Bidgely has introduced Insights Engine, an artificial intelligence (AI) and machine learning-based software to transform how utilities and energy retailers generate analytics insights.
Identified as a 2019 top technology trend with disruptive potential by Gartner, Inc., augmented business intelligence makes data insights more broadly available across organizations, including decision makers and operational workers. With the Insights Engine leveraged across a utility, the combined insights derived from applying AI to customer data enables multiple stakeholders to directly address challenges around four key areas: demand-side management (DSM), electric vehicles (EVs), solar PV and load research.
“The artificial intelligence fabric woven through all of our solutions understands what is plugged into the grid at home and how it operates, be it an EV, a solar plus energy storage system or a washing machine. These insights create an elevated level of business intelligence that permeates throughout the utility. It enables customer segmentation techniques that tech giants like Netflix implement to tailor the right personalized message to the right customer; it creates new opportunities for program cost reduction; and it introduces truly intelligent grid management,” said Bidgely Head of Global Sales Prateek Chakravarty.
According to a Wood Mackenzie report, there are nearly 30 million distributed generation and grid-connected devices installed in homes across the United States alone, with millions more globally anticipated by 2023. As utilities begin to take a more integrated approach to DSM, the Insights Engine patented disaggregation technology eases the ability to flexibly manage these new resources. Four new Insights Engine modules were created to directly address utility pain points in the following areas:
EV Module: for detection and analysis of EV charging in the home, utilities can use the information to design rate plans that encourage off peak charging and proactively offer EV Time of Use (TOU) rates to customers with EVs.
DSM Module: for understanding the efficiency of appliances in the home, utilities can pinpoint homes with the highest potential savings and target DSM campaigns to those specific customers, generating savings of 25 percent in program budget spend.
PV Module: for detection of solar PV plus consumption monitoring in the home, utilities can analyze residential solar customers in their territory to understand the effects of distributed generation for improved distribution planning.
Load Research Module: for identifying trends, outliers and constraints that may affect short and long term planning, utilities can analyze the individual home energy profiles for all customers across all contributing appliance categories.
Source: Company Press Release