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ENERGY CONSUMPTION
OF LOW-LAND BASED
RICE PRODUCTION IN
DAVAO DEL NORTE
JOSSEL BALALA
SHEILA COGAY
BACKGROUND OF THE STUDY
 Rice is a staple food for over 50% of the world’s population Rice consumption increases with the
population. (Kubo and Purevdoj, 2004)
 FAO reported that worldwide rice production is currently expanding by 1.3%—slightly less than the
1.9% growth rate between 1984 and 1994. (FAO, 2000)
 IRRI studied the food problem in relation to world population, and they predict that 800 million tons
of rice will be required in 2025. (IRRI, 2000)
 Crop-yield is directly proportional to the energy input (Srivastava, 1982).
 Boosting crop yield will combat the rapidly growing world population and consumption. Thus,
energy planning is crucial and requires a comprehensive analysis of energy inputs and outputs.
(Khan et al., 2009)
 Philippine rice sufficiency ratio declined from 91.95 of 2014 to 88.93 of 2015. (Philippine Statistics
Authority, 2017)
 Davao del Norte palay production in 2013 slid to 421,692 metric tons, lower by 6.02 percent from
the 2012 level. Area harvested at 103,294 hectares trimmed down slightly by 0.67 percent. Palay
yield, at 4.08 metric tons per hectare, dropped by 5.38%. (Philippine Statistics Authority, 2017)
10/2/2022 2
BACKGROUND OF THE STUDY
 Fuel and fertilizers (N and P) account for the largest share (>75%) of all energy
expenditures in a mixed cropping system (Hetz, 1992; Ahmad, 1994; Safa and
Tabatabaeefar, 2002).
 In Thailand, the largest energy share is agricultural machinery (62.15%), following by
fuel (19.64%), fertilizer (20%), seeds, chemical and labor. (Chaichana, 2014)
 In Malaysia, highest energy consumption is tillage (48.6%), harvesting (32.6%),
planting (15.7%). (Bockari-Gevao, SM., et al., 200%)
 In Iran, highest energy input is water (38.84%), electricity (27.87%), nitrogen fertilizer
(17.5%)
10/2/2022 3
SIGNIFICANCE OF THE STUDY
 The study will help the researcher better understand the scope and activities
associated with rice farming in the province of Davao del Norte.
 It will allow the researcher to test the cost efficiencies of rice farming and provide
relevant information and assistance to farmers to develop their practices and attain
productivity at the most economical way to become more globally competitive and
sustainable business.
10/2/2022 4
OBJECTIVE OF THE STUDY
 To estimate the energy usage of agricultural machinery in Davao del Norte by major
field operation such as tillage, planting, harvest and transport.
 To quantify machinery use in terms of a mechanical index, energy
required/available, fuel consumption and cost per hectare.
 To compare the results across municipalities and address questions about potential
future changes in machinery use.
 To determine appropriate/potential energy savings of the current practices.
 To perform a basic economic analysis.
10/2/2022 5
METHODOLOGY
 Data were collected from municipalities of
Davao del Norte with one (1) hectare and
above land holdings. Three respondents
were selected to represent each
municipalities.
 A pre-designed survey questionnaire were
circulated.
 Rice production process was divided as land
preparation, planting, crop care and maintenance,
harvesting and post harvest process.
