Boston Housing Authority
At a Glance
Industry
Public Housing Authority
Project Types
Commercial Energy Efficiency, Data Analysis
Year
2017
Location
Boston, MA
Net Present Value:
$2,200,000
Annual kWh Savings:
760,000 kWh
Annual CO2 Reductions:
1,100 metric tons
Summary
James Hood identified energy efficiency opportunities and researched financing options for buildings in Boston Housing Authority’s portfolio.
Goals
Thanks to dedicated Energy Management staff, an interdepartmental green team and four past EDF Climate Corps fellows, Boston Housing Authority (BHA) has exceeded its goal of reducing greenhouse gas emissions 25% by 2020. However, BHA is struggling to continue operating aging buildings on ever dwindling budgets. EDF Climate Corps fellow James Hood was hired to research a new Federal refinancing opportunity that allows operational and energy savings to leverage debt over 30-40 years.
Solutions
After researching and meeting with cross-functional BHA teams about the new Federal Rental Assistance Demonstration (RAD) program, it became clear that energy savings would be key to sustain developments in the long-term. To estimate these savings, Hood modeled five priority buildings using the Department of Energy’s whole building energy modeling software, BEopt. He streamlined data collection and built a geospatial mapping database of all BHA developments and buildings using Geographic Information Systems (GIS) software and trained Energy department staff on both software systems.
Potential Impact
The five priority buildings show potential energy savings of over $200,000 annually in projects, totaling over $2 million NPV which could leverage over $2.5 million of additional debt to fund these developments over 40 years. The cost savings help make the case for getting the funding needed to implement these energy projects as part of both RAD conversion and for future in-house energy projects. Going forward, Energy department staff can accurately model building energy savings in-house and can integrate data from building models with key information from other departments into a searchable mapping database that can perform geospatial analysis.