Building America Team: New Ecology, Inc.

Partners: Fraunhofer Center for Sustainable Energy, Massachusetts Clean Energy Center, and JPB Foundation

Every multifamily central hydronic heating and hot water system is unique. They are custom designed, plumbed, and installed by teams with varying technical capability. Unfortunately, control settings are often best guesses and are not typically optimized. Most central heating boilers and domestic hot water heaters in buildings without building automation systems are not operating optimally, nor is the equipment being adequately maintained, resulting in significant energy waste. Monthly billing data are insufficient to use for correctional purposes and, in most cases, no data are collected on the equipment or system operation. This allows for missed opportunities for energy optimization in many multifamily buildings and may accelerate equipment degradation.

A software tool automating optimization analysis and fault detection will improve multifamily boiler-system optimization for greater energy savings, cost-effectiveness, and scalability.

New Ecology has developed an innovative approach to remedy this problem that incorporates the capabilities of the onboard or third-party boiler controls with our own system of sensors with data collection and analysis protocols. In a project completed in the spring of 2018 comprising more than 100 affordable, multifamily buildings in Massachusetts, New Ecology achieved the following:

  • Savings in over 82% of the buildings,
  • An average of 11% gas savings, based on utility bill data,
  • A maximum of 33% gas savings,
  • Unquantified electricity savings from recirculation pumps, and
  • Thousands of boiler cycles.  

Working with Fraunhofer Center for Sustainable Energy, New Ecology will enhance the data acquisition system and develop algorithms for a software tool to automate the optimization analyses and fault detection process to significantly lower implementation cost. This will greatly improve the cost-effectiveness and scalability of multifamily boiler-system optimization and, hence, the energy savings realized. The algorithms and tool will be developed to:

  1. Identify faults and recommendations that can achieve an average of 15%+ reduction in space heating energy consumption
  2. Reduce analysis time by 80%+ relative to manual approaches
  3. Calculate weather-adjusted energy savings estimates that will be within ±20% of those derived from gas consumption analysis
  4. Achieve less than 3-year payback period for boiler optimization.