 Production factors were labor, machinery, diesel
(direct) and seeds, fertilizers, chemical, water
(indirect)
10/2/2022 6
Energy Computation
10/2/2022 7
Energy Coefficients Energy Indices
Mechanization Index
Sample of Questionnaire
10/2/2022 8
Sample of Questionnaire
10/2/2022 9
RESULT AND DISCUSSION
10/2/2022 10
RESULT AND DISCUSSION
10/2/2022 11
RESULT AND DISCUSSION
10/2/2022 12
RESULT AND DISCUSSION
10/2/2022 13
𝐸𝑛𝑒𝑟𝑔𝑦 𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 =
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡
=
71433 𝑀𝐽/ℎ𝑎
9913.6𝑀𝐽/ℎ𝑎
= 7.21
𝐸𝑛𝑒𝑟𝑔𝑦 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 =
𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡
=
4903 𝑘𝑔/ℎ𝑎
9913 𝑀𝐽/ℎ𝑎
= 0.49 𝑘𝑔/𝑀𝐽
𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝐸𝑛𝑒𝑟𝑔𝑦 =
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡
𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑
=
9913 𝑀𝐽/ℎ𝑎
4903 𝑘𝑔/ℎ𝑎
= 2.02𝑀𝐽/𝑘𝑔
𝑊𝑎𝑡𝑒𝑟 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 =
𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑
𝐴𝑚𝑡 𝑤𝑎𝑡𝑒𝑟 𝑎𝑝𝑝𝑙𝑖𝑒𝑑
=
4903 𝑘𝑔/ℎ𝑎
1219.2 𝑚3/ℎ𝑎
= 4.02𝑘𝑔/𝑚3
𝑁𝑒𝑡 𝐸𝑛𝑒𝑟𝑔𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡 − 𝑖𝑛𝑝𝑢𝑡 = 71433
𝑀𝐽
ℎ𝑎
− 9913
𝑀𝐽
ℎ𝑎
= 61519 𝑀𝐽/ℎ𝑎
RESULT AND DISCUSSION
10/2/2022 14
RESULT AND DISCUSSION
10/2/2022 15
𝐸𝑛𝑒𝑟𝑔𝑦 𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 =
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡
=
70179 MJ/ha
13528.4𝑀𝐽/ℎ𝑎
= 5.19
𝐸𝑛𝑒𝑟𝑔𝑦 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 =
𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡
=
4817 kg/ha
13528.4𝑀𝐽/ℎ𝑎
= 0.36 𝑘𝑔/𝑀𝐽
𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝐸𝑛𝑒𝑟𝑔𝑦 =
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡
𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑
=
13528.4 𝑀𝐽/ℎ𝑎
4817 𝑘𝑔/ℎ𝑎
= 2.81 𝑀𝐽/𝑘𝑔
𝑊𝑎𝑡𝑒𝑟 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 =
𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑
𝐴𝑚𝑡 𝑤𝑎𝑡𝑒𝑟 𝑎𝑝𝑝𝑙𝑖𝑒𝑑
=
4817 𝑘𝑔/ℎ𝑎
2289.6 𝑚3/ℎ𝑎
= 2.10 𝑘𝑔/𝑚3
𝑁𝑒𝑡 𝐸𝑛𝑒𝑟𝑔𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡 − 𝑖𝑛𝑝𝑢𝑡 = 70179
𝑀𝐽
ℎ𝑎
− 13528.4
𝑀𝐽
ℎ𝑎
= 56650.6 𝑀𝐽/ℎ𝑎
RESULT AND DISCUSSION
10/2/2022 16
RESULT AND DISCUSSION
10/2/2022 17
𝐸𝑛𝑒𝑟𝑔𝑦 𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 =
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡
=
64070 𝑀𝐽/ℎ𝑎
8474 𝑀𝐽/ℎ𝑎
= 7.56
𝐸𝑛𝑒𝑟𝑔𝑦 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 =
𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡
=
4397 𝑘𝑔/ℎ𝑎
8474 𝑀𝐽/ℎ𝑎
= 0.52 𝑘𝑔/𝑀𝐽
𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝐸𝑛𝑒𝑟𝑔𝑦 =
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡
𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑
=
8474 𝑀𝐽/ℎ𝑎
4397 𝑘𝑔/ℎ𝑎
= 1.93 𝑀𝐽/𝑘𝑔
𝑊𝑎𝑡𝑒𝑟 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 =
𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑
𝐴𝑚𝑡 𝑤𝑎𝑡𝑒𝑟 𝑎𝑝𝑝𝑙𝑖𝑒𝑑
=
4397 𝑘𝑔/ℎ𝑎
1774.44 𝑚3/ℎ𝑎
