The objective of this project was to conduct a demonstration of the Energy Performance and Monitoring Optimization (EPMO) system prototype used to improve the energy efficiency of both heating and cooling systems. The EPMO system was implemented in this demonstration project as an extension of the existing Building Management Systems (BMS) for optimization of control schedules, energy performance visualization, and system diagnostics for building and district heating systems. The system was demonstrated in two buildings at the Naval Station Great Lakes in Illinois.

Technology Description

The EPMO system integrates optimal control algorithms with system performance monitoring, diagnostic tools, and visualization tools. The control algorithms use weather forecast data, zone sensor data, meter data, and information from the air handling units (AHUs) and terminal units to generate optimal control schedules. For example, an optimal control schedule can control the discharge air temperature values to minimize energy consumption while meeting comfort constraints. The EPMO diagnostics tool uses the sensor and meter data to detect and isolate equipment faults, such as stuck dampers or valves, to prioritize the fault correction based on energy impact. The EPMO visualization tool continuously displays the diagnostics information to facilitate understanding of the equipment fault impacts on energy consumption.

Demonstration Results

Based on the performance data recorded during the demonstration period, it was estimated that, on average, the EPMO system exceeded the energy consumption reduction target of 20% and improved occupant thermal comfort by reducing the number of instances outside of the temperature comfort band by 75%. The scalability of the EPMO system was confirmed through the use of an automated method for control schedule optimization, which requires minimal customization for each new system compared to the effort required to retune baseline system control schedules. The robustness of the EPMO system was confirmed by the system correctly diagnosing equipment faults for heat exchanger dampers and valves 84% of the time.

The economic objectives of the demonstration were met with a Simple Payback of 3.5 years and Savings-to-Investment Ratio of two for the EPMO system for the demonstration site buildings. The EPMO system performance was estimated using the sensor and meter data recorded during 26 demonstration days conducted during the period of November 2012 to March 2013 for three AHUs and 54 terminal units. These economic impacts depend on several variables (equipment age, building type, etc.) and may be different for other sites. A unique feature of the EPMO system is its adaptability that can lead to reduced operational costs by automatically re-optimizing the control schedules to accommodate equipment faults that are detected in real-time.

Implementation Issues

The scalability and energy savings potential demonstrated in this effort has led to continued efforts and investments from UTRC targeted at maturing the EPMO system components, including automation to operate without expert supervision. The EPMO diagnostics technology has continued to be matured on several full-scale building HVAC systems. The EPMO optimal control system technology was further matured and implemented in the Energy Efficient Buildings Hub, in Philadelphia, Pennsylvania. In addition, UTRC has been developing and demonstrating an adaptive optimization-based building HVAC control algorithm with the objective of maximizing energy savings and comfort control with less reliance on a-priori developed building and HVAC equipment models.