Analytics Make Smart Grids Smarter
The advent of smart grid and smart meter technology is changing the utility industry’s business model. As a result, utility companies face new requirements to provide advanced analytical and decision-making capabilities. The need to integrate data from many systems such as the Meter Data Management System, the Customer Information System (CIS), the Outage Management System and others, increases the value of the grid while supporting data delivery to a wider range of applications and data consumers.
The advent of smart grid and smart meter technology is changing the utility industry’s business model. As a result, utility companies face new requirements to provide advanced analytical and decision-making capabilities. The need to integrate data from many systems such as the Meter Data Management System, the Customer Information System (CIS), the Outage Management System and others, increases the value of the grid while supporting data delivery to a wider range of applications and data consumers. Utility companies will need to provide this information for many business needs such as the corporate portal, outage management, dynamic pricing, and meter-to-cash analysis. Utility companies need to develop the infrastructure to support the requirements demanded by growing data volumes, new business users, and new data subject areas. There is also an ‘active’ aspect to the requirements as the infrastructure must support the ability to quickly move data into the analytical environment to perform operational analytics and drive real-time decision making based on detailed granular data throughout the utility.
Drivers of an active Smart Grid analytics platform.
Like the telecommunications, retail, and airline industries, the utilities industry has the ability to drive business processes based on detailed customer behavior. These drivers include being able to:
- Determine the true effectiveness of energy efficiency programs through the analysis of AMI data and provide more accurate credits.
- Identify financial issues in the meter-to-cash process, such as incorrect re-bill processing or improper reading adjustments.
- More accurately identify transformer issues and load increases based on individual customer usage patterns, rather than simply on peak day estimates.
- Improve customer communications and program enrollment by targeting customers across multiple dynamic segments, rather than a fixed set of predetermined segments.
- Use Geospatial capabilities to visualize customer usage and event trends.
Many other examples of using detailed meter data exist. The critical aspect is providing the utility company with the ability to support these many applications of the data without creating an unmanageable clutter of data repositories.
A second set of drivers focuses on architectural necessities to support the many data consumers who need access to the valuable information.
Four necessary drivers must be considered:
- Provide the performance and scalability to support:
o Large data volumes of interval and event data from smart sensors and smart meters.
o An increasing number of users accessing the data in different ways, such as very tactical Web services and deep historic trend analysis running at the same time.
o Reduced data latency from the time events have occurred to the time decisions are driven by the data.
- Manage costs by simplifying the development and administration of the integration of differing data sources into a common platform, while maintaining data granularity and consistency.
- Ensure data security through the proper control and auditing of data across the environment to support the different user requirements, from the external customer to the financial analyst.
- Ensure data accuracy through the use of standardized and agreed upon business rules applied to the data.
By taking a holistic approach to data integration, an active Smart Grid analytics platform becomes highly effective when used throughout the utility to improve performance, efficiency and customer service. Making the best decisions possible is dependent upon gaining the richest insights from all available data in as close to real-time as possible.
Learn more by downloading the white paper, How Teradata Makes the Smart Grid Smarter.
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