= 2.48 𝑘𝑔/𝑚3
𝑁𝑒𝑡 𝐸𝑛𝑒𝑟𝑔𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡 − 𝑖𝑛𝑝𝑢𝑡 = 64070
𝑀𝐽
ℎ𝑎
− 8474
𝑀𝐽
ℎ𝑎
= 55596 𝑀𝐽/ℎ𝑎
RESULT AND DISCUSSION
10/2/2022 18
RESULT AND DISCUSSION
10/2/2022 19
𝐸𝑛𝑒𝑟𝑔𝑦 𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 =
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡
=
55366 𝑀𝐽/ℎ𝑎
7357.4 𝑀𝐽/ℎ𝑎
= 7.53
𝐸𝑛𝑒𝑟𝑔𝑦 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 =
𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡
=
3800 𝑘𝑔/ℎ𝑎
7357.4 𝑀𝐽/ℎ𝑎
= 0.52 𝑘𝑔/𝑀𝐽
𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝐸𝑛𝑒𝑟𝑔𝑦 =
𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡
𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑
=
7357.4 𝑀𝐽/ℎ𝑎
3800 𝑘𝑔/ℎ𝑎
= 1.94 𝑀𝐽/𝑘𝑔
𝑊𝑎𝑡𝑒𝑟 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 =
𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑
𝐴𝑚𝑡 𝑤𝑎𝑡𝑒𝑟 𝑎𝑝𝑝𝑙𝑖𝑒𝑑
=
3800 𝑘𝑔/ℎ𝑎
1030.32 𝑚3/ℎ𝑎
= 3.69𝑘𝑔/𝑚3
𝑁𝑒𝑡 𝐸𝑛𝑒𝑟𝑔𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡 − 𝑖𝑛𝑝𝑢𝑡 = 55366
𝑀𝐽
ℎ𝑎
− 7357.4
𝑀𝐽
ℎ𝑎
= 48009 𝑀𝐽/ℎ𝑎
RESULT AND DISCUSSION
10/2/2022 20
𝑀𝐸 𝐴𝑠𝑢𝑛𝑐𝑖𝑜𝑛 =
𝐿𝑀
𝐿𝑀 + 𝐿𝐻
=
0.2 374
0.2 374 + 0.1(366)
= 67.15%
𝑀𝐸 𝐶𝑎𝑟𝑚𝑒𝑛 =
𝐿𝑀
𝐿𝑀 + 𝐿𝐻
=
0.2 1012
0.2 1012 + 0.1(1313)
= 60.65%
𝑀𝐸 𝑁𝑒𝑤 𝐶𝑜𝑟 =
𝐿𝑀
𝐿𝑀 + 𝐿𝐻
=
0.2 1701
0.2 1701 + 0.1(1225)
= 73.52%
𝑀𝐸 𝑆𝑡𝑜. 𝑇𝑜𝑚𝑎𝑠 =
𝐿𝑀
𝐿𝑀 + 𝐿𝐻
=
0.2 2143
0.2 2143 + 0.1(1797)
= 70.46%
RESULT AND DISCUSSION
10/2/2022 21
ECONOMIC ANALYSIS – SEE EXCEL FILE
10/2/2022 22

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6_Energy consumption in low-land based rice production in.pptx

  • 1. ENERGY CONSUMPTION OF LOW-LAND BASED RICE PRODUCTION IN DAVAO DEL NORTE JOSSEL BALALA SHEILA COGAY
  • 2. BACKGROUND OF THE STUDY  Rice is a staple food for over 50% of the world’s population Rice consumption increases with the population. (Kubo and Purevdoj, 2004)  FAO reported that worldwide rice production is currently expanding by 1.3%—slightly less than the 1.9% growth rate between 1984 and 1994. (FAO, 2000)  IRRI studied the food problem in relation to world population, and they predict that 800 million tons of rice will be required in 2025. (IRRI, 2000)  Crop-yield is directly proportional to the energy input (Srivastava, 1982).  Boosting crop yield will combat the rapidly growing world population and consumption. Thus, energy planning is crucial and requires a comprehensive analysis of energy inputs and outputs. (Khan et al., 2009)  Philippine rice sufficiency ratio declined from 91.95 of 2014 to 88.93 of 2015. (Philippine Statistics Authority, 2017)  Davao del Norte palay production in 2013 slid to 421,692 metric tons, lower by 6.02 percent from the 2012 level. Area harvested at 103,294 hectares trimmed down slightly by 0.67 percent. Palay yield, at 4.08 metric tons per hectare, dropped by 5.38%. (Philippine Statistics Authority, 2017) 10/2/2022 2
