Collaborative data validation techniques are the key to taming the enormous volumes of data required for increasingly granular energy market requirements and initiatives.
Meter data impacts many areas of an organization, resulting in a common goal of achieving a high level of meter data accuracy. One of the biggest challenges to obtaining this goal is the large amount of meter data that must be timely validated every day.
In this blog post, we’ll illustrate how collaborative data validation techniques are the key to taming the enormous volumes of data required for increasingly granular energy market requirements and initiatives.
Business analysts' battle with meter data
As more organizations enter the world of five-minute data, the amount of collected meter data is growing exponentially. Comparing multiple data sources for the same resource or tie line (a standard best practice) also significantly increases the amount of meter data. For example, if you have 100 meters capable of receiving five-minute data, this creates 28,800 data intervals to validate. Suppose you add a second data source, and the number doubles. With a third data source, the number triples to 86,400! The growth of behind-the-meter generation and aggregated resources for demand response produces an upsurge in the number of meters to collect data. The business analyst responsible for authenticating ever-increasing amounts of data faces a daunting task.
The vast amounts of meter data collected force organizations to allocate precious analyst time and resources to review meter data. Analysts have the competing objectives of combing through volumes of data with precision and speed. Numerous areas of organizations rely on accurate meter data to make decisions, making requirements for accurate data a key performance metric. Compounding these challenges are market- and reliability-driven data submission deadlines that repeat at ever-shortening intervals. Successful organizations address this by equipping analysts with tools and strategies to quickly identify and correct data discrepancies.
Analysts can spend as much as half their working hours manually correcting meter data. This work’s routine and repetitive nature cry out for meter data validation automation.
PCI Energy Accounting automates data validation
PCI Energy Accounting has automated the identification of potential meter data issues, allowing analysts to spot and correct them quickly.
Gone are the days of eyeballing pages and pages of meter data to locate outliers or missing intervals. Simple checks such as missing data, values outside a range, stuck values, and values that spike interval to interval have been automated as well as more advanced checks such as solar production during night hours and data source comparisons.
Failures and exceptions are easily presented in summary and detail views so analysts can go directly to the issues. Automatically identifying meter data issues saves analysts lots of time, so they can focus on correcting the data, identifying trends, and working with meter shops to fix root causes. The key to automated data validation is viewing the rules and checks through a wide lens to prevent missed opportunities.
PCI Energy Accounting roundtables
Our Energy Accounting analysts believe peer-to-peer engagement ensures that any strategy for data validation automation is robust, successful, and iterative to the benefit of the data end user. Our customers continue to share strategies and specific scenarios of meter data issues during PCI’s monthly customer roundtables. We work collaboratively with customers to understand each scenario and develop automated processes to capture these exceptions. The result for clients who participate is a deeper understanding of the challenges faced by their colleagues and potential solutions that can be applied to similar situations using PCI’s Energy Accounting solution.
Visit our Energy Accounting page to learn more about how your organization can improve its meter data quality and audit with confidence.
