Simulator Laboratory by Serhat Beyenir & Sanja Boskovic is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.
Unless otherwise noted, this book is released under a Creative Commons Attribution (CC BY) 4.0 International license. Under the terms of the CC BY license you can freely share, copy or redistribute the material in any medium or format, or adapt the material by remixing, transforming or modifying this material providing you attribute Serhat Beyenir & Sanja Boskovic. Attribution means you must give appropriate credit to Serhat Beyenir & Sanja Boskovic as the original creator, note the CC BY license this document has been released under, and indicate if you have made any changes to the content. You may do so in any reasonable manner, but not in any way that suggests Serhat Beyenir & Sanja Boskovic endorses you or your use of this work.
To our students who taught us to be better teachers than we were many years ago.
These Simulator Laboratory Worksheets are open educational resources that align with BCIT’s Power Engineering Thermodynamics and Thermal Power Plant Simulator courses.
Open educational resources (OER) are defined as “teaching, learning, and research resources that reside in the public domain or have been released under an intellectual property license that permits their free use and re-purposing by others.” (Hewlett Foundation).
Funding for this project was provided through an OER Grant from the B.C. Open Textbook Project. The B.C. Open Textbook Project began in 2012 with the goal of making post-secondary education in British Columbia more accessible by reducing student cost through the use of openly licensed textbooks and other OER. The B.C. Open Textbook Project is administered by BCcampus and funded by the British Columbia Ministry of Advanced Education, Skills and Training and the Hewlett Foundation.
The BCcampus Writing Guidelines for Style and Tone were referenced during the copy editing and proof reading phases of this project and the Open Textbooks Theme by Brad Payne was used in producing the book.
Cover image by Gretar Ívarsson is found in the public domain.
Images of simulator user interface courtesy of Kongsberg Digital Simulation. We wish to thank Kongsberg for their continuous support.
There are certain theoretical concepts that power engineering students struggle with and there are limited number of textbooks or videos that address these concepts directly linked to the field of power engineering. When we present those challenging concepts in class we also want to make sure that our students develop safe working habits and environmental sensibilities related to sustainable operation of the power engineering equipment.
The primary purpose of this project was to design and develop simulator lab worksheets (SIM LABS) that would be used as ancillary resources for Thermodynamics and Thermal Power Plant Simulator (TPPS) courses. We have limited time to teach theory and we also have to offer practical skills to our students, so having as many SIM LABS as possible can bring those challenging concepts closer to our students and enhance their hands-on skills.
We consider this project as a first step to writing a comprehensive open textbook in the future. Through this project we aimed to
A final note to instructors who teach similar courses: We will be glad to share the “Instructor Guides and Solutions” to all SIM LABS included in this booklet. Please email us at
Sanja_Boskovic@bcit.ca or Serhat_Beyenir@bcit.ca
We owe many thanks to Dr. David Porter (former Associate Vice President) for his leadership in open education during his short tenure at BCIT albeit very impactful. We are equally indebted to BCcampus and openBCIT for co-sponsoring our project.
This was a rare project in which we did not need to disentangle any bureaucratic red tape and that was due to rare people who were involved since day one of our work. Special thanks go to James Rout (Associate Vice President), Ken Jeffery and Lin Brander (co-chairs of the OpenEd Working Group) as well as Alison Griffin, Deirdre Grace, Holly Stanley and Rosario Passos in alphabetical order. These individuals kept us motivated and we truly appreciate their friendliness in equal measures.
Also thanks to those whom we never met in person but received support within Open Grants.
And last but not least, we would like to thank our students, the entire Class of 2017 for their hard work, cooperation and feedback: Adrian Pontellini, Amar Manhas, April Derald Burias, Asmamaw Gebremariam, Brodie Pulles, Chelsea Chiao Shiun Lo, Cole Tewinkel, Darrick Cheung, Devin Hughes, Harjit Kang, Jesiah de Gouveia, John Aldana, Joshua Lewis, Kevin Hamann, Matthew Fermill, Nathan Kwong, Riley Walker, Ryan Ngun, Sean McGilp, Terence Ka Chun Pang, Tommy Yoo, Trevor Rigby, Tylar Hodson and Vangeli Asimakis.