  • 3. BACKGROUND OF THE STUDY  Fuel and fertilizers (N and P) account for the largest share (>75%) of all energy expenditures in a mixed cropping system (Hetz, 1992; Ahmad, 1994; Safa and Tabatabaeefar, 2002).  In Thailand, the largest energy share is agricultural machinery (62.15%), following by fuel (19.64%), fertilizer (20%), seeds, chemical and labor. (Chaichana, 2014)  In Malaysia, highest energy consumption is tillage (48.6%), harvesting (32.6%), planting (15.7%). (Bockari-Gevao, SM., et al., 200%)  In Iran, highest energy input is water (38.84%), electricity (27.87%), nitrogen fertilizer (17.5%) 10/2/2022 3
  • 4. SIGNIFICANCE OF THE STUDY  The study will help the researcher better understand the scope and activities associated with rice farming in the province of Davao del Norte.  It will allow the researcher to test the cost efficiencies of rice farming and provide relevant information and assistance to farmers to develop their practices and attain productivity at the most economical way to become more globally competitive and sustainable business. 10/2/2022 4
  • 5. OBJECTIVE OF THE STUDY  To estimate the energy usage of agricultural machinery in Davao del Norte by major field operation such as tillage, planting, harvest and transport.  To quantify machinery use in terms of a mechanical index, energy required/available, fuel consumption and cost per hectare.  To compare the results across municipalities and address questions about potential future changes in machinery use.  To determine appropriate/potential energy savings of the current practices.  To perform a basic economic analysis. 10/2/2022 5
  • 6. METHODOLOGY  Data were collected from municipalities of Davao del Norte with one (1) hectare and above land holdings. Three respondents were selected to represent each municipalities.  A pre-designed survey questionnaire were circulated.  Rice production process was divided as land preparation, planting, crop care and maintenance, harvesting and post harvest process.  Production factors were labor, machinery, diesel (direct) and seeds, fertilizers, chemical, water (indirect) 10/2/2022 6
  • 7. Energy Computation 10/2/2022 7 Energy Coefficients Energy Indices Mechanization Index
  • 13. RESULT AND DISCUSSION 10/2/2022 13 𝐸𝑛𝑒𝑟𝑔𝑦 𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡 = 71433 𝑀𝐽/ℎ𝑎 9913.6𝑀𝐽/ℎ𝑎 = 7.21 𝐸𝑛𝑒𝑟𝑔𝑦 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 = 𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡 = 4903 𝑘𝑔/ℎ𝑎 9913 𝑀𝐽/ℎ𝑎 = 0.49 𝑘𝑔/𝑀𝐽 𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝐸𝑛𝑒𝑟𝑔𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡 𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑 = 9913 𝑀𝐽/ℎ𝑎 4903 𝑘𝑔/ℎ𝑎 = 2.02𝑀𝐽/𝑘𝑔 𝑊𝑎𝑡𝑒𝑟 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 = 𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑 𝐴𝑚𝑡 𝑤𝑎𝑡𝑒𝑟 𝑎𝑝𝑝𝑙𝑖𝑒𝑑 = 4903 𝑘𝑔/ℎ𝑎 1219.2 𝑚3/ℎ𝑎 = 4.02𝑘𝑔/𝑚3 𝑁𝑒𝑡 𝐸𝑛𝑒𝑟𝑔𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡 − 𝑖𝑛𝑝𝑢𝑡 = 71433 𝑀𝐽 ℎ𝑎 − 9913 𝑀𝐽 ℎ𝑎 = 61519 𝑀𝐽/ℎ𝑎
