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Energy consumption, energy saving and emission reduction of a garment industrial building in Bangladesh
Energy 112 (2016) 91e100
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Energy journal homepage: www.elsevier.com/locate/energy
Energy consumption, energy saving and emission reduction of a garment industrial building in Bangladesh Mohammad Ahsan Habib a, M. Hasanuzzaman b, *, M. Hosenuzzaman b, Asif Salman a, Md Riyad Mehadi a a b
Department of Mechanical and Chemical Engineering (MCE), Islamic University of Technology (IUT), Board Bazar, Gazipur, 1704, Dhaka, Bangladesh UM Power Energy Dedicated Advanced Center, Level 4, Wisma R&D, University of Malaya, 59990, Kuala Lumpur, Malaysia
a r t i c l e i n f o
a b s t r a c t
Article history: Received 15 December 2015 Received in revised form 9 June 2016 Accepted 12 June 2016
The industrial sector is the biggest energy consumer in Bangladesh. Electric motors account for more than 45% of the electricity consumption in the industrial sector in the country. A walk through energy audit has been conducted at Garments in Bangladesh to identify the energy using equipment and energy consumption breakdown. Different energy saving strategies and emissions reduction has been estimated for the garment. It is also found that about 137,003 kWh, 319,673 kWh and 502,343 kWh of energy and BDT 1,312,484, BDT 3,062,463 and BDT 4,812,442 of bill savings for 20%, 40% and 60% speed reduction by using variable speed drive (VSD) respectively. By using high efficiency motors (HEM), about 28,311 kWh, 41,713 kWh and 57,080 kWh of energy and BDT 271,242, BDT 399,574 and BDT 546,852 of bill can be saved for motor loadings of 50%, 75% and 100% respectively. The payback periods of different energy saving strategies indicated that HEMs seems cost-effective. Both HEMS and VSD more cost effective for large motors. It is also found that huge amount of emissions can be reduced for different energy saving strategies applied in garment. © 2016 Elsevier Ltd. All rights reserved.
Keywords: Energy Energy consumption Energy savings Emission reduction Garments building
1. Introduction Energy is one of the crucial factors for continuous development and economic growth. Economy growth is closely related with growth in its energy consumption, particularly in the case of developing countries [1]. The energy consumption will increase by 33% from 2010 to 2030 in the world [2,3]. The world power demand rises from 145 billion MW in 2007 to 218 billion MW in 2035 (i.e., increases by 49%). Energy efficiency improvement is one of the most important functions to reduce energy consumption. Energy efficiency improvement is the main objective of many national energy policies [4]. Monitoring of the energy consumption and developments in energy efficiency is necessary in order to check and apply desired policies. About 35% of world's total energy is used in industrial sectors [5]. Electricity demand in Bangladesh is currently increasing by more than 8% annually. The demand is projected to be 22,500 MW in 2021 where more than 40% of the
* Corresponding author. E-mail addresses: (M. Hasanuzzaman).
[email protected],
http://dx.doi.org/10.1016/j.energy.2016.06.062 0360-5442/© 2016 Elsevier Ltd. All rights reserved.
[email protected]
energy is consumed in the industrial sector in Bangladesh [6,7]. It is also expected that the share of the industrial sector be augmented in the future. Bangladesh is one of the fastest-growing ready-made garment (RMG) exporters in the world where the garment buildings consumed huge amount of energy. Nguyen et al. [8] reviewed the optimization methods for building performance and found location, design and operating parameters have great influence on building performance. Li and Wen [9] reviewed and discussed the different model-based optimal control methods to reduce building energy cost and found the better control and operation strategies can improve building energy efficiency. Garment factories have several energy intensive operations and energy cost on average is about 16.7% (i.e. varying from 6% to 60%) of production costs in Cambodia in 2010 [10]. Nguyen [11] also found the energy cost about 10e15% of the production cost and energy waste about 20e32% due to old technologies and outdated energy management systems. The author also mentioned energy saving potential about up to 30% in garment industry where HEMs and VSD are promising to invest. Unfortunately, this sector mostly uses standard motor, instead of HEMs. The implementation of VSD and HEMs not only save energy but also reduce emissions. Thailand and the Philippines are leading to develop the national standards of energy
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conservation [12]. Brazil has introduced a HEMs policies to reduce energy consumption and found that with the current average tariffs of electricity, HEMs are economical than standard motors [13]. In Europe, electric motors use about 70% of the industrial electricity used where HEMs can significantly reduce energy used and environmental impact [14]. Bortoni [15] found that about 44% of motors operate at 40% or less of the full load capacities in the US in the industries [16]. Normally, load factors for most motors in buildings and industrial facilities range from 50% to 70% [17]. So, the VSDs in electric is a potential solution to reduce energy consumption as well as emission reduction. The aim of this study is to analyze the energy consumption, energy savings, bill savings and payback period and emissions reductions by using VSD and HEMs in the garment. 2. Methodology 2.1. Data collection and characteristics of the garment A walk through energy audit was conducted in Kojima Lyric Garments, Bangladesh. The survey investigated total energy consumption, types of energy supply, types of equipment and energy consumption and usage behaviour. To do the survey, a detailed preparation was taken and made a meeting with the appropriate personnel to set a specific questioners and visited floor by floor under the supervision of authority of the seven storied building with an underground level. 1st floor contains accounts and administrative office, child care room, medical center, cutting section, quick-checking section and some essential electrical equipment like boiler, generator and pump. The 2nd floor contains spot removing room, quality control room, processing and packing section and the office room for Japanese AGM. 3rd floor contains work station for both usual clothing as well as raincoats. The production of raincoat runs only for a few months of a year. Floors 4e6 are similar and contain gaze pattern room, sewing floor, and store room. Floor 7th consists of sample and CAD room, water treatment plant, cafeteria, prayer room and store room. The equipment are divided into 3 groups such as lights, motors and other appliances. Tables 1e3 show the details of the type, number, operating hours of energy consuming equipment in the garment.
Table 2 Number of electric motors, capacity and operating hours in 2014. Machine
Power (W)
Quantity
Operating hour (h/y)
Lay Hook and bar Heat transfer Needle detector PP belt Button hole APW CAD Hand Stitch Overload Pintap Repeat button Zigzac Auto plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind Stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron Table Saddle stitch Tonton Vertical plane Vortex Spot remover WinDa Fabric inspection Bend knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
90 150 150 150 150 300 350 400 400 400 400 400 450 500 500 500 550 550 550 550 550 550 550 550 550 550 550 550 550 550 1000 1000 1020 1120 1500 2000 3000 3240 4000 4103 7460 12,000 35,000
4 2 3 1 1 5 7 3 3 66 4 1 1 380 7 15 8 14 8 18 3 5 19 7 3 217 1 3 14 11 1 1 1 7 1 1 1 5 2 1 1 6 1
2250 1875 1500 1500 2250 1875 1875 1875 225 1875 1875 112.5 1875 1875 600 1875 1875 1875 1875 1875 1875 1875 1875 1875 1875 1250 1875 225 1875 1750 1000 1000 1000 1750 1000 600 600 600 1750 500 500 1750 1000
Table 3 Number of machine/equipment, capacity and operating hours in 2014.
