Visit kWantera at Booth 413 during the
35th WORLD ENERGY ENGINEERING CONGRESS
October 31 - November 2, 2012
Office: 2740 Smallman St. Suite 401 Pittsburgh, PA 15222 • Phone: 412-481-1111 • • © 2012 kWanteraTM All rights reserved.
A surprising number of large energy buyers like manu-facturers, hospitals, universities and building managers are often not aware that they have the opportunity to reduce their energy costs without a single operational change or new investment—simply by paying less for energy. Though this seems obvious, it is much, much harder to do in practice.
In deregulated markets, energy prices fluctuate and, as a result, a ‘fixed-price’ energy contract comes at the expense of a premium from the energy retailer to lock in that price. For financial management reasons, and with no knowledge of the direction of future energy prices, most energy buyers want price certainty over lower cost. However that ‘price assurance premium’ is expensive and can sometimes be as much as 25 percent of the final contract price.
That is why energy buyers are missing a tremendous opportunity to reduce their energy purchase price by as much as ten percent, without increasing their exposure to risk. kWA Pricing changes the equation in your favor by giving you price predictions for electricity and natural gas. It enables you to buy at a lower price, while reducing your risk at the same time.
How It Works
kWA Pricing uses historical and real-time grid, market pricing and weather data to predict energy prices. Our AI-based, machine-learning technology is particularly designed to uncover patterns of behavior in vast quantities of data in order to make predictions about future values.
kWA Pricing forecasts drive short-term, day-ahead and spot purchase decisions along with long-term contract decisions. For example, kWA Pricing can make daily buying recommendations for the day-ahead electrical power markets as well as find and maintain the optimum ratio of fixed versus index priced purchasing for your energy needs, or both. kWA Pricing has been adapted to the PJM, MISO, ERCOT NEISO, NYISO and CAISO in North America and the Nord Pool in the EU energy markets.
If you are interested in learning more, please send an email to and we will contact you.
The kWantera Analytics (kWA) platform relies on the latest advances in AI for our cost-saving applications. It automatically analyzes and cross-correlates vast streams of real-time data from an ever-growing variety of disparate sources in order to generate actionable recommendations for energy managers and buyers.
Contact Us to learn more about kWantera Analytics.
Plane Ticket Analogy
Business travelers face a similar price/risk analysis challenge as energy buyers. For a flight purchase, most travelers consider such factors as the risk of a cancelled flight and/or trip, the best flight schedule, and the price now versus later. Yet most people will buy a non-refundable ticket earlier than is often necessary (or financially prudent) to lock-in a known price and schedule while the risk from that the trip will not change.
But what if your travel website could give you reliable price predictions every day between now and the travel date from each and every airline? You could simultaneously get the best combination of price and risk. Furthermore, what if your travel website sent you real-time emails and texts with future price changes or seat availability and allowed you to lock in that price the moment it was most advantageous to you? This is what kWA Pricing does for energy buyers, giving you the means to optimize your energy purchasing.