Operate the Plant in the following modes and compute the Boiler Thermal Efficiency
First we define efficiency. There are many ways to present it, for example, efficiency is the ability to do something without wasting energy, effort or time. Put it mathematically, it is the ratio of useful output to thermal energy input. Layperson often uses the terms efficiency and effectiveness interchangeably however efficiency is to do with minimizing waste and effectiveness to do with maximizing output (more on this in Heat Exchangers Lab). Boiler efficiency is sometimes defined as combustion efficiency which is computed by the ratio of the burner’s capability to burn fuel completely to the unburnt fuel and excess air in the exhaust. Thermal efficiency on the other hand, indicates the heat exchanger’s (i.e. boiler’s) capacity to transfer heat from the combustion process to the water or steam in the boiler. In general, the maximum boiler efficiency attainable from a boiler depends on such factors as method of burning the fuel, design of the furnace and heat transfer surfaces. In addition, the type of fuel, boiler load and operational practices influence the boiler efficiency. In this lab, we focus on the fuel type, boiler load and best practices.
Next we express the Boiler Thermal Efficiency as follows:
Where energy to steam is the heat transfer required to form steam. Let,
h2=specific enthalpy of steam formed, [kJ/kg],
h1=specific enthalpy of feed water, [kJ/kg].
Because the steam is formed at constant pressure, heat transfer required to form 1 kg of steam in the boiler is
Energy to Steam= (h2-h1) [kJ]
Energy from fuel is computed from the mass of fuel used and its heat (calorific) value. For coal this is the heating value as measured in a bomb calorimeter and it corresponds to the internal energy of combustion. If
mf= mass of fuel burned in a given time
ms= mass of steam generated in the same time
HV= heat value of fuel [kJ/kg]
Energy from fuel= mf x HV [kJ]
Then we can write:
You will run 4 different initial conditions in this lab:
For each condition collect the relevant data to compute the Boiler Thermal Efficiency.
For data collection, use trends as shown below:
In addition to various pressure, temperature and flow values, you will need to log the following tags in your trends:
To calculate the enthalpy values, you may use an app or online tool such as the Superheated Steam Table: https://goo.gl/GdVM4U
For the coal operation with soot built up, use MD250 and set malfunctions as follows:
Your lab report is to include the following:
Further Reading:
Operate the Plant at the following generating capacities to compute the isentropic change in enthalpy and thermal efficiency for the HP turbine.
Recall from the First and Second Law of Thermodynamics that the adiabatic process where entropy remains constant provides the maximum energy for work. As shown on the H-S coordinates, the difference in enthalpy, (H1-H2), is maximum when the lowest enthalpy (H2) is reached at the exit conditions. The ideal expansion is, therefore, a vertical line.
On the diagram above, T1, P1 and P2 are known process variables, for example, H1 is determined by using T1 and P1. H2 then can be found drawing a vertical line from P1 to P2 by following adiabatic isentropic expansion (expansion at constant entropy).
Non-ideal processes or real processes, however, do not present straight lines as shown on the Mollier diagram due to such factors as friction. If the expansion is not isentropic (i.e. entropy is not constant but it increases), the lowest enthalpy (H2) cannot be reached at the exit conditions, in other words, H2’ > H2. This means that ΔH for the ideal expansion is greater than ΔH for the non-ideal expansion between the same pressure boundaries. The internal turbine efficiency is therefore given by:
The difference in enthalpy H2’-H2 is called the reheat factor and is the basis for multi-stage turbines. As can be seen on the Mollier diagram, the pressure curves are divergent. This means that the higher the pressure drop in a single stage turbine the greater the reheat factor and in turn the lower the turbine efficiency. However, if the steam is expanded through multiple stages and between each stage the steam is reheated, higher turbine efficiencies can be achieved. We will see this effect later in the Power Plant Efficiency lab.
You will run 3 different initial conditions in this lab:
For each condition collect the relevant data to compute the isentropic change in enthalpy for the HP turbine. Compare your results, which of the three conditions yield the most favourable results and why?
