Case Study – Chiller Plant Optimization Measurement and Verification
     


By Jenny Conte

CLIENT: Large Suburban Hospital with Central Chilled Water Plant

CHALLENGE:  Perform an independent M&V analysis for the client’s chiller plant and compare it with the M&V analysis performed by the chiller plant optimization vendor. Client had used the vendor solution to help assess the competency and effectiveness of each team member responsible for maintenance and operations, including supervision and management, to identify deficiencies that cause or contribute to system outages and to recommend corrective actions. However, Client questioned the accuracy and therefore effectiveness of the vendor solution for these purposes.

BACKGROUND: The client had engaged a major building controls vendor to optimize the operation of their central chilled water plant to help reduce operating cost. The vendor provided the client with yearly M&V reports documenting how much energy and money was being saved using the vendor’s system, but Client was concerned that reported savings were too high. The vendor was reporting annual reductions in power consumption ranging between 19% and 28% (average of 23% for a 30-month period).

PRELIMINARY ANALYSIS: The vendor’s reports relied upon a base year’s operating data which included a calculation of Kw/ton vs Outside Air Temperature (OAT). Below figure 1 is a graph of the vendor’s calculations.

Note that the BASE kW/ton performance plot is a straight line, and it is not very sensitive to OAT.  Because the chiller compressor motors, water pumps and cooling tower fans have variable frequency drives, we should expect the BASE kW/ton plot to be sensitive to OAT.

Figure 1: Total plant efficiency and ancillary efficiency of performance characteristics

ACCLAIM’S EXPERTISE AT WORK: The client provided Acclaim with the data the vendor used to prepare their yearly reports to the client.  Acclaim quickly noticed several issues with the vendor’s data.

  • The weather normalization data was obtained from the building automation system OAT sensor
  • Onsite dry bulb temperatures (DBT) from Client’s building management system (“BMS”) were used for weather normalization, and these exhibited many clearly erroneous readings
  • The client’s energy cost was the total blended energy cost, which presumed that demand-based charges were affected as much as kWh consumption costs
  • The base year was not developed using measured empirical data but was constructed from fairly simplistic assumptions

Acclaim performed its analysis based on the following:

  • Certified wet bulb temperature data from an airport just six miles from chilled water plant and medical institution
  • Client’s actual price and rate structure for electricity instead of a “blended” unit cost
  • Base year performance that reflects the effects of weather on the chilled water plant

Acclaim believes that ancillary load behavior during the baseline period would have resembled behavior during future periods with the vendor system in place, but less efficiently than with the system.  Acclaim looked to a statistical measure of actual outputs during the Analysis Periods to create a conservative and defensible estimate for its ancillary baseline.  We then added this curve to our combined chiller curve to produce our plant baseline curve.  Because it represents the very least efficient measured operating levels of the equipment, we believe it is a fair assumption of pre-optimization baseline operation. 

Acclaim’s analysis yielded considerably lower kW/ton than the vendor reported, as shown in Figure 2 below. 

Figure 2: Plant baseline kW/ton versus outside air temperature

The vendor applied unit power costs in its M&V Reports of as much as $0.0620/kWh, which included utility demand charges, for use in its savings calculations. However, Acclaim calculated actual impacts to each rate component based on interval power consumption at the meter and determined that savings due to the vendor system were minimal in utility demand charges, and used an effective rate of $0.03256/kWh.

RESULTS: Acclaim calculated an average weather-normalized power reduction during the Analysis Periods of 1,928,525 kWh (annualized 2,278,757 kWh for the actual, higher temperature Analysis Periods), which compares to 3,108,846 kWh and 4,112,778 kWh in the vendor’s 1st and 3rd Year Reports, respectively. Savings are calculated by multiplying expected ton-hour load from an average weather year at the client’s site by the actual and baseline kW/ton efficiency at the temperatures of an average weather year.

Acclaim’s calculated reduction is 38% lower than the vendor reported in its 1st Year M&V Report, of which 32% of the 38% is due to Acclaim’s adjusted baseline. The remaining 6% results from Acclaim’s weather normalization. We normalized to an average weather year (based on NOAA data from 2006 – 2019), and the temperature for the analysis period was 2.9 °F higher on average than a typical year. Also, Acclaim used ambient wet-bulb temperatures for the ton-hours calculations, because it has a higher correlation than ambient dry bulb temperature.

Acclaim calculated annualized savings just over $77,000, which contrasts with the vendor’s reported $193,000 @ $0.0620/kWh.

The vendor’s system reported weather data (wet bulb and dry bulb temperatures) from sensors on the client’s property. By plotting this data against the NOAA recorded temperature from nearby airport, Acclaim proved the unreliability of the onsite data and justified using the airport’s data. BMS temperature data is commonly measured by using sensing devices called thermistors, which have a much larger error range that the precision instruments used by NOAA and which are commonly not calibrated. NOAA temperature data is measured by certified precision instruments, which are highly accurate. NOAA instruments are calibrated annually, and their performance is monitored daily. For these reasons and because of its proximity to the hospital (2.7 miles), Acclaim believes that the NOAA data from the airport most accurately represents outdoor air temperature at the client’s site. Therefore, we relied upon temperature data obtained from the Land NOAA station for our weather correlations.

The actual ton-hours of cooling reported by the vendor’s system are a function of actual chilled water flow, and because Acclaim understands that this flow was calculated using measured differential pressure across the chillers, there may be error in tonnage used in both vendor’s and Acclaim calculations.

THE “TAKE-AWAY”: Acclaim was able to provide an unbiased and technically-superior measurement and verification study to our hospital client.