Data has become the backbone of decision making, creating the need for utilities to not only harness and analyze data, but also draw actionable insights to meet challenges and capitalize on opportunities.
Bidgely’s Artificial Intelligence (AI)-Powered Insights Engine is a business intelligence solution that does just that. Using meter (AMI or Non-Smart Meter), weather, property, and additional third party data sources, Insights Engine applies the latest AI and machine learning techniques to produce simple, easy to digest, appliance-level insights to inform decisions that span across the entire utility value chain - from the grid down to the last mile inside customer’s homes.
Bidgely’s Insights Engine (IE) delivers an operational Business Intelligence layer for utilities to optimize disparate variables, data sources, and use cases around the one common variable in every utility equation: Customer Usage.
- Bidgely’s unique Artificial Intelligence (UtilityAI) capabilities allow us to analyze, disaggregate, and interpret meter data to understand each home’s unique energy consumption down to the appliance end-use level.
- This in turn provides utility business users each customer’s unique recipe to optimize for an infinite number of outcomes such as program enrollment, cost effectiveness, targeted marketing, reduction in calls, coordination of DERs, or even new revenue generation.
Demand Side Management (DSM)
- Determine appliance ownership across 8 appliance categories
- Determine appliance characteristics, such as size of AC unit, or gas vs electric home
- Analyze usage patterns, such as how much appliance consumption occurs during peak hour periods
- More cost effective DSM programs, by targeting highest savings potential homes
- Minimize wasted marketing spend by targeting only applicable customers
- Unlock program operational efficiencies, such as digital quality control
- Unlock future program enhancements, such as variable incentives based on geography and savings potential
Electric Vehicles (EV)
- Detect which customers are charging an EV at their home
- Determine the size of a customer’s EV Charger
- Understand charging patterns, such as peak time charging
- Targeted marketing and enrollment of customer’s into EV rates
- Scalable analytics to design EV rates and plan infrastructure upgrades
Rooftop Solar (PV)
- Detect rooftop solar production, if not known
- Determine solar production per home for every hour of the year
- Easier regulatory filings for PV Rates with a sounder fact base
- Avoid expensive capital investments in submetering
- More confidence in peak load calculations