In addition to various pressure and temperature values; log the following tags in your trends:
To calculate the enthalpy values, you may use an app or online tool such as the Superheated Steam Table: https://goo.gl/GdVM4U
Your lab report is to include the following:
Further Reading:
Operate the Plant at full generating capacity and compute the Power Plant Efficiency when the plant is operating:
Excluding hydroelectric power plants, most power generating plants employ a type of boiler and steam turbine. A schematic diagram of a simple steam power plant is shown below:
High-pressure steam leaves the boiler and enters the turbine. The steam expands in the turbine and does work which enables the turbine to drive the electric generator. The exhaust steam leaves the turbine and enters the condenser where heat is transferred from the steam to cooling water. The pressure of the condensate leaving the condenser is increased in the pump thereby enabling the condensate to flow into the boiler. This thermodynamic cycle is known as the Rankine Cycle.
As noted above, some heat is always lost from the steam to cooling water. In addition, feed pumps consume energy thus reducing the net work output. Rankine Cycle Efficiency then can be expressed as:
or
referring to the diagram above and using the enthalpy values in the Rankine cycle, we can write:
If the exhaust pressure drops from P4 to P4‘ with the corresponding decrease in temperature at which heat is rejected in the condenser the net work is increased by area 1-4-4′-1′-2’-2-1 (see diagram below)
In a similar way, if the steam is superheated in the boiler, it is evident that the work is increased by area 3-3′-4′-4-3 (see diagram below):
Superheating the steam is done by increasing the time the steam is exposed to the flue gases. The result of superheating is that for a given power output, the plant using superheated steam will be of smaller size than that using dry saturated steam.
Above we noted that the efficiency of the Rankine cycle is increased by superheating the steam. If metals could be found that would allow us to reach higher temperatures, the Rankine cycle could be more efficient. To improve the efficiency, the reheat cycle has been developed which is shown schematically below:
In this cycle, the steam is expanded to some intermediate pressure in the turbine and is then reheated in the boiler, after which it expands in the low-pressure turbine to the exhaust pressure. Rankine Cycle with reheat thermal efficiency can be expressed as:
Another variation from the Rankine cycle is the regenerative cycle, which involves the use of feedwater heaters. During the process between states 2 and 2′ the feedwater is heated and the average temperature is much lower during this process than during the vaporization process 2′-3. In other words, the average temperature at which heat is supplied in the Rankine cycle is lower than in the Carnot cycle 1′-2′-3-4-1′, and consequently the efficiency of the Rankine cycle is less than that of the corresponding Carnot cycle. The relationship between Carnot cycle and Rankine cycle is shown below.
In the regenerative cycle, feedwater enters the boiler at some point between 2 and 2′. As a result, the average temperature at which heat is supplied is increased. A schematic of practical cycle is shown below:
In order to calculate the overall plant thermal efficiency, we need to adjust the formulas above to incorporate heat added in the reheater sections of the boiler:
Run the initial condition I10 230 MW_oil_auto:
In this lab, you are essentially calculating the Rankine Cycle thermal efficiency. However, you need to take the reheat cycle into consideration and log the following tags in your trends:
For Boiler Feedwater Inlet Temperature, you may use the Startup Heat Exchanger Feedwater Outlet Temperature tag#: T02447.
For the second calculation, locate the Variable List Page 0100 as shown below:
For the third calculation, make sure you closed all steam extraction valves and set T00305 to 10°C:
To calculate the enthalpy values, you may use an app or online tool such as the Superheated Steam Table: https://goo.gl/GdVM4U
Your lab report is to include the following:
Further Reading:
Operate the Plant at full generating capacity and compare the NOx emissions when the plant is operating:
Combustion of coal generates considerable quantities of byproducts, some of which are considered pollutants. The byproducts are mostly water vapor which is what we see coming out of a power plant smokestack, carbon dioxide, and nitrogen that is readily available in the air we breathe, and they do not necessarily pose any direct health hazard. However, the emissions do carry small concentrations of pollutants into the atmosphere, which translate into large quantities of hazardous emissions due to the large amount of coal combusted. The main pollutants that can cause health problems are sulfur oxides, nitrogen oxides, particulate matter (see Combustion Analysis) and such trace elements as arsenic, lead and mercury.
