Abstract
For homeowners, typical choices to reduce net energy use in their homes include: upgrading their home with a tailored efficiency retrofit or investing in roof-top solar. Determining the unique combination of these options that will provide the most cost-effective solution requires analysis for each home. This analysis needs to be presented in a simple and actionable way to homeowners. The solution should also be easily scalable to thousands of homes to enable utilities to better target efficiency program options and support solar installations. Sacramento Municipal Utility District (SMUD) piloted a new tool developed by Vistar Energy called XeroHome that automates the assessment of energy efficiency and solar opportunities in existing homes. XeroHome demonstrates an approach to using building energy modeling, energy use data analytics and homeowner engagement to identify and target energy efficiency opportunities at scale. XeroHome uses automation to build an EnergyPlus model for each home, based on information from public data sources such as property assessment records, building permit records, aerial/satellite photography, and template models derived from ResStock. Utilizing cloud computing, machine learning and optimization algorithms, energy upgrade packages are ranked by cost-effectiveness for each home and presented over an interactive web-portal. This paper discusses SMUD's pilot project using XeroHome to conduct analysis for 1,500 existing homes in Sacramento, CA. Development of XeroHome's advanced analytics capabilities are discussed in the context of applicability for utility programs.
Original language | American English |
---|---|
Number of pages | 12 |
State | Published - 2018 |
Event | 2018 ACEEE Summer Study on Energy Efficiency in Buildings - Pacific Grove, California Duration: 12 Aug 2018 → 17 Aug 2018 |
Conference
Conference | 2018 ACEEE Summer Study on Energy Efficiency in Buildings |
---|---|
City | Pacific Grove, California |
Period | 12/08/18 → 17/08/18 |
Bibliographical note
Available from ACEEE: see https://aceee.org/files/proceedings/2018/index.html; see NREL/CP-5500-72176 for preprintNREL Publication Number
- NREL/CP-5500-74163
Keywords
- building energy modeling
- cloud computing
- cost-effective
- efficiency retrofit
- energy efficiency
- energy upgrade
- energy use data analytics
- EnergyPlus
- homeowner engagement
- machine learning
- net energy use
- optimization algorithms
- residential buildings
- ResStock
- roof-top solar
- Sacramento Municipal Utility District
- SMUD
- Vistar Energy
- XeroHome