ERGY8071 RETScreen Assignment 2 G-3
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School
Conestoga College *
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Course
8090
Subject
Industrial Engineering
Date
Feb 20, 2024
Type
docx
Pages
9
Uploaded by DeanCaterpillar3662
Assignment #2
ERGY8071
ERGY8071 Assignment 2: Calculating Energy Savings Using a RETScreen Regression Model
Name
Student #
Student #1
Hemali Gohil
8886726
Student #2
Pavankumar Mukeshbhai Nishad
8910301
Student #3
Mohammed Taha Shahezan
8955178
Student #4
Student #5
Your Marks
Maximum Possible Marks
Grade
15
Instructions:
The assignment can be completed individually or in groups of up to 5 students. This assignment is a continuation of Assignment #1. The same grocery store in Southwestern Ontario (assuming London, ON) weather data installed a refrigeration energy conservation measure (ECM).
On eConestoga, you will be provided with post energy conservation measure (ECM) installation electricity and gas data (ERGY8070 RETScreen Assignment Post Data.xlsx). using your current RETScreen expert file complete the following tasks:
1.
Starting with RETScreen’s “Enter Data” button, import the post electricity and gas data into the provided RETScreen file and append it to the existing Baseline Electricity and Gas Consumption data.
IMPORTANT: When importing the post data it is important that the import method of “append” be selected instead of “clear and replace”. Further instructions and screenshots are below.
2.
Using the existing Electricity Consumption, Electric Power and Gas Consumption regression models in your RETScreen file, create CUSUM charts.
Instructions for importing and adding Post Data to the existing Electricity Consumption Data:
In RETScreen:
Data tab => Enter Data
Import
Import method => Choose “Append data” (do NOT choose “Clear and replace”, it will replace existing data)
Green Check
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ERGY8071
Next Screen => Check Dates (begin & end) => Column A Pick End Date => At bottom enter Start Date.
Green Check
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Part 1: Electricity Consumption Regression Model Savings Results (kWh)
1.
Insert Your kWh CUSUM Graph Below (1 marks)
2.
Insert Your kWh M&V Chart Below
(1 marks)
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Assignment #2
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3.
Insert Your kWh Data (Actual & Predicted) Table Below
(1 marks)
Assignment #2
ERGY8071
Part 2: Electricity Power Regression Model Savings Results (kW)
1.
Insert Your kW CUSUM Graph Below (1 marks)
2.
Insert Your kW M&V Chart Below
(1 marks)
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ERGY8071
3.
Insert Your kW Data (Actual & Predicted) Table Below
(1 mark)
Part 3: Gas Consumption Regression Results (kW)
1.
Insert Your Gas Consumption CUSUM Graph Below (1 marks)
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Assignment #2
ERGY8071
2.
Insert Your Gas Data (Actual & Predicted) Table Below
(1 mark)
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Part 4: Results Analysis
In full sentences, answer the following questions. Show your work when necessary:
1.
What commissioning date did you pick for the ECM installation and why? (2 marks)
01-01-2019. On this date , the total difference between actual and predicted energy consumption is zero, where the graph's slope starts to decline. This downward slope indicates a negative usage of energy, suggesting that the shop began using less energy than predicted. This change strongly implies the implementation of an ECM from this date.
2.
What are the annual energy (kWh) savings (i.e. first 12 months after the commissioning date) of this ECM? (1 mark)
5,59,822 kwh
3.
What are the average monthly demand (kW) savings of this ECM? (1 mark)
1013/12 = 84.41 KW
4.
Assuming a blended electricity rate of $0.15/kWh, what is the annual electricity cost savings of this ECM over the first 12 months since the commissioning date? (1 mark)
Annual electricity cost =Annual savings * blended rate
559822 * 0.15 = $ 83,973.3
5.
This ECM was a refrigeration upgrade that cost the grocery store $450,000. What is the simple payback of this ECM? (1 mark)
Simple Payback Period = Cost of new installation / annual energy cost savings due to new system
= 450,000/$ 83,973.3 =
5.35 years
6.
What observations can you make from the gas CUSUM? What are some possible explanations for the gas CUSUM trend (2 marks)
Assignment #2
ERGY8071
The line on the graph goes down and then up after changes made, a link between how much gas used and the weather. In winter, when the weather is colder, more gas is used
to heat the store, so the line goes up. But in summer, not much gas needed for heating, so the line goes down. Even though things upgraded to save energy, it didn't really change how much gas used for heating in the store. When it was colder than usual in the last part of 2020, more gas used than expected.
[Hint: consider the time of year]
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