The goal of this project was to complete strategic decarbonization reports for several telecom switch facilities located throughout Massachusetts. These reports aimed to identify ways in which the carbon emissions of these facilities could be reduced, via analysis of on-site surveys and several years of data on utility/electricity usage throughout the sites.

My work on this project encompassed preparing and analyzing utility data in Microsoft Excel, compiling a list of all existing equipment within the facilities, and creating riser diagram representations of the facilities within Revit.

The most important part of the report was analyzing how much of each type of utility (electric, gas, water, etc.) each facility consumed, and by extension emitted in carbon. From the company, we were provided with a list of utility bills for each month from each facility. Values from these bills, such as usage and cost were input into a Microsoft Excel spreadsheet. Readouts from battery distribution fuse bay (BDFB) units, which managed power distribution, throughout the facility were also input.

For some buildings, multiple utility meters were present. In order to understand which units ascertained to what meters, I compiled a list of all equipment throughout the facilities and their locations, complete with equipment labels and unit types. This aided in analysis as it allowed us to determine which units likely made up a bulk of utility usage. For ease of the reader, these lists were also made into riser diagrams on Revit showing the location of units and were attached to each report as an appendix.

Once the data was entered into Microsoft Excel, several equations were set up to calculate various metrics. These included the cost of each utility per unit, the total carbon emissions based on eGRID data, and power use efficiency based on BDFB data. This data was also mapped to charts, showing usages by month and the percentages of which utilities caused the most carbon emissions from the facilities. For monthly data charts, abnormally hot or cold months were noted to account for temperature-driven fluctuations in energy demand.  

The analysis revealed varying levels of energy efficiency across the company’s facilities. Electricity was the largest contributor to both cost and carbon emissions, while gas and water usage were relatively minor but still showed opportunities for conservation. The data also identified a few old, high-consumption units, which became focal points for efficiency improvements. Comparison between facilities with newer and older equipment confirmed that upgrading existing units yielded greater efficiency.