The transformation and modernization of the electric distribution network is happening at a rapid pace, enabled by sensors, communications, and applications. But understanding how to incorporate the new technology and data streams from multiple systems into current budgets and work processes remains a challenge.
In a nutshell, analytics takes data from disparate sources, compiles it, uses mathematical methods to find trends, then applies business-specific rules to interpret those trends. The results are sorted and visualized. Data sources used for analyzing electric distribution systems include advanced metering infrastructure, SCADA systems, outage management systems, customer information systems, geographical information systems and others.
Starting a project to integrate and derive value from these multiple systems doesn’t have to be daunting. It’s a matter how the project is approached. Many analytics projects run into issues when too much is attempted at one time. Conversely, successful analytics projects start with limited integrations to avoid swamping the limited resources involved. Data cleanup and management is simpler when fewer systems are installed. Success is achieved when the data that is available, perhaps from an AMI system, is balanced against utility business drivers. Not only is business value achieved, but workflow processes are examined. The utility gains experience with analysis and maintaining data beyond what is needed for billing. With success comes confidence and experience to build out the analytics platform one step at a time in a way that prioritizes potential financial value. With experience gained from initial projects, other data and communication sources can start to be leveraged to meet future objectives.
A successful analytics project is like a long journey, it all starts with the first step.