MOUNTAIN VIEW, Calif.–(BUSINESS WIRE)–Bidgely continues to expand its intellectual property portfolio with a new patent grant protecting its lucrative electric vehicle (EV) disaggregation technology, which has been successfully detecting EVs and charger type in the home for utilities since 2018. This grant adds to the robust set of 14 patents protecting unique technology developments like load disaggregation from smart and non-smart meters, as well as solar PV disaggregation and appliance-level similar home comparisons. Bidgelyâ€™s core disaggregation technology powers its industry-first UtilityAI solutions, which extend from customer-facing to internal utility business functions and tackle use cases like distributed energy resource orchestration; electrification; customer engagement; and demand side and peak load management.
â€śWe see 2019 as a breakout year for utility artificial intelligence, and we are leading the drive with the most comprehensive patent portfolio in the industry – serving as the foundation to applying AI and machine learning to energy data,â€ť said Bidgely CEO Abhay Gupta. â€śOur deepening IP, expanding set of UtilityAI solutions and broadening executive bench strength from the tech enterprise space creates a groundswell of momentum for solving utility challenges, such as optimizing shareholder value, personalizing engagement and modernizing the grid.â€ť
In a recent blog post, EY asserts that AI can help power and utility companies access new business models and revenue streams via deep data-driven insights, which enable, in turn, an intelligent, stable and autonomous grid. For example, electrification and EVs are creating significant monetization opportunities as well as solutions to load swings on the grid. With an estimated 2.9 million EVs expected to hit the streets within five years, CAISO estimates this will bring over 11,000 GWh of load to the U.S. power grid (or about $1.5 billion in annual electricity sales). Using artificial intelligence to automatically identify homes with EVs without customer input will be critical to capitalize on this new revenue stream.
Building on its expanded patent portfolio, Bidgely enters 2019 with momentum on both customer and artificial intelligence leadership fronts, recently capturing recognition on the 2019 Cleantech 100 list that showcases companies most likely to make big commercial impacts in the coming 5-10 years. Now serving more than 15 million homes with disaggregation technology for both smart and analog meters without requiring additional hardware, the company continues to delight consumers with 90 percent â€śLikesâ€ť for its digital communications and over 45 percent repeat email open rates.
Through artificial intelligence advancements and strategic partnerships, Bidgely is rapidly scaling its solutions that serve multiple utility functions, ranging from energy efficiency and demand side management; customer engagement, customer satisfaction and call centers; and grid edge, smart home and distributed energy resources planning and controls. For example, through a new partnership with EnergyHub, Bidgely has entered the smart home controls market to balance grid loads at massive scale.
Meet with Bidgely at Upcoming Conferences
Attendees to the upcoming 10th annual Smart Energy Summit and JD Power Utility Client Conference this month can hear Gupta speak about UtilityAI and how utilities can mine untapped customer data to apply the same data-driven approaches consumer tech giants use to capture customer mindshare. To schedule a meeting, please contact: email@example.com.
Bidgely is transforming the way customers interact with their energy use. By combining the power of SaaS-based analytics with consumer-friendly web and mobile applications, Bidgely provides personalized and actionable insights that help customers save energy and enable utilities to build enduring customer relationships. The company works with utilities serving residential customers around the world. For more information, please visit www.bidgely.com or the Bidgely blog at bidgely.com/blog.