by David Groarke, PA Consulting
Utility analytics is all about unlocking the power of data by coordinating forms of information across organizational departments, applications and databases. Rather than deploying one-off solutions, however, utilities should take a holistic approach to managing, analyzing and visualizing data across the organization, creating the most value in the long term.
Across the industry, we are seeing utilities leverage analytical solutions that lower operations and maintenance costs, improve asset and load management, reduce outage management frequency and allow for a sophistication of customer products.
One of the most exciting prospects energy providers face is the collaboration between their concerted effort to gather data from multiple sources and the increasingly sophisticated analytical products and solutions that are emerging from within and outside the energy industry. Each utility will have its own requirements, and as such, we are seeing some power providers’ making targeted analytical investments with single-application solutions. Successful strategies are characterized by the adoption of enterprise solutions that incorporate data from their power infrastructure with other external data sources to create actionable intelligence and situational awareness.
Solutions’ gaining the most traction include:
- Outage management. To curtail the frequency and duration of outages, we are seeing analytical solutions’ being deployed that offer efficient detection and restoration of outages by remotely rerouting power flow to quickly restore customers. In addition, in preparation for weather-based outages, some utilities are using predictive analytics to understand how distribution lines respond to environmental factors and where best to stage crews.
- Revenue protection. In the U.S., nontechnical revenue losses are estimated to cost utilities 1 to 3 percent of revenue each year, according to Electric Light & Power magazine, with many of those losses’ stemming from theft or metering defects. Utilities are reacting to this by deploying analytical capabilities that identify and analyze energy diversion by comparing and correlating usage with other similar customer profiles.
- Load forecasting analytics. Increasingly sophisticated algorithms and software are being deployed across the utility landscape, enabling more accurate predictions of the volume, magnitude and location of energy demand and providing significant financial rewards as utilities begin to forecast errors no larger than 1 percent.
- Asset management. By deploying predictive maintenance analytics that increase the quantity and quality of maintenance schedules, utilities are improving total uptime and reducing maintenance costs.
- Voltage optimization. Analytical capabilities are being used that allow distribution operators to deploy solutions that dynamically lower voltage a few percentage points to end customers while meeting the mandatory service-level voltages.
- Vegetation management. Analytical solutions are allowing utilities to create optimal plans for vegetation management through the use of algorithms that predict vegetation growth that might lead to problems.
- Customer segmentation. Integration of customer consumption data with external data sources such as demographic data can provide utilities with valuable insights for the creation of new targeted products and services.
Although certain geography has its own data analytics business case drivers that result in some solutions’ being naturally prioritized over others, the combination of these solutions offer the largest benefits. For example, half of the recovery costs of BC Hydro’s smart meter program will be found in detecting and preventing energy theft; PPL Electric has reported a 38 percent improvement in service reliability enabled in part by the deployment of sophisticated analytical capabilities; and Oklahoma Gas & Electric in a bid to achieve a goal to shed load substantially by 2020 is using customer analytics to gain visibility into individual customers’ responses to price signals, enabling them to identify the best customers to target with specific marketing campaigns. In each case, clear, strategic goals or business problems have been addressed using a combination of analytical solutions.
As we are at the start of the analytics adoption journey for utilities, we are seeing that many of the challenges to roll out a holistic data analytics strategy revolve around organizational delivery capability and strategic questions:
- What are the best solutions to deploy in our organization given our current infrastructure?
- Do we have the right skill sets in our organization to unlock the potential of these solutions?
- Do we need a consistent model to integrate data?
- Should solutions be vendor-hosted, utility-hosted or cloud-based?
- Who should have access to this data and what are the privacy concerns?
- What analytical solutions will provide the highest return on investment?
- Should we create a centralized data team?
Creating a holistic data analytics strategy is essential if utilities are to realize the potential of these solutions. Combining data sources and effectively integrating these across new and existing systems will provide a powerful and intelligent resource for utilities to manage the grid, customers and operations. The first step to creating that holistic approach should include the development of a clear data strategy and road map that leverages customer and financial benefits associated with data analytics. By thoroughly addressing this first step, utilities will be on course to unlock the potential of utility data analytics.
David Groarke is an energy utilities expert at PA Consulting Group. He has worked with utilities and organizations across Europe, Australia and North America. His project experience spans the entire energy value chain, including transmission and distribution, customer service, meter-to-cash and enterprise services with a focus on smart grid, AMI initiatives and utility business transformation.More PowerGrid International Issue Articles
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