2.2. Mathematical formulation Annual energy consumption by electric equipment can be calculated using Equation (1) [18,19].
AEC ¼ C hr L 0:001
(1)
where AEC ¼ annual energy consumption (kWh), C ¼ rated power, L ¼ load factor, hr ¼ yearly usage hours. Electric motors efficiency over 90% at the rated loads and very inefficient when running on part loads. Motors are more efficient at 75% of rated load and above where very inefficient when operated at lower than 50% of rated load. Many industrial sectors uses oversize motors to meet extra load demand and load also varies during operation that causes motors to work at low load and inefficiency [20]. VSD optimize the voltage and frequency supply to
Table 1 Number and types of lights, capacity and operating hours in 2014. Type
Quantity
Power (W)
Operating hours (h/y)
Tube light (single) Tube light (double) Energy saving bulb
2272 177 96
20 40 20
3000 3000 3000
Machine
Power(W)
Quantity
Operating hour (h/y)
Air compressor Boiler Lift (goods) Lift (passenger) Fridge (8.5 cft) Fridge (10 cft) Fan Exhaust fan (big) Exhaust fan (small) Stand fan Computer Laptop A/C 4.5 Ton A/C 2 Ton Window A/C
11,000 536 11,000 5500 330 610 70 210 90 350 200 150 5200 2100 1900
1 2 1 1 1 1 520 26 5 8 28 12 3 14 2
1500 1750 250 500 2920 2920 2640 3000 3000 1560 3000 2000 1080 1080 1080
the motor to match the speed for actual load demand [21]. The variable speed drives are good candidates to match the required load to work efficiently and to save energy [18]. Properly designed VSD systems can typically save energy consumption by 20%e70% [21]. Energy savings with the application of variable speed drive can be estimated as following equation (3) [18,20,22]. Percentage of
M.A. Habib et al. / Energy 112 (2016) 91e100 Table 4 Percentage energy savings using speed reduction.
Table 8 Annual energy consumption and bill for electrical motors in 2014.
Average speed reduction (%)
Potential energy saving, SSR
20 40 60
15 35 55
(%)
energy saving with speed reduction data has been directly taken from Refs. [18,20,22] that is shown in Table 4.
AESVSD ¼ W Havgusage SSR
(2)
where AESVSD ¼ annual energy saving using VSD (kWh), W ¼ Motor rated power, Haverage ¼ average yearly usage hours, Ssr ¼ percentage energy savings using speed reduction. Energy savings by using Variable speed drive or controlling speed reduction has been calculated at different speed reduction (%). High efficiency motors are more efficient than the standard motor where the typically cost 10e25% more than standard motor [18,23]. Annual energy saving by replacing standard efficient motors with high efficiency motors (HEM) can be estimated by using the following equation and efficiency related data has been taken from Table 5 [23,24]:
AESHEM ¼ W L hr
1 1 Estd Eee
100
(3)
where AES ¼ annual energy saving (kWh), W ¼ motor rated power (W), L ¼ load factor (%), hr ¼ yearly usage hours, Estd ¼ efficiency of standard motor (%), Eee ¼ efficiency of energy efficient motor (%). Table 5 Efficiency of various standard motors and energy efficient motors. Power (W)
1120 1500 2000 3000 3240 4000 4103 7460 12,000
Load (50%)
Load (75%)
Load (100%)
Estd
Eee
Estd
Eee
Estd
Eee
76.04 77.2 77.66 81.07 81.07 81.09 81.15 84.32 84.97
80.06 80.02 82.29 83.69 83.93 84.26 84.35 86.9 88.61
78.03 79.29 79.71 82.39 83.53 84.12 84.73 86.3 86.45
82.28 83.07 84.44 85.25 85.86 86.07 86.5 88.87 89.85
78.5 81 81.33 82.9 83.57 84.67 85.3 85.2 87.94
82.55 83.55 85 85.96 86.38 87.6 87.75 90.1 90.56
Table 6 Emission factor per unit energy use for various fuels. Fuels
Coal Petroleum Natural gas Hydro
93
Machine
Energy consumption (kWh)
Energy bill (BDT)
Lay Hook and bar Heat transfer Needle detector PP belt Button hole APW CAD Hand Stitch Overload Pintap Repeat Button Zigzac Auto Plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind Stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron Table Saddle stitch Tonton Vertical plane Vortex Spot remover WinDa Fabric inspection Bend knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging Total
810 563 675 225 338 2813 4594 2250 270 49,500 3000 45 844 356,250 2100 14,063 8250 14,438 8250 18,563 3094 5156 19,594 7219 3094 149,188 1031 371 14,438 10,588 1000 1000 1020 13,720 1500 1200 1800 9720 14,000 2052 3730 126,000 35,000 913,350
7760 5389 6467 2156 3233 26,944 44,008 21,555 2587 474,210 28,740 431 8083 341,2875 20,118 134,719 79,035 138,311 79,035 177,829 29,638 49,397 187,708 69,156 29,638 1,429,216 9879 3557 138,311 101,428 9580 9580 9772 131,438 14,370 11,496 17,244 93,118 134,120 19,653 35,733 1,207,080 335,300 8,749,895
Annual bill saving for using VSD or energy efficient motor can be calculated by using the following equation:
ABS ¼ AES c
(4)
Table 9 Annual energy consumption and bill for other appliances in 2014.
Emission factors (kg/kWh) CO2
SO2
CO
1.18 0.85 0.53 0
0.0139 0.0164 0.0005 0
0.002 0.002 0.005 0
Table 7 Annual energy consumption and bill for lights in 2014. Type
Energy consumption (kWh)
Energy bill (BDT)
Tube light (single) Tube light (double) Energy saving bulb Total
136,320 21,240 5760 163,320
1,305,946 203,479 55,181 1,564,606
Machine
Energy consumption (kWh)
Energy bill (BDT)
Air compressor Boiler Lift (goods) Lift (passenger) Fridge (8.5 cft) Fridge (10 cft) Fan Exhaust fan (big) Exhaust fan (small) Stand fan Computer Laptop A/C 4.5 Ton A/C 2 Ton Window A/C Total
16,500 1876 2750 2750 964 1781 96,096 16,380 1350 4368 16,800 3600 16,848 31,752 4104 217,919
158,070 17,972 26,345 26,345 9231 17,064 920,600 156,920 12,933 41,845 160,944 34,488 161,404 304,184 39,316 2,087,662
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Simple payback period has been calculated by using following equation:
PBP ¼
Fig. 1. Percentage of energy consumption by the different types of appliances.
where ABS ¼ annual bill saving, AES ¼ annual energy saving, c ¼ average energy cost (BDT/kWh).
