Methodology for Selecting the Dataset
A comprehensive assessment was undertaken to assess the datasets for 2019 and 2020, to conclude which dataset to use to understand the demand of the current system and subsequently size the demand of the proposed scenarios. This analysis involved reviewing half hourly data for the CHP, three boilers and the district heating (system after losses). The half hourly datasets are taken from an excel workbook of cumulative meter readings from within the energy centre. (Charles, 2021). To increase robustness of the technical assessment it is essential to use the fullest dataset, figure 1 shows the process of cross checking the datasets. Initially, concern was arisen as to the 2020 datasets not showing an accurate representation due to the COVID-19 pandemic reducing campus occupancy, however concerns were alleviated due to assurance that the CHP and boilers functioned as usual throughout the year. It was found that , 2020 database is more reliable than 2019 as large data losses occurred throughout 2019 – most likely due to malfunction of the reading meters.
Figure 1- Pathway to selecting the most robust dataset to use for calculation throughout the project. Data from the year 2020 is more reliable.
Monthly natural gas consumption invoices were provided (Vital Energi, 2020). The monthly invoices were analysed for 2020 and cross checked with the excel meter reading database (Charles, 2021) for the CHP, Boiler 1, Boiler 2 and Boiler 3. The bar chart illustrated in figure 2 indicates there is a large discrepancy within the month of July.
Figure 2 - Graph Detailing the percentage deviation between the Invoices (Vital Energi, 2020) and meter readings (Charles, 2021). Highlighting large deviations in July.
A detailed analysis for the CHP and the three boilers, were broken down separately month by month to show the deviation between meter readings and invoices. Through this breakdown it is pinpointed the major deviation occurs within July, for boiler 1. Table 1 details the breakdown for boiler 1, this deviation is assumed to be the result of a faulty meter.
Table 1 - Month by Month (in year 2020) breakdown comparison of the kWh thermal output from the meter reading, compared with the invoices for Boiler 1. A 100% deviation ocurred between the meter reading and invoice in July.
Due to inaccuracy and missing data within the meter readings provided, it is concluded that the invoice data for the year 2020 is the most robust data to use to calculate the size of heat pumps and/or amount of hydrogen fuel needed for scenario 1, 2 and 3.
Software appraisal
When embarking on the project it was important to consider the software we would use to undertake the analysis of the 3 proposed systems. The key criteria taken into consideration for selecting software were;
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Whether CHP operation can be carried out through that software
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License affordability / accessibility
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User friendliness
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Clarity of the analysis output
SUMMARY OF SOFTWARES CONSIDERED
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energyPRO – Energy PRO is a developed by EDM International; a Denmark based company. Energy pro is a software developed for CHP analysis. It is quite user friendly and affordable.
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Design Builder - Design builder is the most user-friendly energy software. It offers some CHP outputs however has more of a green building focus. It is also relatively expensive.
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HomerPro- This software is US based, the new version has some hydrogen compatible components. It is affordable for students. Homer pro is more functional for cost analysis, compared to technical aspects.
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TRANSYS – A US based software. It is best used in building modelling and simulation software for projects such as green buildings. However, there are some CHP options although not to the extent that energyPRO offers. This software is too expensive.
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Microsoft Excel- It is not an energy analysis software, but the open source nature means it can be used to do manual energy analysis with formulas, building an analysis tool specific to the project.
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AutoCAD – Useful for laying the various routes for the water source heat pump piping and trenching throughout the city centre of Glasgow.
SELECTION OF SOFTWARE
Figure 3 - Comparison of Accessibility and Suitability of the 7 software considered for use within the project.
Based upon analysis, shown by the software comparison in figure 3 it was found that Excel would be the most applicable software and is used to form the bulk of the project assessment, with use of energyPRO to validate calculations within the hydrogen and electrolysis aspects of the project. AutoCAD is also used within aspects of the WSHP scenario, when planning routes for piping between the River and the Campus.
Methodology for Sizing Scenario 1
When considering sizing the heat pump, first the river properties must be understood. Calculations were undertaken to understand the amount of heat available to take from the river, alongside understanding the flow rate of the river, then the size of heat pump can be determined.
The steps to sizing scenario 1 were as follows;
ONE - Analysis of the demand data provided by the Estate’s team at the University was undertaken. This allowed us to decide upon a Design Day which the WSHP system would be designed to supply.
TWO - The properties of the river Clyde were obtained through SEPA and the NRFA to be analysed. A reliable flow rate that is available almost 100% of the time was selected, taking into consideration any abstraction limits or regulations. Analysis of the water temperature is also necessary to ensure the likelihood of the system freezing is rare.
THREE - From the river properties, the amount of heat available from the river is determined using the following equation:
𝑄 = 𝑚̇ 𝜌 𝐶𝑝 ∆𝑇
Where
𝑄 = the heat which is drawn into the heat pump.
𝑚̇ = the mass flow of water (0.8m3/s).
𝜌 = the density of the fluid water (1000kg/m3).
𝐶𝑝 = the heat capacity of the water (4200 J/kgK).
∆𝑇 = the temperature difference between the water entering and exiting the heat pump (3°C).
FOUR - Sizing and optimisation of the heat pumps and thermal store to meet the demand of the university.
For each heat pump added to the system the following calculation is undertaken to determine the percentage of annual heating demand met by that heat pump:
𝑃. 𝐻. 𝑃. (%) = Number of half-hours demand is required/17520 (number of half hours in year) x 100
FIVE - Sizing of a thermal store was undertaken to allow the heat pumps to provide a steady output at a smaller size. This was calculated using the following equation obtained from CIBSE Guide B1: Heating (CIBSE, 2016):
Where
M: Mass of the stored water
Cp= 4.18 kJ/kgK
Θws – Θw1 = 30° C
Trec= 3600s
Φ= 7MW
SIX- The diameter of the pipes required to transport the river water from the river to the heat pumps was calculated using the following equation:
Where
d= pipe diameter
Q = flow rate
v= Velocity
The circulation pump based at the river was determined via manufacturer's websites and relies on the flow rate and pressure head.
