1 [N.2.1.4] R&D on Energy Conservation Operation Support System for Decompressed Residual Oil Combustion Boiler (Decompressed residual oil combustion group) Yutaka Sakai, Shuichiro Natake, Tadafumi Yoshimura, Takao Adachi, Seiji Takahashi, Kenji Saito, Tatsue Miyagawa, Eikichi Takahashi 1. R&D Objectives According to a survey conducted by the Petroleum Energy Center, the availability of generated electric power, using decompressed residual oil as fuel, is about 20,000 MW maximum, on the assumption that the domestic topper capacity is 5.3 million BPSD. There are two combustion formats for decompressed residual oil: 1) the IGCC format whereby gas obtained through gasification (partial oxidation) is burnt, and 2) the BTG format, whereby fuel is burnt directly by burner. In general, the BTG format is used for heavy oil, but with decompressed residual oil, because the amount of residual carbon in the fuel is so large, the concentration of oxygen in the emissions is believed to be of higher value than during normal combustion of C heavy oil. On the other hand, because of requirements for reduction of CO 2 discharged from boilers for electric power generation, demands call for the establishment of a combustion control method in which the concentration of oxygen in emissions from the burning of decompressed residual oil by burner is reduced. In the present R&D, the objective is to conserve energy, reduce waste and secure continuous long-term operation through operational control of boilers for power generation, using decompressed residual oil as fuel. Another aim is to develop an operational support system whereby the concentration of oxygen in emissions is reduced from the present level of 2.0% to 0.5%. The benefits forecast from the present R&D are presented in Table 1. Table 1: Benefits Forecast from the Present R&D (R&D target values) Oxygen concentration in emissions: Reduced from 2.0% to 0.5% (Premises) Electric power generation format: BTG Electric power generation volume: 6,700 MW Fuel usage volume: 156 t/hr CO 2 emissions volume: 580 t/hr Electric power generating boiler specifications 350 MW/boiler 2 systems (Effects) Fuel consumption volume: Reduced 65,000 tons per year ・20,000 MW ÷ 3 ÷ (350 × 2 MW) × 156 t/h × 24 × 365 × 0.5% CO 2 emissions volume: Reduced 240,000 tons per year ・20,000 MW ÷ 3 ÷ (350 × 2 MW) × 580 t/h × 24 × 365 × 0.5%
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[N.2.1.4]
R&D on Energy Conservation Operation Support System
2.1 Creation of Emissions Forecast Formula with Combustion Test Furnace
In attempting to lower the concentration of oxygen in emissions, it is the emissions properties
that are affected the most. Given this fact, an investigation was made of methods for forecasting,
by means of a test furnace, the relationship between oxygen concentration in emissions and
emissions (NOx, dust) concentrations.
(1) Test furnace
Table 2 presents a comparison of combustion test furnace specifications with the
specifications of large-scale boiler for power generation.
Table 2: Combustion Test Furnace Specifications
Combustion test furnace Large-scale boiler
for power generation, etc.
Scale · Structure Water cooled jacket Water pipe boiler
(Evaporation) Refractory material attached (50-200 t/h)
Burner unit count 1 burner 4-12 burners
Combustion volume/burner -300 L/h 600-1200 L/h
Furnace capacity load 0.7-2.0 MJ/m3h 1.0-2.0 MJ/m
3h
Air preheating temperature Room temperature-350°C 200-300°C
Oxygen concentration in emissions 0.5-4% 1.5-2.0%
Atomizing vapor temperature 180-400°C 250-400°C
Fuel A heavy oil, heavy oil Heavy oil
(2) Identification of forecast parameters
Impacts on each emissions concentration were investigated from the standpoint of 1) fuel
properties and 2) combustion conditions, and parameters were identified.
(3) Creation of emissions forecast formula
Taking each parameter as a variable, the concentration of each emissions component was
determined by linear regression.
2.2 Dust Concentration Reduction Method
By reducing the concentration of oxygen in emissions, the concentration of dust increases as a
negative effect. The effects of combustion improver were investigated for the purpose of
reducing both the oxygen concentration in emissions and dust concentration.
2.3 Verification by Field Boiler Combustion
Concerning the applicability of the forecast formula as determined above, fuel was obtained and
verifications were made using 2 large-scale boilers for electric power generation.
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2.4 Development of Operation Support System
Corrections were made in the forecast formula based on the results of field boiler combustion
tests. A support system for operation by linear programming was developed by means of the
interval method and the direct search method.
An outline of the operation support system appears in Figure 1.
<Input>
Target value Restriction value
<Output>
Items to be changed Setting value
Operational support system
<Variable>
Nitrogen content TG residual carbon combustion speed TG residual carbon volumeOxygen concentration in emissions Furnace capacity load Furnace internal length Air preheating temperatureOxygen concentration in air, etc.
<Evaluation function>
NOx value Continuous operating time period Dust concentration (industrial waste volume)Emissions loss Combustion improver volume Operation costs, etc. F
ore
ca
st
form
ula
Figure 1: Outline of Operation Support System
3. R&D Results
3.1 Emissions Forecast Formula with Combustion Test Furnace
(1) Parameters
As a result of test furnace combustion in which fuel properties and operational conditions
were varied, it was determined that measurement concentrations of NOx and dust could be
forecast most accurately through linear regression, using the parameters given in Table 4.
The relationship between forecast values and measured values of NOx concentration and
dust concentration, by means of test furnace combustion, is illustrated in Figure 2.
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Table 4: Emissions Forecast Formula Parameters
Emissions Fuel properties Combustion conditions
Oxygen concentration in emissions
Furnace load
Air preheating temperature
NOx Nitrogen volume
Nozzle position
Oxygen concentration in emissions
Furnace load
Air preheating temperature
Nozzle position
Dust volume TG residual carbon volume
TG residual carbon
combustion speed
Stagnation time period (furnace internal length)
NO
x p
pm
(m
ea
su
red
va
lue
)
NOx ppm (forecast value)
NOx concentration
Du
st
co
nce
ntr
atio
n m
g/N
m3
(me
asu
red
va
lue
)
Dust concentration mg/Nm3 (forecast value)
Dust concentration
Figure 2: Measurement Values vs Forecast Values of NOx
Concentration and Dust Concentration Determined by
Forecast Formula
The TG residual carbon combustion speed and TG residual carbon volume given in Table
4 are values obtained from analysis of sample fuels provided, conducted by the method
shown in Figure 3, using differential thermal balance.
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Te
mp
era
ture
(°C
)
Time sec
Air volume: 100 ml/min
Speed in rising temperature: 100°C/min
Preserved temperature: 500°C
Differential thermal analysis conditions
TG residual carbon volume
We
igh
t m
g
TG residual carbon combustion speed
A × T × l n (m1/m2) / τ A; constant m1; weight of TG residual carbon final
production point m2; weight of 95% combustion point τ; (m2-m1) time period
TG residual carbon volume
Residual weight after testing
Figure 3: Volume and Combustion Speed of TG Residual Carbon