IC ABS
(5)
where ABS ¼ annual bill saving (BDT), AES ¼ annual energy saving (kWh), IC ¼ incremental cost (BDT). It is known that emission of greenhouse gases (GHGs) (i.e. CO2, SO2, CO) are emitted when fossil fuels are burned [25]. The amount of GHGs reduction for energy savings strategies in this garment is based on the percentages of the generation of electricity from different fuels mix, emission factors for power generation of power plant for the specific fuels and percentages of electricity generated by each type of fuels (i.e. coal, petroleum, natural gas etc.) [18,25]. Emission reductions associated with energy savings strategies are estimated based on fuel type, percentage of electricity generated by the specific fuel and the emission factor of fuels to produce the electricity by using equation (6) [18,25,26]. The emission factor per unit electricity generation for various fuels has been considered same as Malaysian power plant emissions factor that has been taken from Refs. [18,20] and shown in Table 6. The fuel mix electricity generation of Bangladesh has been taken from the presentation of Secretary Power Division in a Seminar in Dhaka, March
Table 10 Energy and bill saving using VSD at certain speed reduction. Machine
Lay Hook and bar Heat transfer Needle detector PP belt Button hole APW CAD Hand stitch Overload Pintap Repeat button Zigzac Auto plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron table Saddle stitch Tonton Vertical plane Vortex Spot remover WinDa Fabric inspection Bend Knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
Annual energy saving (kWh) for speed reduction
Annual bill saving (BDT) for speed reduction
20%
40%
60%
20%
40%
60%
122 84 101 34 51 422 689 338 41 7425 450 7 127 53,438 315 2109 1238 2166 1238 2784 464 773 2939 1083 464 22,378 155 56 2166 1588 150 150 153 2058 225 180 270 1458 2100 308 560 18,900 5250
284 197 236 79 118 984 1608 788 95 17,325 1050 16 295 124,688 735 4922 2888 5053 2888 6497 1083 1805 6858 2527 1083 52,216 361 130 5053 3706 350 350 357 4802 525 420 630 3402 4900 718 1306 44,100 12,250
446 309 371 124 186 1547 2527 1238 149 27,225 1650 25 464 195,938 1155 7734 4538 7941 4538 10,209 1702 2836 10,777 3970 1702 82,053 567 204 7941 5823 550 550 561 7546 825 660 990 5346 7700 1128 2052 69,300 19,250
1164 808 970 323 485 4042 6601 3233 388 71,132 4311 65 1212 511,931 3018 20,208 11,855 20,747 11,855 26,674 4446 7410 28,156 10,373 4446 214,382 1482 533 20,747 15,214 1437 1437 1466 19,716 2156 1724 2587 13,968 20,118 2948 5360 18,1062 50,295
2716 1886 2263 754 1132 9430 15,403 7544 905 165,974 10,059 151 2829 1,194,506 7041 47,152 27,662 48,409 27,662 62,240 10,373 17,289 65,698 24,204 10,373 500,226 3458 1245 48,409 35,500 3353 3353 3420 46,003 5030 4024 6035 32,591 46,942 6879 12,507 422,478 117,355
4268 2964 3557 1186 1778 14,819 24,204 11,855 1423 260,816 15,807 237 4446 1,877,081 11,065 74,095 43,469 76,071 43,469 97,806 16,301 27,168 103,239 38,036 16,301 786,069 5434 1956 76,071 55,786 5269 5269 5374 72,291 7904 6323 9484 51,215 73,766 10,809 19,653 663,894 184,415
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95
Table 11 Payback periods by using VSD at a certain speed reduction. Machine
Power (W)
Lay Hook and Bar Heat Transfer Needle Detector PP belt Button hole APW CAD Hand Stitch Overload Pintap Repeat Button Zigzac Auto Plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind Stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron Table Saddle stitch Tonton Vertical Plane Vortex Spot Remover WinDa Fabric Inspection Bend Knife Spot Remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
90 150 150 150 150 300 350 400 400 400 400 400 450 500 500 500 550 550 550 550 550 550 550 550 550 550 550 550 550 550 1000 1000 1020 1120 1500 2000 3000 3240 4000 4103 7460 12,000 35,000
Incremental cost (BDT)
134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 141,120 141,120 141,120 165,375 165,375 225,057 280,623 798,231
Payback period (y) 20%
40%
60%
461.9 332.5 415.7 415.7 277.1 166.3 142.5 124.7 1039.2 124.7 124.7 2078.4 110.8 99.8 311.8 99.8 90.7 90.7 90.7 90.7 90.7 90.7 90.7 90.7 90.7 136.0 90.7 755.8 90.7 97.2 93.5 93.5 91.7 47.7 62.4 81.8 54.6 50.5 16.4 56.1 42.0 9.3 15.9
197.9 142.5 178.1 178.1 118.8 71.3 61.1 53.4 445.4 53.4 53.4 890.7 47.5 42.8 133.6 42.8 38.9 38.9 38.9 38.9 38.9 38.9 38.9 38.9 38.9 58.3 38.9 323.9 38.9 41.6 40.1 40.1 39.3 20.5 26.7 35.1 23.4 21.7 7.0 24.0 18.0 4.0 6.8
126.0 90.7 113.4 113.4 75.6 45.3 38.9 34.0 283.4 34.0 34.0 566.8 30.2 27.2 85.0 27.2 24.7 24.7 24.7 24.7 24.7 24.7 24.7 24.7 24.7 37.1 24.7 206.1 24.7 26.5 25.5 25.5 25.0 13.0 17.0 22.3 14.9 13.8 4.5 15.3 11.5 2.5 4.3
EMi ¼ EPi (PEi1 Em1p þ PE2i Em2pþ PE3i Em3pþ … … … PEni Emnp)
(6)
where Emi ¼ total amount of emission (ton), Epi ¼ electricity production in the year i, PEin ¼ percentage of electricity generation in a year i of fuel type n recommended, Empn ¼ fossil fuel emission for a unit of electricity generation of fuel type n. 3. Results and discussion 3.1. Energy consumption and annual bills
Fig. 2. Annual energy and bill saving by using VSD.
2015. According to the presentation, fuel mix electricity generation are about 2%, 29%, 62%, 2% from coal, petroleum, natural gas, hydro respectively [27].