Methodology for Sizing Scenario 2
The current system uses natural gas as fuel. In order to calculate the hydrogen demand, the thermal output for the CHP and the 3 boilers of the current system is used. The thermal output value is firstly converted from kWh to MJ. Once the value is found in MJ, it is then divided by the lower heating value for hydrogen which is 119.96 MJ/kg.
In order to validate results, three different methods of approach to calculate the mass of hydrogen required within the system were used. To illustrate validation, the H2 average daily usage for boiler 2, in January was calculated by all three methods.
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The given data from Invoice (Vital Energi, 2020); Total Energy output for month of January = 886240 kWh thermal.
METHOD 1
METHOD 2
METHOD 3
Method 3 was used throughout the project to size Scenario 2, with regards to calculating the Hydrogen demand. Please refer to excel download "Hydrogen Excel Model" for in depth analysis.
Methodology quantifying number of truck deliveries of hydrogen
Once the demand of hydrogen was calculated, calculating the source of hydrogen was next considered. Firstly for truck delivery.
The hydrogen demands for the CHP and 3 boilers were calculated for every single half hour increment of 2020 data. This was then used to give an approximate monthly and daily need of hydrogen. Three types of trucks, with varied capacities to transport quantities of hydrogen gas; 900 kg, 600 kg and 300 kg (Brown, 2019) were found.
Methodology sizing Electrolyser to produce hydrogen onsite
Another pathway considered was producing the hydrogen onsite via electrolysis. The method used to size the electrolyser is as follows;
Step 1) Convert Peak Energy demand of system from MWh to kWh
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Peak Energy Demand = 15.7 MWh
Step 2) Calculate the peak demand in an hour
The average hydrogen demand is 132 kg per hour, peak demand 471kg per hour. Nel M4000 electrolysis unit (Nel, 2021) has been selected, due to the production rate almost meeting the peak hourly demand of Hydrogen. The electrolyser’s hydrogen production rate is 372 kg/hr, this is 99kg less than the peak hydrogen demands, this has led to the requirement of installation of a buffer tank, to supply the additional demand of Hydrogen within Peak hours.
Methodology Sizing Hydrogen Storage Tank
Step 1) Hydrogen storage was sized using the following equation to hold the capacity of hydrogen equivalent to that of three hours of peak demand:
Step 2) Converting the mass to volume, as when hydrogen is pressurised, density must be considered. Density and Pressure have a directly proportional relationship. An assumption is made that the pressure of the storage tank is 700 bar (Mazzoli, 2005), giving a density of 42 kg/m3.
Step 3) Sizing the tank dimensions.
As both the radius and height of the tank are unknown variables, an assumption was made that the height of the tank would be 2.5m.
The calculated radius using the above equation, within excel is 2.5m. Giving a spherical tank with dimensions h=2.5m and r=2.5m. Please refer to excel sheet download “Hydrogen Excel Model” for detailed analysis and sizing of tank.
Methodology quantifying oxygen / hydrogen produced by electrolyser
The Nel production rate, for an efficiency of 62% is known to be 372 kg of O2 per hour. The oxygen produced in the system is calculated as shown:
The water needed to produce the 372kg of hydrogen and 186 kg of oxygen per hour is calculated as shown:
Methodology for Sizing Scenario 3
The combined WSHP and hydrogen fuelled CHP scenario required a two step sizing, for both technologies of the system. The steps undertaken were similar of those used in methodology for scenario 1 and 2;
ONE- Sizing of the electrolyser is carried over from scenario 2 as WSHPs are replacing the boilers for the third scenario.
TWO- Following the same principles outlined in the methodology for scenario 1, sizing and optimisation of heat pumps and thermal storage is undertaken to meet the demand of the university alongside the hydrogen fuelled CHP.
Methodology for Calculating CO2e- Savings
The Scottish government had a goal for 2018 for the electricity grid to reduce its emissions factor to 0.05 kgCO2e/kWh. (Anandarajah and McDowall, 2012) With considerations of the advancements in Renewable Electricity generation in Scotland in the recent year, an assumption has been made for this report that this target was met, and surpassed to an assumed Emissions factor of 0.03 kgCO2e/kWh in Scotland in the year 2021.
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The current System was considered using the natural gas emission factor 0.18 kgCO2e/kWh. (Department for Business, Energy & Industrial Strategy, 2019)
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Scenario 1 was considered using the electricity grid factor of 0.03 kgCO2e/kWh
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Scenario 2 was considered using the electricity grid factor of 0.03 kgCO2e/kWh for the electrolyser consumption and the hydrogen combustion emission factor 0 kgCO2e/kWh
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Scenario 3 was considered using the electricity grid factor of 0.03 kgCO2e/kWh for electrical consumption of the electrolyser and of the Heat Pumps.
The carbon dioxide emissions for each of the scenarios were calculated, by using the energy output in kWh of electricity and/ or hydrogen fuel used within the proposed systems and multiplying by the applicable CO2 Emissions Factor.
Example of the methodology used;
CURRENT SYSTEM
The kWh output of natural gas consumed in 2020 = 85573725 kWh (Vital Energi, 2020)
SCENARIO 1
The calculated kWh output of electricity consumed in a year = 26300000 kWh
SAVINGS BY SWITCHING TO SCENARIO 1
The same methodology was applied with the criteria relevant for each scenario as detailed above.