How to create a data pipeline worthy of your program
As load management becomes more critical for the grid, utilities and system operators are looking to incentivize solutions that flatten demand and ultimately match it to renewable generation. There is a growing recognition that distributed energy resources (DERs) are part of the solution, as they provide both facility-level and grid-level benefits.
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To better understand DERs, utilities around the country are piloting programs to incentivize their adoption. A typical component of such programs is the collection of operational data from DER systems as they come online. Using illustrative examples, the authors will discuss why developing robust data standards as part of program design for the DER operational data is critical in driving the program’s success. Through evaluating DERs such as energy storage systems, electric vehicles (EVs), and combined heat and power (CHP) across numerous utilities, the authors will detail best practices and considerations that factor into developing these data standards. The authors will present their work in developing and deploying a novel data-driven M&V approach focused on evaluating the monetizable and non-monetizable benefits of a variety of storage projects. The framework involves the validation of operational data from a multi-party data pipeline. Drawing upon this framework, the authors will share key findings on data best practices for utilities as they expand their DER offerings.