Energy consumption data has been collected by a walk through energy audit in Kojima Lyric Garments, Bangladesh. The survey investigated and collected types of equipment, number of equipment, rating of each equipment for energy consumption, usage behaviour etc. Energy consumption of equipment's has been calculated by using Equation (1) and data from Tables 1e3 that are shown in Tables 7e9. The percentage of energy consumption by the different types of appliances are shown in Fig. 1. Energy bill has been calculated based on the energy consumption and unit energy cost. Table 7 shows that lights consume about
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Table 12 Energy and bill savings by using HEMs at different loadings. Machine
Lay Hook and bar Heat transfer Needle detector PP belt Button hole APW CAD Hand stitch Overload Pintap Repeat button Zigzac Auto Plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron table Saddle stitch Tonton Vertical plane Vortex Spot remover WinDa Fabric inspection Bend knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
Annual energy saving (kWh) for loading
Annual bill saving (BDT) for loading
50%
75%
100%
50%
75%
100%
27 19 22 7 11 93 152 74 9 1634 99 1 28 11,762 69 464 272 477 272 613 102 170 647 238 102 4926 34 12 477 350 33 33 34 453 46 43 35 321 462 68 114 2218 1288
40 28 34 11 17 140 228 112 13 2458 149 2 42 17,687 104 698 410 717 410 922 154 256 973 358 154 7407 51 18 717 526 50 50 51 681 74 60 55 299 430 63 115 3873 1076
51 35 42 14 21 176 287 141 17 3094 187 3 53 22,265 131 879 516 902 516 1160 193 322 1225 451 193 9324 64 23 902 662 62 62 64 857 94 75 112 607 875 128 233 7875 2187
256 178 214 71 107 890 1453 712 85 15,657 949 14 267 112,683 664 4448 2610 4567 2610 5871 979 1631 6198 2283 979 47,189 326 117 4567 3349 316 316 323 4340 439 416 333 3074 4428 649 1092 21,251 12,341
385 268 321 107 161 1338 2185 1070 128 23,543 1427 21 401 169,440 999 6688 3924 6867 3924 8829 1471 2452 9319 3433 1471 70,957 490 177 6867 5036 476 476 485 6526 713 571 530 2862 4123 604 1098 37,104 10,307
485 337 404 135 202 1684 2750 1347 162 29,637 1796 27 505 213,299 1257 8420 4940 8644 4940 11,114 1852 3087 11,731 4322 1852 89,324 617 222 8644 6339 599 599 611 8215 898 718 1078 5820 8382 1228 2233 75,440 20,956
163,320 kWh (about 13% of total energy consumption, Fig. 1) energy and energy bill about BDT 1,564,606. It is also shown that single tube lights are the major energy consumer in the garment where consume about 136,320 kWh (83% of total lighting) energy and energy bill about BDT 1,305,946. Table 8 shows that electric motors are the major energy consumer and consume about 913,350 kWh (about 70% of total energy consumption, Fig. 1) energy and energy bill about BDT 8,749,895. From Table 9, it is found that others appliances consume about 21, 7919 kWh (about 17% of total energy consumption, Fig. 1) energy and energy bill about BDT 2,087,662. 3.2. Energy savings, bill savings and payback period by using variable speed drive Electric motors are efficient at 75% of rated load and above where very inefficient at lower than 50% of rated load due to the reactive current increase, power factors etc [28]. In such cases, variable speed drive can be the potential candidates to match the load requirements and consequently save a huge amount of energy, lower utility bills and protect the environment from harmful
pollutants [22]. Energy savings of electric motors have been calculated by using Equation (2) and data from Tables 2 and 4 that are shown in Table 10. Energy bill savings and payback period of electric motors have been calculated by using Equations (4) and (5) that are shown in Tables 10 and 11. Fig. 2 shows the total annual energy and bill savings by using VSD. From Fig. 2, it is found that about 137,003 kWh, 319,673 kWh and 502,343 kWh of energy can be saved for a 20%, 40% and 60% speed reduction by using a variable speed drive respectively. It is also found that the energy saving is high at the higher percentage of speed reduction. The annual bill savings for the energy savings of BDT 1,312,484, BDT 3,062,463 and BDT 4,812,442 for 20%, 40% and 60%, respectively. Fig. 2 also shows that energy and bill savings increase with increases the percentage of motor speed reduction. From Table 11, it is found that payback periods are shorter for a higher percentage of speed reduction (for example 60% speed reduction). It also found that payback periods are shorter for larger motors (i.e. 4 kW and above) that also depend on the operating hours. Saidur et al. [18] found that the payback periods for using a variable speed drive for larger motors (i.e. about 7.5 kW and above) are reasonable (i.e. within 1e3 years).
M.A. Habib et al. / Energy 112 (2016) 91e100
97
Table 13 Payback period for replacing by HEMs. Machine
Power (W)
Lay Hook and Bar Heat Transfer Needle Detector PP belt Button hole APW CAD Hand Stitch Overload Pintap Repeat Button Zigzac Auto Plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind Stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron table Saddle stitch Tonton Vertical plane Vortex Spot remover WinDa Fabric inspection Bend knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
90 150 150 150 150 300 350 400 400 400 400 400 450 500 500 500 550 550 550 550 550 550 550 550 550 550 550 550 550 550 1000 1000 1020 1120 1500 2000 3000 3240 4000 4103 7460 12,000 35,000
Incremental cost (BDT)
1000 1000 1000 1000 1000 1000 1000 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1806 4032 4200 4578 4578 4578 6500 7000 17,000
Payback period (y) 50% load
75% load
100% load
15.6 11.2 14.1 14.1 9.4 5.6 4.8 7.1 59.0 7.1 7.1 118.0 6.3 5.7 17.7 5.7 5.2 5.2 5.2 5.2 5.2 5.2 5.2 5.2 5.2 7.7 5.2 42.9 5.2 5.5 5.3 5.3 5.2 2.7 4.1 9.7 12.6 7.4 2.1 7.1 6.0 2.0 1.4
10.4 7.5 9.3 9.3 6.2 3.7 3.2 4.7 39.2 4.7 4.7 78.5 4.2 3.8 11.8 3.8 3.4 3.4 3.4 3.4 3.4 3.4 3.4 3.4 3.4 5.1 3.4 28.5 3.4 3.7 3.5 3.5 3.5 1.8 2.5 7.1 7.9 8.0 2.2 7.6 5.9 1.1 1.6
8.2 5.9 7.4 7.4 4.9 3.0 2.5 3.7 31.2 3.7 3.7 62.4 3.3 3.0 9.4 3.0 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 4.1 2.7 22.7 2.7 2.9 2.8 2.8 2.8 1.4 2.0 5.6 3.9 3.9 1.1 3.7 2.9 0.6 0.8
Table 12. Energy bill savings and payback period of electric motors have been calculated by using Equations (4) and (5) that are shown in Table 13. Fig. 3 shows the total annual energy and bill savings. From Fig. 3, it is found that 28,311 kWh, 41,713 kWh and 57,080 kWh of energy can be saved for motor loadings of 50%, 75% and 100%, respectively. This will translate into bill savings of BDT 271,242, BDT 399,574 and BDT 546,852 for motor loadings of 50%, 75% and 100% respectively. Fig. 3 also shows that energy and bill savings increase with increases the percentage of motor loading. The payback period of the HEM varies from motor to motor depends on capacity and operation hours that are less than 6 years for capacity more than 500 W motors in most of the cases. Even the PBPs are less than 1 year for some of the motors with higher capacity and higher operating load. Fig. 3. Annual energy and bill savings by using HEMs.
