Rapid Energy Model Development for Residential Energy Simulation

This is a web-based, energy efficiency recommendation engine providing a customized “path to zero-net energy” for any existing home. Homeowners can use this technology to quickly check which energy efficiency options make most sense for their individual homes, to reduce their energy use and move them closer to the goal of a zero-net energy (ZNE) home. This tool uses current technologies in building energy simulation and combines it in a novel way with other recent developments in 3D building data from aerial photography and cloud computing, to develop individual 'energy models' of each home. The process is fully automated and repeatable, to allow generation of energy models at a massive scale, from individual homes to neighborhoods and cities. Generating data at this scale provides a unique insight into energy efficiency opportunities in the existing homes sector.

The Building Energy Model (BEM)-based “targeting” and “homeowner engagement” tool combines building energy simulations and energy usage data analytics to identify energy efficiency and solar generation opportunities in existing residential buildings. The tool is currently in a private release stage and is available for use through a web browser. This project sought to develop energy models and conduct parametric simulation analyses on a list of Energy Efficiency Measures (EEMs) for two selected neighborhoods in Santa Monica, California. The analysis resulted in recommendations for a custom path to Zero Net Energy (ZNE) for each home. To complete the Phase 1 evaluation of the tool, the project selected six homes (three from each neighborhood) for evaluation, based on size and vintage. The evaluation team verified the input assumptions, assessed consistency in the translation of given inputs to model inputs, evaluated the accuracy of the tool’s energy savings calculations, and verified the cost assumptions and economic calculations performed by the tool. The project found some errors and inconsistencies with the figures reported by the tool and made specific recommendations on how the tool should be refined for improved accuracy, consistency, and transparency. The tool has great potential for being an effective tool for recommending cost-effective EEMs for individual homes and guiding homeowners with a path to ZNE, and recommends the continuation of this Emerging Technology product into Phase 2, which will further enhance the tool’s fidelity and improve the accuracy of assumptions made in base BEMs.