Energy & Utilities
Case StudyBaltimore Gas and Electric (BGE)

Baltimore Gas and Electric generated $2.8 million in economic benefit from identifying fraud and unbilled energy usage with machine learning

Baltimore Gas and Electric Company (BGE) is leveraging machine learning to identify and tackle unbilled energy usage. In doing so, the company has generated $2.8m in economic benefit and is expecting its annual economic benefit to reach $20 million. The company is using C3 IOT''s solutions, such as C3 Revenue Protection™ and C3 AMI Operations™ to improve the operation of its advanced metering infrastructure (AMI) network.

The Project

"Baltimore Gas and Electric installed three C3 IoT Smart Grid Applications: C3 AMI Operations™, C3 Revenue Protection™ and C3 Energy Intelligence™. Deployment involved developing 42 integrations to 12 source systems. C3 IoT loaded two years of historical BGE data in a 10 terabyte federated cloud image and configured more than 140 complex analytics and predictive algorithms to match BGE’s requirements and available data. In the first six months, C3 Revenue Protection identified non-technical loss cases generating $2.8 million in economic benefit from verified fraud cases. During the same timeframe, C3 AMI Operations identified sensor health issues with a 99% accuracy rate. BGE expects these applications to deliver an annual economic benefit of $20 million to BGE and its customers."

AI Usage

"C3 IoT loaded two years of historical BGE data in a 10 terabyte federated cloud image and configured more than 140 complex analytics and predictive algorithms to match BGE’s requirements and available data."

Data

"12 unique source systems provide data to the C3 IoT Platform, running on the AWS Cloud 42 distinct extracts, both as daily batch files and message integrations 10 TB federated cloud image of data 35 billion rows of data aggregated, federated, and analyzed 8 GB / 220 million rows of new data delivered each day to the C3 IoT Platform 140 complex analytics in use across applications 650 rules contribute to the complex analytics results reported to the end user"

Results

Baltimore Gas and Electric claims the following results: * 99% accuracy on investigated cases of sensor malfunction * 90% yield in the field confirming fraud using machine learning * 120% of BGE’s target value achieved as defined in its business case * Generated $2.8 million in economic benefit from verified fraud cases, in the first six months

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