3.3. Energy savings, bill savings and payback period by using high efficiency motor Energy savings of electric motors have been calculated by using Equation (3) and data from Tables 2 and 5 that are shown in
3.4. Comparison the effectiveness of common energy saving measure Energy conservation and management are very important because of the energy consumption has direct social, economic and environmental impacts. Energy efficient use and energy savings in the end-use section are the easiest ways to reduce costs in any
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organization. Using best practice methodologies and proper energy management can reduce costs, lower emissions and increase profitability [21]. Electric motor is one of the major energy consumer in any commercial and industrial sectors. These PBPs indicate the implementation of energy-efficient motors seems very cost-effective as their PBPs are less than one-third of the motor life (if an average motor life of 20 years is considered) particularly for large motors. Energy efficient also depends on operating conditions. The energy efficiency motors are most cost effective when replacing motors with operation more than 2000 h annually [29]. This analysis found that the PBPs of VSD varies from motor to motor depends on capacity and operation hours. Most of the cases, the PBPs are more than 10 years for capacity less than 7.5 kW motors. But the PBPs are less than 10 years for some of the motors with higher capacity and higher operating load. Tolvanen [30,31] found that VSD is not cost effect for smaller motor. Saidur [20] found also that VSD is cost effect for motor capacity more 10 kW at higher speed reduction. This analysis found that the PBPs of HEM varies from motor to motor depends on capacity and operation hours. Most of the cases, the PBPs are less than 6 years for capacity more than 500 W motors. Even the PBPs are less than 1 years for some of the motors with higher capacity and higher operating load. According to the Copper
Development Association, the HEMs replacement compared to the minimum motors efficiency have PBPs of less than 15 months for 37.3 kW (50 hp) motors [29,32]. Saidur [20], Hasanuzzaman et al. [24] and Almeida et al. [33] also analyzed the energy savings, costeffectiveness and found that HEM is cost effective. Many end users routinely replace failed motors rated up to 75 kW with HEMs [21]. In some cases, rewind of an existing HEM is cost effective compared to purchase a new motor [29,34]. An analysis also found that industrial end users rewind 40% of the motors that fail each year and the percentage of rewinding increases with increasing the capacity of the motors [35]. Hasanuzzman et al. [24] found about 81% of motors with more than 15 kW (20 hp) are rewound and the rewinding percentage increases with increasing motor's capacity. But if rewinding costs more than 60% of the new HEM, then better choice to buy new motor [29,34]. 3.5. Emission reduction By introducing high DSV, HEMs, and energy efficient light, not only saved energy, but also saved huge amount of emission of various gaseous pollutants. Emissions reduction have been calculated by using Equation (6) and energy savings data from Tables 10 and 12 that are shown in Tables 14 and 15. The emission reduction
Table 14 Emission reduction at a certain speed reduction for using VSD. Machine
20% SR emission reduction (Kg)
40% SR emission reduction (Kg)
60% SR emission reduction (Kg)
CO2
SO2
CO
CO2
SO2
CO
CO2
SO2
CO
Lay Hook and bar Heat transfer Needle detector PP belt Button hole APW CAD Hand stitch Overload Pintap Repeat button Zigzac Auto plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron table Saddle stitch Tonton Vertical plane Vortex Spot remover WinDa Fabric inspection Bend knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
7274 5052 6062 2021 3031 25,258 41,254 20,206 2425 444,535 26,942 404 7577 3,199,303 18,859 126,288 74,089 129,656 74,089 166,701 27,783 46,306 175,962 64,828 27,783 1,339,778 9261 3334 129,656 95,081 8981 8981 9160 123,212 13,471 10,777 16,165 87,290 125,727 18,423 33,497 1,131,543 314,318
65 45 54 18 27 225 368 180 22 3968 240 4 68 28,557 168 1127 661 1157 661 1488 248 413 1571 579 248 11,959 83 30 1157 849 80 80 82 1100 120 96 144 779 1122 164 299 10,100 2806
45 31 38 13 19 157 256 126 15 2762 167 3 47 19,879 117 785 460 806 460 1036 173 288 1093 403 173 8325 58 21 806 591 56 56 57 766 84 67 100 542 781 114 208 7031 1953
16,973 11,787 14,144 4715 7072 58,935 96,260 47,148 5658 1,037,248 62,864 943 17,680 7,465,041 44,004 294,673 172,875 302,531 172,875 388,968 64,828 108,047 410,577 151,265 64,828 3,126,149 21,609 7779 302,531 221,856 20,955 20,955 21,374 287,496 31,432 25,145 37,718 203,678 293,363 42,988 78,160 2,640,267 733,408
152 105 126 42 63 526 859 421 51 9258 561 8 158 66,633 393 2630 1543 2700 1543 3472 579 964 3665 1350 579 27,904 193 69 2700 1980 187 187 191 2566 281 224 337 1818 2619 384 698 23,567 6546
105 73 88 29 44 366 598 293 35 6445 391 6 110 46,384 273 1831 1074 1880 1074 2417 403 671 2551 940 403 19,424 134 48 1880 1378 130 130 133 1786 195 156 234 1266 1823 267 486 16,405 4557
26,672 18,522 22,227 7409 11,113 92,611 151,265 74,089 8891 1,629,961 98,786 1482 27,783 11,730,778 69,150 463,057 271,660 475,405 271,660 611,235 101,873 169,788 645,193 237,703 101,873 4,912,521 33,958 12,225 475,405 348,630 32,929 32,929 33,587 451,779 49,393 39,514 59,271 320,065 460,999 67,553 122,823 4,148,991 1,152,498
238 165 198 66 99 827 1350 661 79 14,549 882 13 248 104,709 617 4133 2425 4243 2425 5456 909 1516 5759 2122 909 43,849 303 109 4243 3112 294 294 300 4033 441 353 529 2857 4115 603 1096 37,034 10,287
166 115 138 46 69 575 940 460 55 10,128 614 9 173 72,889 430 2877 1688 2954 1688 3798 633 1055 4009 1477 633 30,524 211 76 2954 2166 205 205 209 2807 307 246 368 1989 2864 420 763 25,780 7161
M.A. Habib et al. / Energy 112 (2016) 91e100
99
Table 15 Emission reduction at a certain loading by using HEMs. Machine