During the combustion process in a coal-fired power plant, nitrogen from the coal and air is converted into nitric oxide (NO) and nitrogen dioxide (NO2); these nitrogen oxides are commonly known as NOx. NOx emissions contribute to the formation of acid rain.
NOx is primarily formed by two mechanisms: thermal NOx and fuel-bound NOx.
Thermal NOx formation takes place at high flame temperatures. Formation of thermal NOx increases exponentially with combustion temperature. Fuel-bound NOx formation is dependent upon the nitrogen content of the fuel.
The best way to minimize NOx formation is to reduce flame temperature, reduce excess oxygen, and/or to burn low nitrogen-containing fuels.
The purpose of the DeNOx plant is for removal of nitrogen oxide from the flue gases. The plant employs a selective catalytic reduction method. The medium used for the reduction is ammonia gas.
The DeNOx plant includes two selective catalytic reduction (SCR) reactors and an ash silo. Various dampers channel the flue gases either into or bypass the SCR-reactors.
The DeNOx plant is highly automatic, controlled by Programmable Logic Control sequences. The sequences are S701-Purge, S702/703-Start/stop Reactors, S704/705-Heating of Reactors, S706/707-Ammonia Injection, S708/709-Product Handling and S710/711-Soot Blowing.
To reduce NOx, a quantity of additional air above all burner planes is supplied. This over-fire-air (OFA) reduces NOx by enabling richer fuel mix in the high-temperature combustion zone at the burners (two-step combustion). Approximately 10 % of the combustion air is added as OFA air. OFA controller failure (MD200 malfunction 0881) is modeled in the simulator:
To further reduce NOx generation, a portion of the secondary air is split off the main duct and directed into a third channel just above the burner. The damper controlling this over-burner-air is abbreviated OBA. OBA controller failure (MD180 malfunction 0780) is modeled in the simulator:
In the simulator, the chemical composition of the coal or other fuels can be specified. The sum of the five components C, H, S, O and N should preferably add up to 100%, to avoid confusion, but it is not strictly necessary because the C, H, S, O and N setting is always recalculated to a 100% basis prior to using in other computations. Water and inert matter (ash/slag) should then be added. The water content varies much and has a great impact on the amount of preheating required by primary air. The simulator computes the lower heat value (including water/inert matter) and theoretical combustion air needed and flue gas produced. The air/flue gas values are given in ncm/kg (ncm=normal cubic meter).
In this lab, we will burn both default and lower quality coal for a comparison. Fuel data can be changed using Variable List page 0111 on MD180, for example:
Run the initial condition I14 80% Coal and setup trends for the following variables:
G02197 X17821 G17107 X17106 D17104
T17103 C08444 G08444 G08443 C08400
Your trend windows should look like the following:
Make sure your trend printouts are labeled properly otherwise, data analysis will be very confusing.
Tabulate your data as shown below:
Percentage deviation can be expressed as
and tabulated as follows:
Your lab report is to include the following:
Further Reading:
Operate the Plant in full generating capacity and study the effect of heat exchanger surface area using the Low Pressure Feed Heater 3.
A heat exchanger is equipment in which heat exchange takes place between two working media that enter and exit at different temperatures. The main function of heat exchanger is to either remove heat from a hot working media or to add heat to the cold working media. Depending on direction of working media-fluid flow the heat exchanger is either parallel (concurrent) flow heat exchanger or counter flow heat exchanger (see Figures below).
The terms are related to how the fluid flows through their respective flow passages relative to each other. If fluids flow in the same direction such as in Figure 1 it is termed a parallel flow. If fluids flow in opposite directions as in Figure 2 it is termed counter flow.
Parallel flow in heat exchangers occurs when both fluids enter the heat exchanger at their largest temperature difference. The temperature difference becomes less over the length of the heat exchanger. In the counter flow heat exchanger, fluids enter at opposite ends and therefore at different ends of the temperature scale Figure 2. The temperature difference between two fluids is relatively constant over the length of the exchanger.
