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Energy efficiency measures – Institutional – Hospital – Performance analysis / USA

Template assignment

A new energy control system, a new lighting system and a new cooling system (chiller) were installed in a hospital located in Chicago, Illinois, United States of America. These energy efficiency measures were implemented over a period of several years. Determine the energy savings achieved after the installation of these systems. Electricity is used for space cooling and other typical electrical loads. Natural gas is used for space and water heating. The hospital has an outdoor swimming pool that is heated between the months of May and June.

Teacher's notes

Follow these steps:
 
Start

►Select climate data for Chicago

 
Data

Step 1 - Consumption:
a. Import natural gas consumption data (in million Btu units) (Template_EEM_Institutional_Hospital_Performance_Analysis_USA_NaturalGas.csv)
b. Import electricity consumption data (Template_EEM_Institutional_Hospital_Performance_Analysis_USA_Electricity.csv)
Step 2 - Factor of influence: Download NASA weather data
Step 3 - Data processing:
a. Calculate cooling and heating degree-days (the reference temperatures are estimated at 17°C and 14°C respectively)
b. Merge cooling degree-days data into the electricity consumption data table
c. Merge heating degree-days data into the fuel consumption data table

 
Analytics

Whole data set: Natural gas – 2006-2011

►Tools - Graph: Generate a time series graph showing the natural gas consumption and heating degree-days
Note: the graph shows a good correlation except for the summer months; when there is no space heating, only water heating, especially during the months of May and June when the outdoor swimming pool is heated.
a. In the natural gas data table, insert a new column and manually enter the swimming pool natural gas consumption estimate
b. Insert another column to calculate the natural gas used for space heating and service hot water
Step 1 - Baseline: Establish the baseline based on the entire duration of the natural gas consumption data set excluding the swimming pool water heating consumption, using the regression analysis
Step 2 - Target: Skip this step
Step 3 - Comparison: Generate a CUSUM graph
Note: A change in the CUSUM graph slope indicates that a change occurred in the system energy performance.

Period prior to energy efficiency measures implementation: Natural gas – 2006-2007

Step 1 - Baseline: Establish the baseline based on the period prior to energy efficiency measures implementation using the regression analysis
Step 2 - Target: Skip this step
Step 3 - Comparison: Generate a CUSUM graph
Note: The last data point on the CUSUM graph shows the total energy savings after the energy efficiency measures are implemented based on the baseline prediction.

Period after energy efficiency measures implementation: Natural gas - 2010

Step 1 - Baseline: Establish the baseline based on the period after energy efficiency measures implementation using the regression analysis
Step 2 - Target: Set the target to 0 or skip this step
Step 3 - Comparison:
a. Generate a CUSUM graph
b. Generate a control chart to track energy performance on a continuous basis

 
The Natural gas 2006-2007 CUSUM graph shows that the natural gas consumption was reduced by approximately 720 million Btu during the first four years after the energy efficiency measures were implemented. This represents approximately 180 million Btu per year.
 
Whole data set: Electricity – 2006-2011

Step 1 - Baseline: Establish the baseline based on the entire duration of the electricity data set using the regression analysis
Step 2 - Target: Skip this step
Step 3 - Comparison: Generate a CUSUM graph

Period prior to installation of the new lighting system: Electricity – 2006-2007

Step 1 - Baseline: Establish the baseline based on the period prior to installation of the new lighting system using the regression analysis
Step 2 - Target: Skip this step
Step 3 - Comparison: Generate a CUSUM graph

Period prior to installation of the new chillers: Electricity – 2007-2008

Step 1 - Baseline: Establish the baseline based on the period prior to installation of the new chillers using the regression analysis
Step 2 - Target: Skip this step
Step 3 - Comparison: Generate a CUSUM graph

Period after energy efficiency measures implementation

Step 1 - Baseline: Establish the baseline based on the period after the implementation of energy efficiency measures using the regression analysis
Step 2 - Target: Set the target to 0 or skip this step
Step 3 - Comparison:
a. Generate a CUSUM graph
b. Generate a control chart to track energy performance on a continuous basis

 
For example, the Electricity 2006-2007 CUSUM graph shows that the electricity consumption was reduced by approximately 74 MWh during the first year following the installation of the new lighting system. And the Electricity 2007-2008 CUSUM graph shows that the electricity consumption was reduced by approximately 45 MWh during the first year following the installation of the new cooling system (chiller).
 
Reporting

Step 1 - Report: Create a report for managers
Step 2 - Edit: Insert a text page to describe the analysis
Step 3 - Output: Export the report in PDF (*pdf) format

 
Solution

The worked-out solution is the data file selected from within the RETScreen Project Database. The user automatically downloads the Project Database file while downloading the RETScreen software.