts as a failure of the electric grids. However, the blackout is a preventive measure, a result of the automatic protection system operation.
To continue reading this article click here.
You must be logged in to post a comment.
 |
 |
 |
These are some interesting machine learning use cases (link here with https://www.explorium.ai/usecases/). It is refreshing and interesting to see use cases focused on alternative industries.