Lay Hook and bar Heat transfer Needle detector PP belt Button hole APW CAD Hand Stitch Overload Pintap Repeat Button Zigzac Auto plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron table Saddle stitch Tonton Vertical plane Vortex Spot Remover WinDa Fabric inspection Bend knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
50% load emission reduction (kg)
75% load emission reduction (kg)
100% load emission reduction (kg)
CO2
SO2
CO
CO2
SO2
CO
CO2
SO2
CO
16 11 13 4 7 56 91 44 5 978 59 1 17 7042 42 278 163 285 163 367 61 102 387 143 61 2949 20 7 285 209 20 20 20 271 27 26 21 192 277 41 68 1328 771
0.1 0.1 0.1 0.0 0.1 0.5 0.8 0.4 0.0 8.7 0.5 0.0 0.1 62.9 0.4 2.5 1.5 2.5 1.5 3.3 0.5 0.9 3.5 1.3 0.5 26.3 0.2 0.1 2.5 1.9 0.2 0.2 0.2 2.4 0.2 0.2 0.2 1.7 2.5 0.4 0.6 11.9 6.9
0.1 0.1 0.1 0.0 0.0 0.3 0.6 0.3 0.0 6.1 0.4 0.0 0.1 43.8 0.3 1.7 1.0 1.8 1.0 2.3 0.4 0.6 2.4 0.9 0.4 18.3 0.1 0.0 1.8 1.3 0.1 0.1 0.1 1.7 0.2 0.2 0.1 1.2 1.7 0.3 0.4 8.3 4.8
24 17 20 7 10 84 137 67 8 1471 89 1 25 10,589 62 418 245 429 245 552 92 153 582 215 92 4434 31 11 429 315 30 30 30 408 45 36 33 179 258 38 69 2319 644
0.2 0.1 0.2 0.1 0.1 0.7 1.2 0.6 0.1 13.1 0.8 0.0 0.2 94.5 0.6 3.7 2.2 3.8 2.2 4.9 0.8 1.4 5.2 1.9 0.8 39.6 0.3 0.1 3.8 2.8 0.3 0.3 0.3 3.6 0.4 0.3 0.3 1.6 2.3 0.3 0.6 20.7 5.7
0.1 0.1 0.1 0.0 0.1 0.5 0.8 0.4 0.0 9.1 0.6 0.0 0.2 65.8 0.4 2.6 1.5 2.7 1.5 3.4 0.6 1.0 3.6 1.3 0.6 27.6 0.2 0.1 2.7 2.0 0.2 0.2 0.2 2.5 0.3 0.2 0.2 1.1 1.6 0.2 0.4 14.4 4.0
30 21 25 8 13 105 172 84 10 1852 112 2 32 13,330 79 526 309 540 309 695 116 193 733 270 116 5582 39 14 540 396 37 37 38 513 56 45 67 364 524 77 140 4715 1310
0.3 0.2 0.2 0.1 0.1 0.9 1.5 0.8 0.1 16.5 1.0 0.0 0.3 119.0 0.7 4.7 2.8 4.8 2.8 6.2 1.0 1.7 6.5 2.4 1.0 49.8 0.3 0.1 4.8 3.5 0.3 0.3 0.3 4.6 0.5 0.4 0.6 3.2 4.7 0.7 1.2 42.1 11.7
0.2 0.1 0.2 0.1 0.1 0.7 1.1 0.5 0.1 11.5 0.7 0.0 0.2 82.8 0.5 3.3 1.9 3.4 1.9 4.3 0.7 1.2 4.6 1.7 0.7 34.7 0.2 0.1 3.4 2.5 0.2 0.2 0.2 3.2 0.3 0.3 0.4 2.3 3.3 0.5 0.9 29.3 8.1
Fig. 4. Annual emission reduction by using VSD.
has been presented in Tables 14 and 15 for variable speed drive and high efficiency motors respectively. Figs. 4 and 5 show the annual emissions reduction for variable speed drive and high efficiency motors respectively. From Figs. 4 and 5, it is found that about 100,304.91 kg, 175,677.73 kg and 276,065 kg of CO2 emissions can
Fig. 5. Annual emission reduction by using HEMs.
be reduced by using a variable speed drive for 20%, 40% and 60% of motor speed reductions respectively. Similarly about 2431.5 kg, 3230.06 kg and 3679.31 kg of CO2 emissions can be reduced by using energy-efficient motors at 50%, 75% and 100% loadings respectively. Besides CO2, huge amount of SO2, CO can be reduced
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M.A. Habib et al. / Energy 112 (2016) 91e100
that is also shown in Figs. 4 and 5. Figs. 3 and 5 also show that emissions reduction increase with increases the percentage of speed reduction and motor loading. The coal will be the main fuel after 2015 because Bangladesh has finalized a plan to establish coalbased power plants (i.e. 1320 MW at Rampal, 1200 MW at Matarbari, 4800 MW 4 at Moheskhali, 1320 MW at Payra in Patuakhali) and agreements have also been signed to establish coal power plant to generate 1411 MW electricity under public-private partnership [27]. So, emissions reduction will be the one of the issue for sustainable environment in Bangladesh. 4. Conclusion Based on end-use energy breakdown, it is found that about 70% of energy consumption by electric motors. It is also found that about 137,003 kWh, 319,673 kWh and 502,343 kWh of energy and BDT 1,312,484, BDT 3,062,463 and BDT 4,812,442 of bill savings for 20%, 40% and 60% speed reduction by using variable speed drive respectively. The payback periods are shorter for a higher percentage of speed reduction (for example 60% speed reduction) for larger motors (i.e. 4 kW and above) that also depend on the operating hours. By using high efficiency motors, about 28,311 kWh, 41,713 kWh and 57,080 kWh of energy and BDT 271,242, BDT 399,574 and BDT 546,852 of bill can be saved for motor loadings of 50%, 75% and 100% respectively. These payback periods indicate the implementation of HEMs seems very cost-effective as their payback periods are less than one-third of the motor life especially for large motors. By using VSD, about 100,304.91 kg, 175,677.73 kg and 276,065 kg of CO2 emissions can be reduced for 20%, 40% and 60% of motor speed reductions respectively. Similarly about 2431.5 kg, 3230.06 kg and 3679.31 kg of CO2 emissions can be reduced by using energy-efficient motors at 50%, 75% and 100% loadings respectively. Acknowledgement The authors would like to acknowledge the financial support from the University Malaya Research Grant scheme (Project No: RP016A-15SUS) to carry out this research. References [1] Mathur R, Chand S, Tezuka T. Optimal use of coal for power generation in India. Energy Policy 2003;31(4):319e31. [2] Abdelaziz EA, Saidur R, Mekhilef S. A review on energy saving strategies in industrial sector. Renew Sustain Energy Rev 2011;15(1):150e68. [3] Hasanuzzaman M, Rahim NA, Hosenuzzaman M, Saidur R, Mahbubul IM, Rashid MM. Energy savings in the combustion based process heating in industrial sector. Renew Sustain Energy Rev 2012;16(7):4527e36. [4] Saidur R, Mahlia TMI, Hasanuzzaman M. Developing energy performance standard, label and test procedures and impacts analysis for commercial chillers. Energy Educ Sci Technol Part A Energy Sci Res 2011;27(1):175e90. [5] Gielen D, Taylor P. Indicators for industrial energy efficiency in India. Energy Build 2009;34(8):962e9. [6] IEEOCB. Industrial energy efficiency opportunities and challenges in Bangladesh. 2014. Final Report, http://www.adb.org/sites/default/files/ project-document/80742/45916-014-tacr-01.pdf. [7] Hasanuzzaman M, Al-Amin AQ, Khanam S, Hosenuzzaman M. Photovoltaic power generation and its economic and environmental future in Bangladesh. J Renew Sustain Energy 2015;7(1):013108.
