Sunverge Energy, a leading provider of intelligent energy storage systems for residences and small businesses, today announced the addition of money-saving demand charge management features to its energy management platform. Using sophisticated predictive analytics, the new algorithm determines the ideal mix of PV, storage and grid power to keep a customer from incurring demand charges – saving customers money while reducing peak load on the grid.
Proposals for residential demand charges are on the rise in the U.S., as utilities and regulators consider alternative mechanisms to allocate grid costs to residential Distributed Energy Resource (DER) customers. While most such proposals are still under consideration, demand charges are becoming more prevalent in some of the world’s fastest-growing energy storage markets such as Australia and Japan.
As these charges proliferate, consumers face the complex problem of managing their power resources to minimize the impact of those charges. At the same time, utilities are increasingly concerned with managing the grid as more DERs create dynamic load shifts, especially at peak times when the grid is most challenged. Sunverge designed its algorithm to address these problems simultaneously.
“Our demand charge reduction algorithm provides both consumer and grid benefits,” said Ken Munson, co-founder and CEO of Sunverge Energy. “Consumers can cut their power bill in half in Australia and by one-third in the U.S.1., and utilities can more effectively manage voltage and reduce high energy peaks that strain and damage distribution infrastructure.”
Sunverge’s systems capture and store excess power generated by the rooftop solar panels installed by homeowners and small businesses for their later use. In cases where electric rates are based on time of use, the system uses its integral intelligence to automatically switch from grid power to stored renewable power when energy prices are at their highest. This reduces both the monthly bill for owners and the emissions from traditional power plants that would otherwise provide peak power to the customer.
Demand charges add another variable to this energy arbitrage equation by creating a “set point” for the use of the grid, beyond which consumers are subject to the charge. The demand charge reduction algorithm determines, at billing rate intervals, the appropriate amount of power to use from PV, to store into or discharge from the battery, and to feed into or pull from the grid, optimizing the balance of power resources such that the customer does not reach the grid’s set point.
The goal is to maintain a reserve of stored power that will provide the predicted energy needs for the home based on usage patterns, while avoiding exceeding the set point.
“This is a complex task, but thanks to predictive analytics and built-in intelligence, the Sunverge system is capable of managing all the variables for the best outcome,” Munson said. “As we continue to see changes that affect both the management of home energy use and the grid itself, we’ll continue to make our systems even smarter.”
