Unlocking Grid Orchestration with GridOS Data Fabric

Grid orchestration. It’s a subject we’ve covered extensively, from what Grid OS is, to why Grid orchestration is necessary, to Grid Orchestration software uses. It’s one of the best ways to accelerate your energy transition and ensure a reliable, resilient, and sustainable electrical grid, both now and in the future.

To unlock grid orchestration, it’s important to remember that merely acquiring the right applications is not enough. Grid orchestration applications need a fuel source to function and produce the insights you need to orchestrate the grid. That fuel source is data.

Every business in the utility industry is sitting on mountains of data from both inside and outside their organization. There’s clearly no shortage of it – the real challenges with data center around discovering, governing, and utilizing it.

Utilities’ efforts to access and use their data are often hindered by a combination of the following challenges:

Volume of power grid data.

There’s simply so much data available, especially from sensors and DERs, that utilities struggle to identify and visualize all of it.

Decentralization.

Power grid data is “distributed” by nature, simply meaning that is stored all across the grid ecosystem. Keeping it all in one place (centralizing) is not an option – many utilities have tried unsuccessfully. Keeping data distributed ensures quality and accuracy, but makes it very difficult to locate.

Siloing.

Even if you do locate the right power grid data, it is likely stored in one of three main silos that complicate access: OT data, IT data, and external data. There may even be subsilos within these main silos, each presenting an additional roadblock to navigate.  

Speed.

Grid sensors generate data in near-real time, and the insights within that data need to be leveraged just as quickly.

Volatility.

Additionally, grid data is becoming more volatile, especially with the growth of modern assets like Distributed Energy Resources (DERs). DERs are not as tightly connected to the control room as SCADA connected assets, resulting in volatile data streams.  

Variety. Grid data exists in a wide array of types and formats – some compatible with grid orchestration applications, others not.

So, what’s the solution to circumventing these challenges and unlocking the full power of grid data?

It’s called a grid data fabric.

Specifically, the GridOS Data Fabric.

Let’s start with the basics. A data fabric is a data management solution that enables integration and sharing across heterogeneous data sources. It plays a critical role in helping users “see” across data silos by pulling data together that can be hard to find and share.

It is important to note that a data fabric does not store data – it should not be confused with a data lake or data warehouse. Rather, a data fabric can best be thought of as a foundation that brings together distributed data of all types. Such a distributed data foundation makes it easy for applications, programs, and users to access and leverage the right data – any type, any format, from any location, at any time.

To fully understand how a data fabric works, it is also key to understand the concept of federation.

Data federation is a software process that allows multiple databases to function as one. The process takes data from a range of sources and converts it to a common model. This provides a single source of data that front-end applications can leverage.

A federated database is virtual and doesn’t physically store any data. Since the data is not centralized, its ownership still remains with the different applications and functions within the utility, improving data quality and accuracy.

The GridOS Data Fabric is the federated grid data management layer of the GridOS platform – the first platform designed exclusively for grid orchestration. Essentially, it serves as a distributed data foundation that can fuel AI- and ML-powered applications, grid automation initiatives, and other data-driven use cases that are essential for proper grid orchestration. It is designed to help utilities access, integrate, and contextualize energy data, combined from disparate sources into a unified view capable of spanning T&D and the edge.

The GridOS Data Fabric’s ability to simplify and accelerate the discovery, governance, and utilization of data is needed to unlock the full power of grid data – and, by extension, grid orchestration as a whole.

Simply having better, easier data access and sharing enables a slew of key grid orchestration applications and use cases, including:

• Planning use cases
• DER optimization and look-ahead analysis
• Real-time and look-ahead transmission and distribution integration
• Simulations
• Scenario analysis
• Training data for AI/ML applications
• Grid automation via real-time data
• Proactively and reactively managing disruptions
• Orchestrate multidirectional energy flows to drive up renewables penetration
• Forecasting and visibility
• And more

We will delve deeper into some of these use cases and the inner workings of the GridOS Data Fabric in a future blog. Download our whitepaper for more information on how the GridOS Data Fabric can help you unlock grid orchestration.