electricity consumption power-house report presentation -danielle jacobs -callum bugler -salaama...
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Electricity ConsumptionPower-HouseReportPresentation
-Danielle Jacobs-Callum Bugler-Salaama Maneveld-Clive Mncwabe-Sam Skosana
• Data collection
• Current system is tedious and ineffective and not managed effectively.
• Delays are caused because the collection of data is not collected in a standardised format
• Often the data is incorrect and/or incomplete
• Powerstar has proven to be problematic.
Situation of Concern
• Reduce UCT’s expenditure on electricity
• Through better data recording, there is an opportunity for improved managerial decisions to be made going forward.
• By lowering electricity usage the university is reducing the core contributor to its carbon footprint.
Business Opportunities
• Await results regarding refitted environmentally friendly equipment as well as add further environmentally additions to the campus
• Use the IS department and the class of INF3011F to address the problem at hand.
• Hire external, private sector help.
Analysis of Options/Alternative Solutions
• Improve the current data collection method
• Calculate UCT’s carbon footprint caused by the scope 2 indirect upstream activity
• Report fact-based conclusions on findings which are comprehensible and contextual regarding our project.
Project Objectives
Data Collection
Data Data format Data Holder Comments
Main Campus, Satellite Residences, Med Campus and Hiddingh Campus
Excel sheet Yusef Davids andShane Pontes
Properties and Services Utilities data used for electricity billing; monthly breakdown.
GSB Excel sheet Charlene Paris Figures were given in an excel spreadsheet.
Off Campus Website to Excel sheet PowerStar Data was transcribed from the website.
UCT Population Excel sheet Registrar’s Office
This is the total of students registered at UCT for 2014 (31254) and the staff was estimated to 5000.
Emission Factor Excel sheet Sandra Rippon
IS department chose the emission factor based on the GHG protocols recommended for 2014.
UCT Per Campus Carbon Emissions for 2014
65%
14%
5%
16%
0% 1%
Main Campus
Medical Campus
GSB
Satellite Residences
Hiddingh
Off Campus
UCT Per Campus Monthly Electricity Consumption for 2014
January
February
March
AprilMay
JuneJuly
August
Septem
ber
October
November
Decem
ber0
500000
1000000
1500000
2000000
2500000
3000000
3500000
4000000
4500000
Main CampusMedical CampusGSBSatellite ResidencesHiddinghOff Campus
KWh
UCT Per Campus Electricity Consumption Comparison for 2013 and 2014
Main Cam
pus
Medica
l Cam
pusGSB
Satel
lite Resi
dence
s
Hiddingh
Off Campus
0.00
5,000,000.00
10,000,000.00
15,000,000.00
20,000,000.00
25,000,000.00
30,000,000.00
35,000,000.00
40,000,000.00
45,000,000.00
50,000,000.00
20132014KW
h
• Emission Factor
• Data conversion to CO2 equivalents
• Comparison of Results
Carbon Footprint Calculation
Units 2013 2014
Tons CO2-eq 71 734 879.40 68 287 772.03
• Missing buildings on Power star(they are grouped)
• Some medical school meters not accounted for.
• Loadshedding late in the year
• Software malfunction
• Human error
Data Anomalies
• Occupancy Sensors
• Solar Heating in Residences
• Shutting Off Computers After Inactivity
• Power Down Challenge
• Electricity Week
Recommendations
Sustainable Data Collection Recommendations
• Implement an improved automated system that records energy consumption more efficiently and accurately.
• Standardize data capture templates across all campuses.
• Apply built-in conditional formatting and interactive graphs to Excel templates to highlight input errors.
Data Capture Template
Per Campus Data Capture Template
Infographic
• Incorrect data
• Delay in receiving accurate data
• Time slot which suits everyone
• Load shedding
• New power star data holder/controller
• Error on billing data
Challenges
• 3 month time frame
• Power-Star Anomalies
• Two source of data
• Building meters
Limitations
• Main group issue was communication.
• Used effective techniques which include:– Serious Creativity– Prpic’s model of reflective practice
Reflection
Questions?