The heat transfer process that occurs in any heat exchanger can be described by the following equations.
Considering the surface area involved in heat transfer, Newton’s Law of cooling states that the rate of heat loss is proportional to the difference in temperatures between the body and its surroundings and given by,
where α is called the heat transfer coefficient [W/m2K], area is taken in m2 and ΔT is the temperature difference.
Furthermore Q, heat transferred between the hot water and cold water can be calculated as follows:
Or
where F is the correction factor which equals 1 for this SIMLAB (it takes values between 0.5 and 1). RT is the overall resistance, U, overall heat transfer coefficient and LMTD is the Log Mean Temperature Difference.
The overall resistances can be calculated using:
Heat transfer coefficients ah and ac can be calculated using the following expression for Nusselt number for hot and cold water:
For cooling
For heating
And the LMTD is given by the following correlation where 1 and 2 presents the ends of the heat exchanger:
Recall from the Boiler Efficiency Lab that efficiency is to do with minimizing waste and effectiveness to do with maximizing output. Here we define heat exchanger effectiveness as the ratio of actual heat transfer rate to the maximum possible heat transfer rate for the given temperatures.
Where Cmin is defined either by cold or hot fluid whichever is smaller and it is defined by:
Run the initial condition I10 230 MW_oil_auto and setup trends for
Heat Area Factor | C34201 |
Q | Q34228 |
Tcold1 | T24214 |
Tcold2 | T34214 |
mcold | G34213 |
Thot1 | T34204 |
Thot2 | T34227 |
mhot | G34203 |
As always, label your trends using descriptive names. In this lab, you are changing the Heat Area Factor (heat transfer coefficient x area) of LP Feed Heater 3 and comparing the temperature data. Your evaluation will be based on LMTD and Heat Exchanger Effectiveness values.
Your lab report is to include the following:
Further Reading:
Operate the Plant at 80% capacity burning coal to
In the Boiler Efficiency lab, we stated that Combustion Efficiency is defined as the ratio of the burner’s capability to burn fuel completely to the unburned fuel and excess air in the exhaust. In this lab, we will perform a combustion analysis.
Fossil fuels may be classified into solid, liquid and gaseous fuels. The vast majority of fuels are based on carbon (C), hydrogen (H2) or some combination of carbon and hydrogen called hydrocarbons.
During combustion, oxygen (O2) combines rapidly with C, H2, sulphur (S2) and their compounds in solid, liquid and gaseous fuels and results in the liberation of energy. Except for special applications such as oxyacetylene welding, in which a high-temperature flame is required, the O2 necessary for combustion is obtained from air. Air contains O2 and nitrogen (N2), plus negligible amounts of other gasses and for engineering purposes, may be considered to have the following percentage composition by mass:
O2: 23%
N2: 77%
The proportions in which the elements enter into the combustion reaction by mass are dependent upon the relative molecular weights as shown below:
Element | Symbol | Molecular Weight |
Carbon | C | 12 |
Sulphur | S2 | 32 |
Hydrogen | H2 | 2 |
Oxygen | O2 | 32 |
Nitrogen | N2 | 28 |
Complete combustion of simple hydrocarbon fuels forms carbon dioxide (C02) from the carbon and water (H20) from the hydrogen, so for a hydrocarbon fuel with the general composition CnHm, the combustion equation on a molar basis is as flows:
Where the balance should be satisfied following the moles for any mathematcial equation:
Carbon balance:
kmol CO2/ kmol fuel
Hydrogen balance:
kmol H2O/ kmol fuel
Oxygen balance:
kmol O2/ kmol fuel
Considering that combustion occurs in air rather than in pure oxygen, the nitrogen in the air may react in the combustion process to produce nitrogen oxides. Beside, some fuels contain elements other than carbon, and these elements may react with oxygen during combustion. Also, combustion is not always complete, and the exhaust gases contain unburned and partially burned products in addition to C02 and H2O.