[8] Nguyen AT, Reiter S, Rigo P. A review on simulation-based optimization methods applied to building performance analysis. Appl Energy 2014;113: 1043e58. [9] Li X, Wen J. Review of building energy modeling for control and operation. Renew Sustain Energy Rev 2014;37:517e37. [10] Energy efficiency NAMA in the garment industry in Cambodia. United Nations Development Programme; 2015. http://www.undp.org/content/dam/undp/ library/Environment%20and%20Energy/MDG%20Carbon%20Facility/NAMA% 20Final%20Cambodia%202.pdf? (09/06/2016). [11] Nguyen DAT. Energy efficiency in the food processing and garment sector in Vietnam. 2012. https://www.giz.de/fachexpertise/downloads/2012-en-thipep-informationswork-vietnam-enereff.pdf (09/06/2016). [12] Yanti PAA, Mahlia TMI. Considerations for the selection of an applicable energy efficiency test procedure for electric motors in Malaysia: lessons for other developing countries. Energy Policy 2009;37:3467e74. [13] Delgado MAP, Tolmasquim MT. Analysis of a feasible tariff policy for the introduction of high efficiency electric motors in Brazil. Energy Convers Manag 2002;43:827e44. [14] Almeida ATD, Ferreira FJTE, Fong JAC, Brunner CU. Electric motor standards, ecodesign and global market transformation. In: Industrial and commercial power systems technical conference, Clear water Beach, FL, USA; 2008. Article number 4606292. [15] Bortoni EDC. Are my motors oversized? Energy Convers Manage 2009;50(9): 2282e7. [16] Capehart BL, Turner WC, Kennedy WJ. Guide to energy management. fifth ed. The Fairmont Press; 2005. [17] Jayamaha L. Energy efficient building systems. McGraw Hill; 2008. [18] Saidur R, Hasanuzzaman M, Yogeswaran S, Mohammed HA, Hossain MS. An end-use energy analysis in a Malaysian public hospital. Energy 2010;35(12): 4780e5. [19] Saidur R, Sambandam M, Hasanuzzaman M, Devaraj D, Rajakarunakaran S, Islam MD. An energy flow analysis in a paper-based industry. Clean Technol Environ Policy 2012;14(5):905e16. [20] Saidur R. Energy consumption, energy savings, and emission analysis in Malaysian office buildings. Energy Policy 2009;37(10):4104e13. [21] Siemens. Energy saving technology to deliver the fastest returns. 2011. Top 10 energy saving options, https://w3.siemens.co.uk/home/uk/en/aboutus/ Documents/Top10_energy_saving%20options_0911UK.pdf. [22] Saidur R, Rahim NA, Hasanuzzaman M. A review on compressed-air energy use and energy savings. Renew Sustain Energy Rev 2010;14(4):1135e53. [23] Garcia AGP, Szklo AS, Schaeffer R, McNeil MA. Energy-efficiency standards for electric motors in Brazilian industry. Energy Policy 2007;35(6):3424e39. [24] Hasanuzzaman M, Rahim NA, Saidur R, Kazi SN. Energy savings and emissions reductions for rewinding and replacement of industrial motor. Energy 2011;36(1):233e40. [25] Saidur R, Hasanuzzaman M, Mahlia TMI, Rahim NA, Mohammed HA. Chillers energy consumption, energy savings and emission analysis in an institutional buildings. Energy 2011;36(8):5233e8. [26] Mahlia TMI. Emissions from electricity generation in Malaysia. Renew Energy 2002;27(2):293e300. [27] Sufi S. Budget 2015-2016, allocation energy & power sectors. 2015. http:// www.en.banglanews24.com/fullnews/bn/111543.html (5 June 2015). [28] Kaya D, Yagmur EA, Yigit KS, Kilic FC, Eren AS, Celik C. Energy efficiency in pumps. Energy Convers Manag 2008;49(6):1662e73. [29] Hasanbeigi A. Energy-efficiency improvement opportunities for the textile industry. 2010. https://www.energystar.gov/sites/default/files/buildings/ tools/EE_Guidebook_for_Textile_industry.pdf. [30] Tolvanen J. LCC approach for big motor-driven systems savings. World Pumps 2008;2008(506):24e7. [31] Tolvanen J. Saving energy with variable speed drives. World Pumps 2008;2008(501):32e3. [32] CDA. Copper development association, high-efficiency copper-wound motors mean energy and dollar savings. 2001. http://energy.copper.org/motorad. html. [33] Almeida AT, Fonseca P, Bertoldi P. Energy-efficient motor systems in the industrial and in the services sectors in the European Union: characterisation, potentials, barriers and policies. Energy 2003;28(7):673e90. [34] MDM. Motor decisions matter, consortium for energy efficiency (CEE). 2007. Motor Planning Kit, Version 2.1. Strategies, Tools, and Resources for Developing a Comprehensive Motor Management Plan, http://www.motorsmatter. org/tools/mpkv21.pdf. 2007. [35] Xenergy. Evaluation of the motor challenge program. Oak Ridge, Tennessee: U.S: Department of Energy and Oak Ridge National Laboratory; 2000. http:// www.unido.org/fileadmin/import/userfiles/timminsk/usdoe_ motorchallengeprogram_evaluation.pdf.
