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In Texas, Octopus Energy Launches Smart Home Product Said To Integrate Demand Response, Lower Fixed-Rate

March 23, 2022

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Copyright 2010-21 EnergyChoiceMatters.com
Reporting by Paul Ring • ring@energychoicematters.com

The following story is brought free of charge to readers by EC Infosystems, the exclusive EDI provider of EnergyChoiceMatters.com

For Texas customers, Octopus Energy today announced the launch of Intelligent Octopus, described as, "its first-ever integrated demand response, fixed-rate plan that rewards customers with a specialized rate for helping to balance the grid when demand for energy is high."

Intelligent Octopus will pair directly with smart home devices. With today’s beta launch, Intelligent Octopus customers can connect their smart thermostats to Octopus Energy’s system that monitors grid activity. When demand on the grid increases, Octopus Energy adjusts enrolled customers’ thermostats for 5- to 15-minute increments to decrease energy usage, afterwhich customers’ smart home products are adjusted back to their original settings.

In exchange for such control, Octopus provides a lower fixed rate, applicable to all hours, compared to its other comparable plans.

In the Oncor service area, Octopus's Intelligent Octopus 12 plan is a 100% renewable, 12-month fixed rate with an average all-in rate, at 1,000 kWh, of 10.3 cents per kWh, reflecting an all-hours energy charge of 5.0673¢ per kWh, a $10 monthly fee, plus Oncor delivery charges of 3.8907¢ per KWh and $3.42 per month. There is no early termination fee

To the extent the customer does not pair their smart thermostat to Octopus, the customer is not eligible for the lower rate, and the plan has an average all in rate of 11.3 cents per kWh (reflecting an energy charge of 6.0673¢ per kWh, which reflects rates under a standard Octopus plan)

Intelligent Octopus will also expand to additional smart home devices and providers in the months to come.

Intelligent Octopus is powered by Octopus Energy’s proprietary Kraken technology that uses advanced data and machine learning to automate a majority of the energy supply chain.

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