Over the last decade, we have researched and developed novel workflows designed to assess any building in a fraction of the time, and at a fraction of the cost, compared to traditional methods. This work has gone through rigorous technical reviews and has been published in some of the most reputed scientific journals.

While working as consultants to develop decarbonization plans for several large university campuses over a decade ago, our founders recognized that the effort and cost associated with traditional assessment methods simply cannot be replicated at the scale and rate at which the existing building stock needs to be decarbonized. Our approach has evolved over time, from a basic spreadsheet tool to track campus carbon emissions to a fully developed API that can analyze any building, anywhere in the world, using only a basic set of information. This evolution can be traced through various academic papers and articles published in peer-reviewed scientific journals.

A comparison of two modeling approaches for establishing and implementing energy use reduction targets for a university campus

S. Nagpal, C. Reinhart | Energy and Buildings, 2018

This paper compares two different traditional energy model approaches to assess a building portfolio –one spreadsheet based, and the second based on archetype building energy models. This work identified the gaps in current techniques and established the need for new workflows.

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A methodology for auto-calibrating urban building energy models using surrogate modeling techniques

S. Nagpal, C. Mueller, A. Aijazi, C. Reinhart | Journal of Building Performance Simulation, 2018

To work towards an ideal model that fills the above gaps, while significantly reducing the computational cost of developing building energy models, this paper proposes a hybrid auto-calibration methodology with rapid-response data-driven approximation techniques.

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A framework for using calibrated campus-wide building energy models for continuous planning & greenhouse gas emissions reduction tracking

S. Nagpal, J. Hanson, C. Reinhart | Applied Energy, 2019

This paper presents a framework to expand the point-in-time analysis capabilities of conventional energy modeling platforms and proposes a tool for the development and implementation of portfolio-level continuous energy tracking and planning systems.

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Auto-calibrated urban building energy models as continuous planning tools for greenhouse gas emissions management

S Nagpal | Massachusetts Institute of Technology, 2019

All the papers mentioned above were comprehensively combined in a doctoral dissertation that presents workflows to evaluate future carbon scenarios for large building portfolios in the form of a continuous planning tool implemented at the campus of Massachusetts Institute of Technology.

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