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Green Mountain Power logo
150M meter readings daily

Key highlights

Category

Energy and Utility

Location

Headquarters: Colchester, Vermont, USA

Key Solution Components

  • Modern Data Platform: Cloudera Enterprise
  • Workloads: Data Warehouse, Data Science, Data Engineering
  • Key Components: Apache Hive, Apache Impala, Apache Kafka, Apache Kudu, Apache Spark Machine Learning
  • BI & Analytics Tool: Tableau
  • ETL Tool: Talend

Applications supported

  • Business Intelligence / Self-service analytics
  • Customer billing

Data sources

  • Master Data Management Systems

Impact

  • Gained new insights that enabled staff to disable underperforming gas turbines
  • Innovated billing processes, giving customers insightful aggregates that differentiate it in the market
  • Accelerated transformation and load processes by 10 times
  • Reduced reporting times from 30 minutes to 30 seconds

Big data scale

  • 150 million meter readings daily, captured in 15-minute intervals

Green Mountain Power can better understand power usage, price, generation, and distribution by providing staff with access to years of meter data in seconds and dramatically increasing the speed to insight.

Green Mountain Power is the largest utility in Vermont serving 80 percent of Vermonters. It was ranked number one by Fast Company in energy innovation and received one of the highest rankings in J.D. Power’s electric utility residential customer satisfaction study for mid-sized utilities in the East region.

Challenge

Following implementation of an advanced metering infrastructure (AMI), Green Mountain Power saw a fivefold increase in its meter data. The company found that its legacy data management platform couldn’t provide either the performance or scalability to meet the company’s analytics demands.

“We were going from one meter reading a day, to 96 reads for each customer, with readings captured every 15 minutes,” said Nara Neel, data and analytics lead at Green Mountain Power. “For each reading, we also capture data across five different meter channels such as kilowatt (kWh) consumed, kWh generated, and average voltages. That's 480 reads in all for each customer daily. It's a lot of data and we cannot crunch all these 15-minute intervals using our Exadata infrastructure. We tried it. It's not doable in a timely manner.”

Solution  

Green Mountain Power deployed a modern data warehouse on Cloudera that provides the scalability, performance, and real-time capabilities to store, process, and analyze IoT data, and  power both self-service and operational analytics. The platform supports a variety of user needs:

  • Executives can view daily financial performance reports via Tableau dashboards instead of waiting for books to close at the end of the month.
  • Power generation staff can view fluctuating power demands in real time so they can bring alternative energy sources, such as solar or battery power, online to fulfill surges in demand before outages occur.
  • Energy management and operational specialists can obtain comprehensive customer insights to advise businesses of specific steps they can take to reduce their energy consumption and costs.
  • Customers now receive personalized insights, delivered through innovative billing processes and online, that help them actively understand their power usage and reduce their electric bill. These insights include weekly predictions on their spending based on the prior week’s usage and monthly snapshots displaying their peak usage times.

“With Cloudera in place, we can deliver analytics and reports that we couldn’t before,” said Neel.

The platform processes more than 150 million transactions daily and previously cumbersome ETL (extract, transform, and load) jobs run faster, with transformation and load processes occurring 10 times faster than before. Additionally, correlation of data and reporting can be completed significantly faster. “Reports that before took 30 minutes to run now take only 30 seconds,” said Neel.

Implementation

Currently, Green Mountain Power runs the Cloudera platform on-prem. But in the future, the company plans to move some processes to the cloud, using Cloudera Altus on Amazon Web Services. “With cloud we can tackle different analytics needs faster,” said Neel. “Cloudera provides us with the tools to not only make our transition to the cloud easy, but also will simplify management, security, and governance across our hybrid environment.”

Results

With comprehensive customer insights, Green Mountain Power can better understand power usage, design rates based on each customer’s usage, and advise customers on how to reduce their electric bills. For example, one water district rescheduled several processes that weren’t time sensitive when Green Mountain Power energy specialists shared that its peak usage also coincided with peak demand, thus raising their utility costs.

Additionally, greater operational visibility has enabled the company to improve operating efficiency. For example, new dashboards that tell the “story” of each generation plant—from power generated to revenue produced to costs—enabled executives to dig deep into the costs associated with each turbine. They were able to spot and, ultimately, disable underperforming turbines with this new insight.

“Green Mountain Power is customer obsessed and we produce some of the highest levels of customer satisfaction and trust in the utility industry today,” said Neel.

Our work is helping us innovate in customer care and operational reporting so we can more effectively manage demand and keep customer satisfaction high.

-Nara Neel, Data and Analytics Lead, Green Mountain Power