Breaking down energy consumption with data analytics

The United States has an energy consumption rate that outpaces the rest of the world. According to the World Watch Institute, the average American consumes five times more energy than the average global citizen. Even more troubling is that developing nations are quickly making up ground, with China becoming the No. 1 consumer of coal in the world.

With the world facing down a potential energy crisis, many organizations have pursued virtually every avenue for methods to reduce consumption. Some studies have found that big data tools can provide invaluable insight into understanding how people use energy and what can be done to make processes more efficient.

According to GigaOM, one energy analyst startup has been using big data tools built upon a Hadoop architecture to process data gathered from more than 50 million homes. Officials from the company said it can save as much as 2 terawatt hours of energy with the information it has gleaned, saving the United States $200 million in energy costs. Their software collects data from 96 billion meter reads, processing the information and producing recommendations for reducing customer electricity use.

In Austin, Texas, energy research firm Pecan Street recently released the results of its extensive study on energy consumption within the state, according to Time magazine. The firm used data analytics tools to gather information from nearly 90 million electricity use and voltage reads per day. Researchers identified several wasteful practices contributing to the state's high energy consumption rates. Air conditioning units, for instance, accounted for 50 percent of the energy used during the state's notoriously humid summer months. Big data software found that electric heaters, however, were the most inefficient machines at consuming energy, using up more electricity than air conditioners in a given year. By scaling back on these devices, consumers can greatly reduce their wasteful energy practices.

Using big data analytics, researchers can identify the trends sending energy consumption rates soaring and provide viable solutions to the worldwide problem.

Categorized by :

Leave a Reply

Your email address will not be published. Required fields are marked *

Hortonworks Data Platform
The Hortonworks Data Platform is a 100% open source distribution of Apache Hadoop that is truly enterprise grade having been built, tested and hardened with enterprise rigor.
Get started with Sandbox
Hortonworks Sandbox is a self-contained virtual machine with Apache Hadoop pre-configured alongside a set of hands-on, step-by-step Hadoop tutorials.
Modern Data Architecture
Tackle the challenges of big data. Hadoop integrates with existing EDW, RDBMS and MPP systems to deliver lower cost, higher capacity infrastructure.