Air is composed of oxygen, nitrogen, and small amounts of carbon dioxide, argon, and other trace components. For the purposes of the further calculation it is perfectly reasonable to consider air as a mixture of 21% (mole basis) 02 and 79 % (mole basis) N2. Nitrogen will be considered as an “inert” gas in the combustion calculations. The stoichiometric relation for complete combustion of a hydrocarbon fuel, CnHm, becomes
The balance equations are:
Carbon balance:
kmol CO2/ kmol fuel
Hydrogen balance:
kmol H2O/ kmol fuel
Oxygen balance:
kmol O2/ kmol fuel
Nitrogen balance:
kmol N2/kmol fuel
Flue gas compositions are presented in terms of mole fractions as kmol of product per kmol of fuel.
Example 1. Combustion of Octane in Air
Determine the stoichiometric air/ fuel mass ratio and product gas composition for combustion of octane ( C8H18) in air.
Carbon balance:
kmol CO2/ kmol fuel
Hydrogen balance:
kmol H2O/ kmol fuel
Oxygen balance:
kmol O2/ kmol fuel
Nitrogen balance:
kmol N2/kmol fuel
The combustion equation becomes:
Air/ fuel mass based ratio considering that 1 kmol fuel is 114 kg of fuel ( 8*12 + 18 *(1) = 114):
Flue gas composition on molar basis is:
Total number of kmol of flue gasses = kmol CO2 + kmol H2O + kmol N2 = 8 +9+ 47 = 64 kmol flue gasses/ kmol fuel
CO2 = 8/64 = 12.5 %
H2O = 9/64 = 14 %
N2 = 47/64 = 73.5%
Other components and impurities in the fuel make the calculation process more complicated. For example if sulfur exists in fuel it is usually combust into sulfur dioxide (SO2). Ash, the noncombustible inorganic (mineral) impurities in the fuel, undergoes a number of transformations at combustion temperatures, will be neglected in the further calculation (ash will be assumed to be inert).
For most solid and liquid fuels, the chemical composition is on a mass basis, as determined in the ultimate analysis.
The combustion reactions are written following the stoichiometric rules as defined above. The quantity of matter entering into a reaction is equal to the quantity of matter in the products of the reaction.
The reaction for the complete combustion of C may be written as follows:
C+O2=CO2
or, if molecular weights are used,
12+32=44
1 kg C + 2⅔ kg O2 = 3⅔ kg CO2
The complete combustion of H2 occurs as follows:
2H2 +O2 =2H2O
4+32=36
1 kg H2 + 8 kg O2 = 9 kg H2O
Sulphur burns as follows:
S +O2 =SO2
32+32=64
1 kg S + 1 kg O2 = 2 kg SO2
In addition, 1 kg of O2 (stoichiometric mass of O2) is contained in 1/0.232=4.3 kg air which is the stoichiometric mass of air. This air will contain 4.3-1=3.3 kg N2. Therefore we can write:
1 kg S + 4.3 kg air = 2 kg SO2+3.3 kg N2
If the analysis of fuel is given by mass, follow the steps below:
Run the initial condition I14 80% Coal and setup trends for the following variables:
X00820 X00821 X00822 X00823 X00824 E23356
G02196 G02197 X32419 X02419 G00831 H00830
In this lab, you are carrying out two combustion analyses. For data collection, set up your trends, a sample trend plot is shown below (Make sure your trend printouts are labeled properly otherwise, data analysis will be very confusing):
To change the fuel composition use the Variable List Page#: 0111 on MD180:
Your lab report is to include the following:
Further Reading:
Version 0.7 – December 6, 2017 (Additional copy editing and proof reading)
Version 0.6 – September 22, 2017 (Guest-lecturing at Kalmar Maritime Academy, Sweden)
Version 0.5 – March 28, 2017 (BCIT OpenEd Week presentation)
Version 0.4 – March 1, 2017 (Second Sprint event with our students)
Version 0.3 – February 1, 2017 (First Sprint event with our students)
Version 0.2 – December 19, 2016 (First draft)
Version 0.1 – November 3, 2016 (Initial development)