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Case Study: Jersey Electricity

Jersey Electricity (JE) is a utility company dealing in importation, generation, transmission and distribution of electricity. They are the sole supplier to over 48,000 domestic and commercial customers in the Island of Jersey.

Smart Meter Automation: Improving Customer Engagement

jerseyelectricity

Case Study: Jersey Electricity

Forward Thinking

Whilst legislation was introduced in the UK and most of Europe to force the introduction of Smart Meters into all properties by 2020; no such legislation was introduced to Jersey. However, JE made the
decision to be ahead of the game and install Smart Meters in all properties by 2017. Traditional meters were to be replaced by Smart Meters that automatically transmit readings and interval data to 650
local data concentrators situated around the Island, every 3 hours or on demand.

Smart Metering is seen by JE as a way of improving customer engagement by providing accurate reports that outline energy consumption and usage analytics to its customers.

The Solution: WhereScape Red

WhereScape were evaluated, and subsequently chosen, having proven their ability to build powerful data warehouses, rapidly and cost effectively. By automating the entire data warehouse lifecycle
from design and planning through to implementation and operation,

We have found that RED is as flexible as we had hoped it would be and that WhereScape have been an excellent partner in the project to date.

Gary Parsons Manager, Jendev

WhereScape gave JE the ability to:

  • Utilise data from a variety of source types
  • Store almost 1 billion half hour readings annually
  • Refresh on a daily basis, publish data to a customer portal and JE departments
  • Provide adhoc analysis
  • Scale as data volumes increased
  • Respond rapidly to any changes in requirements
  • Leverage existing internal skills and fully document the process (so it was always up to date).

At a time when some global energy suppliers are perceived to be making large profits at the expense of their customers, JE have a true competitive advantage.

In just 22 development days the data warehouse was built, documented and released into production. It included:

  • 68 load/stage tables and views
  • 17 ODS tables – recording history
  • 4 facts with 15 dimensions and 4 role play dimension views
  • 3 OLAP cubes with 14 OLAP dimensions
  • 106 procedures containing 30,000 lines of code
  • 3 parallel scheduled workflows
  • User and Technical Documentation including full Data Lineage and Data Dictionary

The Benefits

By automating Smart Metering, from data collection through to information publishing, JE can now:

  • Access a Single Version of the Truth: JE have the ability to bring together data from different sources, store and present data within a data warehouse and OLAP database and provide self-service reports through Excel and SSRS.
  • Validate Data: Validate data on a daily basis, identifying meter reading errors as early as possible rather than as part of the quarterly billing process.
  • Provide Customers with Accurate & Accessible Consumption patterns: Automatically load validated meter readings and interval data into the customer portal.
  • Understand and Utilise Data: JE now have the ability to apply an array of business rules to their data enabling them to improve engagement with their customers.
  • Set up a Cross Functional Team: JE knowledge share and learn technical capabilities for future development.

Smart Metering Automation: The Results

Smart Metering has enabled JE to improve their engagement with customers. Accurate time of day usage information enables customers to adapt their energy usage, taking advantage of off-peak tariffs offered by JE in order to reduce their electricity bills. At a time when some global energy suppliers are perceived to be making large profits at the expense of their customers, JE have a true competitive advantage.

Additionally Smart Metering Automation enables JE to identify network performance issues more readily. Use of meteorological data with accurate time of day usage statistics also enables better forecasting of customer demand, thus enabling plant and equipment to be better utilised.