HVAC systems are a ripe target for energy savings across a range of facility types: They typically account for 30 to 40 percent of energy use in health care facilities and college campuses and 65 percent of the energy used in pharmaceutical manufacturing facilities.

Chilled water systems also consume substantial amounts of water. Commercial buildings often draw more water for cooling and heating than for any other use — including the obvious ones. Water consumption varies by climate and building type, but studies show the HVAC system may account for up to 48 percent of a building’s water consumption, with restrooms and kitchens using 31 to 37 percent, and landscaping accounting for only 18 to 22 percent.

We recently calculated that an energy-intensive manufacturer could achieve about 80 percent of its targeted energy savings just through HVAC optimization. To achieve results like that, though, facility managers must ensure the equipment operates efficiently at all times and in all situations. Energy-efficient equipment on its own is not enough: Maximizing performance requires optimization software that orchestrates the whole system to utilize the equipment’s designed efficiency. Over time, equipment performance will drift, and the system will need to be adjusted in real time.



Optimization goes well beyond tuning up or replacing equipment.

Typical optimization projects involve some combination of matching the system to actual use requirements; installing instrumentation (such as flow meters, power meters, and temperature and relative humidity sensors) to enable real-time control decisions and analysis; installing variable-frequency drives on fans, chillers, and pumps; installing modern equipment controls; and eliminating bottlenecks. With those measures in place, real-time optimization software can then operate the system for both cost efficiency and energy efficiency.


The most successful optimization efforts follow these three rules:

  1. You cannot optimize what you do not measure — Without an accurate measure of energy use by each piece of equipment in the system, it is impossible to accurately predict and report the impact of varying conditions on the system.
  2. Optimize systems, not just individual components — If an optimization plan focuses only on installing the most efficient pieces of equipment without considering how to maximize performance of the whole system, it won’t capture the total available system efficiency. Holistic automated optimization of HVAC systems typically increases energy efficiency by an additional 10 to 25 percent over just installing new equipment.
  3. Optimization must be automatic, dynamic, and continuous for maximum efficiency — Optimization should be a real-time dynamic process, not a static set-and-forget process. If a plant’s operational control is not based on real-time inputs, it cannot be fully optimized.


You cannot optimize what you do not measure


Focus on whole systems, not just individual components


Must be automatic, dynamic, and continuous for maximum efficiency

FOLLOW THE RULES: Along with energy-efficient equipment, these steps will help achieve true system optimization.


Calculating the current performance of the HVAC system is the first step in the optimization process. A detailed engineering analysis should show an hour-by-hour simulation of the system’s baseline performance against normalized weather data and load profiles for a full year. Next, a scope-of-work document should identify the electrical, mechanical, and control upgrades needed for a holistic optimization program. Based on those two evaluations, the engineering team can create a model that simulates the system’s post-upgrade performance and determines the project’s energy and cost savings.

To support the business case for the project, a life-cycle cost analysis should account for full implementation costs, including mechanical, electrical, controls, optimization, project management, qualification, sales taxes, affiliate staff fees, information technology costs, permits, commissioning, engineering, contingency, and so on; it must also factor in the cost of money, depreciation, utility incentives, and maintenance. A comprehensive analysis lets you calculate the project’s internal rate of return and net present value.

Typical optimization projects involve a combination of the following energy conservation measures:

  • Matching the system to actual use requirements, ensuring proper temperature and relative humidity set points, air-change-per-hour requirements, and space pressurization;
  • Installing instrumentation (such as flow meters, power meters, and temperature and relative humidity sensors) to enable real-time control decisions, measurement and verification, and reports on key performance indicators;
  • Installing variable frequency drives on air-handling unit (AHU) fans, chillers, boiler combustion fans, chilled and hot water pumps, condenser water pumps, and cooling tower fans;
  • Installing modern AHU, chiller, and boiler controls; and
  • Eliminating mixing and bottlenecks (such as hot or rogue zones and undersized terminal units) by replacing three-way temperature control valves with two-way control valves and closing decouplers.

These measures allow optimization software to operate the system for maximum efficiency. For example, intelligently resetting the supply air temperature on an AHU will reduce simultaneous heating and cooling while allowing the system to reset chilled water and hot water temperatures back at the utility plant. An automated system can also control condenser water pumps, cooling towers, and chillers based on their relationship to one another.



At the Penn State Health Milton S. Hershey Medical Center, results exceeded expectations. After the center optimized 12 chillers — eight in the central plant and two in each of the two satellite plants — its energy intensity dropped 4 percent. The project is yielding 4.16 GWh in annual savings, versus the 3.4 GWh facility leaders anticipated when they embarked on the project.

The University of Maryland’s Institute for Bioscience and Biotechnology Research (IBBR) shows how even newer plants with inflexible climate requirements can run more efficiently with the right strategy and technology.

James Johnson, the university’s director of facilities and lab services, converted the five-year-old IBBR plant to an all-variable flow plant and then added an optimization and control layer. From the variable-speed drives and sensors installed on chillers, pumps, valves, and tower fans, the software collects a tremendous amount of data about the plant equipment, including water flow, electrical power consumption, load conditions, and more. It compares the data to control algorithms, assesses plant conditions in real time, and then automatically changes pump and fan speeds using chilled water temperature, equipment staging, and other operational changes to maximize efficiency. The plant now runs 27 to 37 percent more efficiently.

Financial savings can be impressive as well. The corporate campus of a large health care provider in the Southeast is on track to save more than $200,000 each year with its chiller plant optimization. The University of Texas at Austin is saving $1.5 million annually by using the OptiCx platform to reduce electricity, steam, and water usage. And a major hospital chain in the South is saving $900,000 a year after having optimized only about one-third of its portfolio.

Projects like these show that building operators can wring savings out of even the most demanding environments, with new or existing equipment. The key is following the three rules of optimization.

Publication date: 11/5/2018

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