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SMART BUILDING BEST PRACTICE SHOWCASE

888 Boylston Street

Located at Prudential Center in the heart of Boston’s vibrant Back Bay
CASESTUDY
888 Boylston Street neighborhood, 888 Boylston Street is a 17-story mixed-use building con-
Project Details
Boston Properties
Number of Buildings: 1 Boston’s Most Sustainable Building
Square Footage: 425,000
Location: Boston, MA Located at Prudential Center in the heart of Boston’s vibrant Back Bay neighborhood, 888 sisting of a three-story retail base, 14-story office tower and two levels of
Project Status: Started Boylston Street is a 17-story mixed-use building consisting of a three-story retail base,
Start date: 14-story office tower and two levels of subgrade parking. Focusing on “High Performance
Target Completion date: Design from the Inside Out,” 888 Bolyston promotes health, productivity, and a superior
Primary Contact: user experience. The project has been designed to optimize energy efficiency, and is
Ben Myers expected to operate 47% more efficiently than buildings of the same type in a similar subgrade parking. Focusing on “High Performance Design from the Inside
bmyers@bostonproperties.com climate zone. Sustainability features include a dedicated outside air system with active
chilled beams, heat recovery, LED lighting, and rainwater harvesting. The roof and crown
Jim Whalen of the building accommodate solar photovoltaic panels and fourteen vertical axis wind
jwhalen@bostonproperties.com turbines, which together produce enough power for 15 homes in Massachusetts. Living
walls and a green roof provide connections with nature and support a healthier urban
ecosystem at the Prudential Center. Out,” 888 Bolyston promotes health, productivity, and a superior
user experience. The project has been designed to optimize energy effi-
ciency, and is expected to operate 47% more efficiently than buildings of
the same type in a similar climate zone. Sustainability features include
Goals: Operations Energy Efficiency Sustainability Tenant Experience Financial Optimization
a dedicated outside air system with active chilled beams, heat recovery,
CHALLENGES:
• Procurement, installation and interconnection of the renewable energy system, solar photovoltaics,
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and vertical axis wind turbines
• Performing the necessary due diligence and execution of our first active chilled beam building, as
opposed to a conventional variable air volume (VAV) system LED lighting, and rainwater harvesting. The roof and crown of the build-
• Underwriting features like high performance glazing that increase construction costs
SUCCESSES:
• We delivered the most sustainable building in Boston
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• The green building features are a unique product identity that has been attractive to customers with SHOWCASE SPONSORS: ing accommodate solar photovoltaic panels and fourteen vertical axis
a strong commitment to sustainability, and they provide measurable increases to standard returns
• Demonstrated our commitment to sustainable development as responsible stewards of the
built environment
wind turbines, which together produce enough power for 15 homes in
Massachusetts. Living walls and a green roof provide connections with
nature and support a healthier urban ecosystem. The high performance
design strategy and green power commitment reduce annual carbon
emissions by 96%.
Stanford University
CASESTUDY Stanford recently transformed its energy supply from a 100% fossil-fu-
Stanford’s Central Energy Optimization Software
Project Details Stanford University
Number of Buildings: 155+ Transition to a Smart, Low Carbon Energy Supply Paradigm el-based cogeneration plant to an electric grid-sourced, high efficiency
Square Footage: 10 Million
Location: Stanford, California Stanford recently transformed its energy supply from a 100% fossil-fuel-based cogeneration
plant to an electric grid-sourced, high efficiency heat recovery system. At the heart of the
Project Status: Ongoing system are three Heat Recovery Chillers (HRC) that concurrently generate district cooling
Start date: 2012 and heating along with three large thermal energy storage tanks. Balancing equipment run
Target Completion date: 2015 time, optimizing energy efficiency, and minimizing operating costs is a complex challenge, heat recovery system. At the heart of the system are three Heat Recovery
Primary Contact: made manageable through a Model Predictive Control system developed by Stanford
Gerry Hamilton known as the Central Energy Plant Optimization Model (CEPOM). Under direction from
gerryh@stanford.edu Stanford, CEPOM was adapted for industrial use and incorporated into Stanford’s new
central energy facility (CEF) control system by Johnson Controls Inc., naming the updated
software program the Enterprise Optimization Solution (EOS). The system predicts the
university’s background energy use profile for the next seven days and schedules CEF Chillers (HRC) that concurrently generate district cooling and heating
operations to most effectively meet those loads. EOS performs this forward looking analysis
and recalibrates operating schedules as needed every 15 minutes, enabling the CEF to
virtually run itself.
along with three large thermal energy storage tanks. Balancing equipment
run time, optimizing energy efficiency, and minimizing operating costs
is a complex challenge, made manageable through a Model Predictive
Goals: Operations Energy Efficiency Sustainability Tenant Experience Financial Optimization
Control system developed by Stanford known as the Central Energy Plant
CHALLENGES:
• Building a Central Energy Facility that could match in practice the efficiencies and cost savings proven in theory
• Upsize existing HRC technologies to meet Stanford’s loads while incorporating sufficient monitoring and controls to Optimization Model (CEPOM). Under direction from Stanford, CEPOM was
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ensure reliability levels needed for major research laboratories and hospitals
• Finding a CEF controls optimization software package that had the smarts to achieve peak efficiency while also
ensuring all critical loads were reliably met
SUCCESSES:
• Stanford developed and patented a new plant operating system to continuously model CEF adapted for industrial use and incorporated into Stanford’s new central
performance, expected loads, and forecasted energy rates to ensure optimum system performance
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• All CEF operating data and building utility interface data is compiled in a new process data historian for SHOWCASE SPONSORS:
ease of monitoring and availability for third party analytics applications
• EOS enables the CEF to achieve the university’s goals of 68% reduction in GHG emissions, 50%
reduction in energy consumption, and 15% reduction in water use energy facility (CEF) control system by Johnson Controls Inc., naming the
• EOS is an energy modeling and dispatch system that uses over 1,220 variables to develop 15-minute
dispatches that show the optimal way to run the CEF
updated software program the Enterprise Optimization Solution (EOS). The
system predicts the university’s background energy use profile for the next
seven days and schedules CEF operations to most effectively meet those
loads. EOS performs this forward looking analysis and recalibrates oper-
ating schedules as needed every 15 minutes, enabling the CEF to virtually
run itself.
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