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Bidgely Partners with New Hampshire Electric Cooperative to Enhance Rate Design Strategies for Utility Customers

NHEC leveraged Bidgely’s UtilityAI™ platform to restructure rate plans that reward the co-op’s members for positive energy use

MOUNTAIN VIEW, Calif.--(BUSINESS WIRE)--Bidgely’s UtilityAI platform has been deployed by New Hampshire Electric Cooperative (NHEC) to analyze residential members’ consumption patterns to identify “low-cost-to-serve” behaviors and examine the potential effect on rates. Bidgely’s Analytics Workbench (AWB) business intelligence and data analytics tool dramatically reduced the resources and time required by NHEC to conduct load analyses and provided greater visibility into whole-home and appliance-level usage. Results identified three member segment types – night load, all-year base load and heavy winter peak – that can potentially save 3 to 4 percent per year, based on their actual cost to serve, with minimal impact to NHEC’s other members.

“Customer satisfaction and rate structures are highly intertwined, and NHEC recognized the opportunity to proactively reward identified customers for positive power use behaviors,” said Abhay Gupta, CEO of Bidgely. “Designing customer-centric rates based on AMI data is the future of rate design innovation. Through our advanced load disaggregation, NHEC could design rates that better aligned with customer usage patterns.”

Eliminating the need for member surveys or additional metering hardware, Bidgely uses existing advanced metering infrastructure (AMI) data as well as supplemental customer data from utilities. In this case, NHEC provided hourly meter data spanning a two-year period, which Bidgely used to disaggregate appliance-level consumption data for approximately 60,000 NHEC residential members based on a multitude of categories, including heating, cooling, pool pumps, lighting, refrigeration, laundry, cooking, entertainment and more.

Bidgely’s advanced analytics then allowed the identification of member “clusters” based on energy patterns, appliance ownership, geographic location as well as time of use. Leveraging Bidgely’s AWB to analyze the cost to serve each segment, NHEC was able to determine that multiple segments used energy in a way that was less expensive to serve than current charge rates. Additionally, NHEC discovered the rate being charged to these members could be lowered without a significant impact on other member groups paying the normal rate.

For a deeper dive into how Bidgely’s Analytics Workbench tool helped enhance rate design, download Advanced Rate Design with Analytics: A New Hampshire Electric COOP Case Study.

About Bidgely

Bidgely is an AI-powered SaaS Company accelerating a clean energy future by enabling energy companies and consumers to make data-driven energy-related decisions. Powered by our unique patented technology, Bidgely’s UtilityAI™ Platform transforms multiple dimensions of customer data – such as energy consumption, demographic, and interactions – into deeply accurate and actionable consumer energy insights. We leverage these insights to empower each customer with personalized recommendations, tailored to their individual personality and lifestyle, usage attributes, behavioral patterns, purchase propensity, and beyond. From a Distributed Energy Resources (DER) and Grid Edge perspective, whether it is smart thermostats to EV chargers, solar PVs to TOU rate designs and tariffs; UtilityAI™ energy analytics provides deep visibility into generation, consumption for better peak load shaping and grid planning, and delivers targeted recommendations for new value-added products and services. With roots in Silicon Valley, Bidgely has over 17 energy patents, $75M+ in funding, retains 30+ data scientists, and brings a passion for AI to utilities serving residential and commercial customers around the world. For more information, please visit www.bidgely.com or the Bidgely blog at bidgely.com/blog.

Contacts

Christine Bennett
Bidgely
press@bidgely.com

Bidgely


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Contacts

Christine Bennett
Bidgely
press@bidgely.com

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