Data democratization: developing open source data and models

Designing future clean energy systems and the best* pathways to achieve them requires access to high fidelity data and models, with high spatial and temporal granularity. Extensive effort has been made towards understanding our current energy system and modeling future changes: these may include climate and weather models for wind and solar potential across the world, techno-economic and socio-economic models for technology adoption and market proliferation, energy and electricity demand growth models in different customer segments, and synthetic power networks to model electric grids. However, a significant gap still remains, particularly in power systems where real data of network topologies, utility models, and customer data are not widely available due to data privacy concerns and system security. Real energy data is difficult to find, typically not publicly available, and lacks standardization. Further, as we look towards data-driven methods including AI and ML for prediction and real-time operations, representative datasets are needed to support algorithm development and offline testing if we have any hopes to transfer these technologies from research labs to the field. The creation of synthetic datasets with realistic electric grids accompanied with representative load profiles and DER adoption patterns requires considerable effort, but is a valuable and necessary task. 

* In the multidisciplinary world of energy systems, "best" can be measured along multiple axes, with different weights to each factor depending on the application. Generally, best can include cost, carbon reduction or abatement, equitable access, timeline to technology deployment, among other metrics.

Nationwide Distributed Energy Resource Modeling

In collaboration with Microsoft Research and Breakthrough Energy


We are featured in the July edition of Microsoft Research's Research Focus Blog, on Twitter and LinkedIn!

Distributed energy resources (DERs) like residential solar,  utility storage, and electric vehicles present a challenge to grid operations. In order to understand their impact on future grid operations, control, and decarbonization initiatives, we need visibility into the distribution grid. We need data and models. 

We have assembled a project-driven dataset of DERs for the contiguous U.S., generated using only publicly available data. Our dataset is integrated with a high-resolution test system of the U.S. grid which has high spatial model of the U.S. transmission system and bulk resources. Our integrated U.S. grid model and DER dataset enables planners, operators, and policy makers to pose questions and conduct data-driven analysis of rapid decarbonization pathways for the electricity system. We have also assembled a Research Project Database which poses a series of open technical and policy questions related to decarbonization initiatives. Our integrated DER dataset and US grid model can be used towards answering these questions and understanding pathways to deep decarbonization.

This is our Call to Action: for the energy community to collaborate on enhancing datasets, further developing the modeling and simulation capabilities of integrated test systems, and sharing insights around how to reach decarbonization goals.