AutomatedBuildings.com Article - Data-Driven Management for Building Portfolios

Managing a diverse portfolio of buildings and systems can be a daunting task that often becomes a balancing act of keeping occupants comfortable and happy while simultaneously trying to minimize operating and maintenance costs. Major repairs can build up over years of deferred maintenance, leaving the building management team unsure where to start. Repairs are often prioritized by complaints from occupants, leaving more pertinent items unaddressed because they do not directly impair occupant comfort. When compounded over time, the cost of not performing the maintenance becomes remarkably high.

Falcon Engineering found this to be exactly the case at a large K-12 public school district in the Northeast where several newly constructed schools, as well as many older ones, were among the most costly to operate. After further investigation, it was discovered that the complex systems within the newly constructed schools were not performing as designed, resulting in substantial waste. The buildings were flagged by the prioritization algorithms within Falcon’s central database system. The system prioritizes buildings based on monthly energy and cost data automatically imported from the district’s local utility provider.

As the list of deferred maintenance tasks grows, it is vital that tasks and capital improvement investments are prioritized with a “data-driven” approach. The closed-loop data, information, action cycle such as the one pictured below will allow the school facilities staff to continually monitor and improve the energy efficiency of their buildings with automated feedback from monthly utility bills.

In addition to their daily responsibilities, facilities and management staff are continually faced with the challenge of prioritizing maintenance tasks within a confined budget. A central database can allow facilities management to make smart, data-driven decisions. Utility data stored in such a database can not only provide the necessary data for benchmarking but can in fact act as the backbone for continuous improvement programs; however, for a portfolio having large number of buildings it becomes a necessity to prioritize buildings for immediate attention. Such a priority list (top 10 list) can help in project planning and allocation of resources needed for energy efficiency and renewable energy projects.

A variety of metrics can be used for the quantification of utility data. Metrics such as Energy/SF, $/SF, etc. can be used in making such prioritizations. The Falcon Group considered the following parameters to prioritize work:

The prioritization index was generated based on weighted potential cost and energy savings. To evaluate the effect of various decision variables (such as Cost intensity and Energy Use intensity) on these metrics, a Portfolio Prioritization Tool was created as shown below. This tool utilizes two independent methods to prioritize buildings: 1) weighted savings method and 2) frequency method.
The weighted savings method is used to generate the priority index for all the buildings in the portfolio. The user decides cost and energy intensities (i.e. $ 1.65/SF) to calculate potential savings. The user also selects weight factors (0 to 100 %) for cost and energy. These are used to scale the cost and energy based on the district’s priorities. For example, the district can select 60% and 40% weight factors for cost and energy respectively putting an added importance on utility costs and a reduced importance on BTU consumption.

Based on the user inputs and the pre-programmed prioritization algorithm the tool generates a prioritization list. The top buildings in the list are the buildings having the worst performance. Implementation of energy efficiency projects in these buildings would bring about the Energy/Cost savings specified in the input.

The second module of this tool was the frequency analysis. This module evaluates the occurrence of a specific building in the top 10 lists as the weighing factors are varied throughout the spectrum (i.e. Energy from 0% to 100% and cost from 100% to 0%). This helps us in selecting the buildings that stay in the top priority lists irrespective of the values of the weighing factors. Frequency analysis tables as shown below are generated for every case.

Once again the use of a live central database can prove advantageous if this tool is linked with updated monthly utility data. In that case the top priority list will be dynamic and would keep on changing based on the implementation of energy efficiency projects with time. Hence as mentioned earlier, it will act as the backbone for the continuous improvement program.

The Falcon Group worked in conjunction with EDF Climate Corps (http://edfclimatecorps.org/) to audit three schools that were included on the Top-10 list using both the weighted savings and frequency methods. The findings from the prioritization tool were confirmed during the audits. Two of the three schools were constructed within the last ten years and despite the inclusion of high efficiency mechanical equipment, high performance building envelopes and renewables, energy costs per square foot were nearly twice the district average. The third building, constructed in 1963, performs in a similar fashion to the new construction buildings.

The majority of the central HVAC equipment was not maintained or running properly during the time of the audits. The following list includes some of the conditions observed:

Corrective action will result in increased occupant comfort, extended useful service life for HVAC equipment and ongoing cost savings that can be reinvested in other areas of the school district.

The district will use the results and recommendations from the energy audits to plan energy efficiency and renewable energy retrofit projects at high priority schools. All findings will be stored in the central database allowing authorized parties within a particular project to quickly reference historical information. The automated utility data import will allow for easy energy savings verification before, during and after the implementation of an energy efficiency project. This automated feedback closes the loop in the data information action cycle, allowing for continuous improvement. From this cycle, the facilities staff can infer best practices and important lessons learned to be implemented at other schools.

About the Authors

Casey Birmingham, Project Manager – The Falcon Group
Mr. Birmingham is a Project Manager with the Energy/MEP division at the Falcon Group, specializing in energy audits, energy monitoring and visualization and building operations. He has designed and installed a low-cost energy monitoring and visualization system for the Falcon Group’s Headquarters office in Bridgewater, NJ. The system tabulates minute by minute electric and natural gas data and provides results and recommendations based on weather-correcting factors.

Mr. Birmingham and the Energy/MEP division have led a variety of EERE building retrofit projects over the past few years, including the conceptualization and design of a building energy management system (BEMS) as part of the New Jersey Pay for Performance program. The BEMS will utilize data from communicating thermostats for optimized control of the building’s boilers, chiller and VFD drives. When complete, the project will reduce the building’s site energy consumption by over 40%, saving over $380,000 in annual operations costs.

He is a graduate of Northeastern University and holds a Bachelor’s Degree in Mechanical Engineering. He currently holds his Engineer in Training (EIT) certificate and is pursuing a professional engineering license. He is a member of the American Society of Heating, Refrigerating and Air Conditioning Engineers (ASHRAE). He has completed coursework provided by ASHRAE in both HVAC and HVAC controls. This is Mr. Birmingham’s second contribution to AutomatedBuildings.com.

Pankaj Rajput, Intern/Mechanical Engineer – The Falcon Group
Mr. Rajput is a Mechanical Engineering Intern with the Energy/MEP division at the Falcon Group. He is currently pursuing his Masters in Mechanical Engineering with specialization in numerical modeling of thermal and fluid systems, from New York University. He has worked on the creation of a centralized energy database for measurement and verification of energy savings and the automation of various database management processes for Falcon’s Energy Division.

Mr. Rajput is a graduate of the Indian Institute of Technology (BHU), Varanasi, and holds a Bachelor’s degree in Mechanical Engineering. Before attending graduate school he worked as an Executive Engineer at NTPC Ltd., India’s largest power corporation for two years. He is an active member of American Society of Mechanical Engineers (ASME), American Institute of Aeronautics and Astronautics (AIAA) and The New York Academy of Sciences. This is his first contribution to AutomatedBuildings.com.

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