  • 15. RESULT AND DISCUSSION 10/2/2022 15 𝐸𝑛𝑒𝑟𝑔𝑦 𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡 = 70179 MJ/ha 13528.4𝑀𝐽/ℎ𝑎 = 5.19 𝐸𝑛𝑒𝑟𝑔𝑦 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 = 𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡 = 4817 kg/ha 13528.4𝑀𝐽/ℎ𝑎 = 0.36 𝑘𝑔/𝑀𝐽 𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝐸𝑛𝑒𝑟𝑔𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡 𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑 = 13528.4 𝑀𝐽/ℎ𝑎 4817 𝑘𝑔/ℎ𝑎 = 2.81 𝑀𝐽/𝑘𝑔 𝑊𝑎𝑡𝑒𝑟 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 = 𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑 𝐴𝑚𝑡 𝑤𝑎𝑡𝑒𝑟 𝑎𝑝𝑝𝑙𝑖𝑒𝑑 = 4817 𝑘𝑔/ℎ𝑎 2289.6 𝑚3/ℎ𝑎 = 2.10 𝑘𝑔/𝑚3 𝑁𝑒𝑡 𝐸𝑛𝑒𝑟𝑔𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡 − 𝑖𝑛𝑝𝑢𝑡 = 70179 𝑀𝐽 ℎ𝑎 − 13528.4 𝑀𝐽 ℎ𝑎 = 56650.6 𝑀𝐽/ℎ𝑎
  • 17. RESULT AND DISCUSSION 10/2/2022 17 𝐸𝑛𝑒𝑟𝑔𝑦 𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡 = 64070 𝑀𝐽/ℎ𝑎 8474 𝑀𝐽/ℎ𝑎 = 7.56 𝐸𝑛𝑒𝑟𝑔𝑦 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 = 𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡 = 4397 𝑘𝑔/ℎ𝑎 8474 𝑀𝐽/ℎ𝑎 = 0.52 𝑘𝑔/𝑀𝐽 𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝐸𝑛𝑒𝑟𝑔𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡 𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑 = 8474 𝑀𝐽/ℎ𝑎 4397 𝑘𝑔/ℎ𝑎 = 1.93 𝑀𝐽/𝑘𝑔 𝑊𝑎𝑡𝑒𝑟 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 = 𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑 𝐴𝑚𝑡 𝑤𝑎𝑡𝑒𝑟 𝑎𝑝𝑝𝑙𝑖𝑒𝑑 = 4397 𝑘𝑔/ℎ𝑎 1774.44 𝑚3/ℎ𝑎 = 2.48 𝑘𝑔/𝑚3 𝑁𝑒𝑡 𝐸𝑛𝑒𝑟𝑔𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡 − 𝑖𝑛𝑝𝑢𝑡 = 64070 𝑀𝐽 ℎ𝑎 − 8474 𝑀𝐽 ℎ𝑎 = 55596 𝑀𝐽/ℎ𝑎
  • 19. RESULT AND DISCUSSION 10/2/2022 19 𝐸𝑛𝑒𝑟𝑔𝑦 𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡 = 55366 𝑀𝐽/ℎ𝑎 7357.4 𝑀𝐽/ℎ𝑎 = 7.53 𝐸𝑛𝑒𝑟𝑔𝑦 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 = 𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡 = 3800 𝑘𝑔/ℎ𝑎 7357.4 𝑀𝐽/ℎ𝑎 = 0.52 𝑘𝑔/𝑀𝐽 𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝐸𝑛𝑒𝑟𝑔𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑖𝑛𝑝𝑢𝑡 𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑 = 7357.4 𝑀𝐽/ℎ𝑎 3800 𝑘𝑔/ℎ𝑎 = 1.94 𝑀𝐽/𝑘𝑔 𝑊𝑎𝑡𝑒𝑟 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 = 𝐺𝑟𝑎𝑖𝑛 𝑦𝑖𝑒𝑙𝑑 𝐴𝑚𝑡 𝑤𝑎𝑡𝑒𝑟 𝑎𝑝𝑝𝑙𝑖𝑒𝑑 = 3800 𝑘𝑔/ℎ𝑎 1030.32 𝑚3/ℎ𝑎 = 3.69𝑘𝑔/𝑚3 𝑁𝑒𝑡 𝐸𝑛𝑒𝑟𝑔𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑢𝑡𝑝𝑢𝑡 − 𝑖𝑛𝑝𝑢𝑡 = 55366 𝑀𝐽 ℎ𝑎 − 7357.4 𝑀𝐽 ℎ𝑎 = 48009 𝑀𝐽/ℎ𝑎
  • 20. RESULT AND DISCUSSION 10/2/2022 20 𝑀𝐸 𝐴𝑠𝑢𝑛𝑐𝑖𝑜𝑛 = 𝐿𝑀 𝐿𝑀 + 𝐿𝐻 = 0.2 374 0.2 374 + 0.1(366) = 67.15% 𝑀𝐸 𝐶𝑎𝑟𝑚𝑒𝑛 = 𝐿𝑀 𝐿𝑀 + 𝐿𝐻 = 0.2 1012 0.2 1012 + 0.1(1313) = 60.65% 𝑀𝐸 𝑁𝑒𝑤 𝐶𝑜𝑟 = 𝐿𝑀 𝐿𝑀 + 𝐿𝐻 = 0.2 1701 0.2 1701 + 0.1(1225) = 73.52% 𝑀𝐸 𝑆𝑡𝑜. 𝑇𝑜𝑚𝑎𝑠 = 𝐿𝑀 𝐿𝑀 + 𝐿𝐻 = 0.2 2143 0.2 2143 + 0.1(1797) = 70.46%
  • 22. ECONOMIC ANALYSIS – SEE EXCEL FILE 10/2/2022 22

Editor's Notes

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