Contents lists available at ScienceDirect
Energy journal homepage: www.elsevier.com/locate/energy
Energy consumption, energy saving and emission reduction of a garment industrial building in Bangladesh Mohammad Ahsan Habib a, M. Hasanuzzaman b, *, M. Hosenuzzaman b, Asif Salman a, Md Riyad Mehadi a a b
Department of Mechanical and Chemical Engineering (MCE), Islamic University of Technology (IUT), Board Bazar, Gazipur, 1704, Dhaka, Bangladesh UM Power Energy Dedicated Advanced Center, Level 4, Wisma R&D, University of Malaya, 59990, Kuala Lumpur, Malaysia
a r t i c l e i n f o
a b s t r a c t
Article history: Received 15 December 2015 Received in revised form 9 June 2016 Accepted 12 June 2016
The industrial sector is the biggest energy consumer in Bangladesh. Electric motors account for more than 45% of the electricity consumption in the industrial sector in the country. A walk through energy audit has been conducted at Garments in Bangladesh to identify the energy using equipment and energy consumption breakdown. Different energy saving strategies and emissions reduction has been estimated for the garment. It is also found that about 137,003 kWh, 319,673 kWh and 502,343 kWh of energy and BDT 1,312,484, BDT 3,062,463 and BDT 4,812,442 of bill savings for 20%, 40% and 60% speed reduction by using variable speed drive (VSD) respectively. By using high efficiency motors (HEM), about 28,311 kWh, 41,713 kWh and 57,080 kWh of energy and BDT 271,242, BDT 399,574 and BDT 546,852 of bill can be saved for motor loadings of 50%, 75% and 100% respectively. The payback periods of different energy saving strategies indicated that HEMs seems cost-effective. Both HEMS and VSD more cost effective for large motors. It is also found that huge amount of emissions can be reduced for different energy saving strategies applied in garment. © 2016 Elsevier Ltd. All rights reserved.
Keywords: Energy Energy consumption Energy savings Emission reduction Garments building
1. Introduction Energy is one of the crucial factors for continuous development and economic growth. Economy growth is closely related with growth in its energy consumption, particularly in the case of developing countries [1]. The energy consumption will increase by 33% from 2010 to 2030 in the world [2,3]. The world power demand rises from 145 billion MW in 2007 to 218 billion MW in 2035 (i.e., increases by 49%). Energy efficiency improvement is one of the most important functions to reduce energy consumption. Energy efficiency improvement is the main objective of many national energy policies [4]. Monitoring of the energy consumption and developments in energy efficiency is necessary in order to check and apply desired policies. About 35% of world's total energy is used in industrial sectors [5]. Electricity demand in Bangladesh is currently increasing by more than 8% annually. The demand is projected to be 22,500 MW in 2021 where more than 40% of the
* Corresponding author. E-mail addresses: (M. Hasanuzzaman).
[email protected],
http://dx.doi.org/10.1016/j.energy.2016.06.062 0360-5442/© 2016 Elsevier Ltd. All rights reserved.
[email protected]
energy is consumed in the industrial sector in Bangladesh [6,7]. It is also expected that the share of the industrial sector be augmented in the future. Bangladesh is one of the fastest-growing ready-made garment (RMG) exporters in the world where the garment buildings consumed huge amount of energy. Nguyen et al. [8] reviewed the optimization methods for building performance and found location, design and operating parameters have great influence on building performance. Li and Wen [9] reviewed and discussed the different model-based optimal control methods to reduce building energy cost and found the better control and operation strategies can improve building energy efficiency. Garment factories have several energy intensive operations and energy cost on average is about 16.7% (i.e. varying from 6% to 60%) of production costs in Cambodia in 2010 [10]. Nguyen [11] also found the energy cost about 10e15% of the production cost and energy waste about 20e32% due to old technologies and outdated energy management systems. The author also mentioned energy saving potential about up to 30% in garment industry where HEMs and VSD are promising to invest. Unfortunately, this sector mostly uses standard motor, instead of HEMs. The implementation of VSD and HEMs not only save energy but also reduce emissions. Thailand and the Philippines are leading to develop the national standards of energy
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conservation [12]. Brazil has introduced a HEMs policies to reduce energy consumption and found that with the current average tariffs of electricity, HEMs are economical than standard motors [13]. In Europe, electric motors use about 70% of the industrial electricity used where HEMs can significantly reduce energy used and environmental impact [14]. Bortoni [15] found that about 44% of motors operate at 40% or less of the full load capacities in the US in the industries [16]. Normally, load factors for most motors in buildings and industrial facilities range from 50% to 70% [17]. So, the VSDs in electric is a potential solution to reduce energy consumption as well as emission reduction. The aim of this study is to analyze the energy consumption, energy savings, bill savings and payback period and emissions reductions by using VSD and HEMs in the garment. 2. Methodology 2.1. Data collection and characteristics of the garment A walk through energy audit was conducted in Kojima Lyric Garments, Bangladesh. The survey investigated total energy consumption, types of energy supply, types of equipment and energy consumption and usage behaviour. To do the survey, a detailed preparation was taken and made a meeting with the appropriate personnel to set a specific questioners and visited floor by floor under the supervision of authority of the seven storied building with an underground level. 1st floor contains accounts and administrative office, child care room, medical center, cutting section, quick-checking section and some essential electrical equipment like boiler, generator and pump. The 2nd floor contains spot removing room, quality control room, processing and packing section and the office room for Japanese AGM. 3rd floor contains work station for both usual clothing as well as raincoats. The production of raincoat runs only for a few months of a year. Floors 4e6 are similar and contain gaze pattern room, sewing floor, and store room. Floor 7th consists of sample and CAD room, water treatment plant, cafeteria, prayer room and store room. The equipment are divided into 3 groups such as lights, motors and other appliances. Tables 1e3 show the details of the type, number, operating hours of energy consuming equipment in the garment.
Table 2 Number of electric motors, capacity and operating hours in 2014. Machine
Power (W)
Quantity
Operating hour (h/y)
Lay Hook and bar Heat transfer Needle detector PP belt Button hole APW CAD Hand Stitch Overload Pintap Repeat button Zigzac Auto plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind Stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron Table Saddle stitch Tonton Vertical plane Vortex Spot remover WinDa Fabric inspection Bend knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
90 150 150 150 150 300 350 400 400 400 400 400 450 500 500 500 550 550 550 550 550 550 550 550 550 550 550 550 550 550 1000 1000 1020 1120 1500 2000 3000 3240 4000 4103 7460 12,000 35,000
4 2 3 1 1 5 7 3 3 66 4 1 1 380 7 15 8 14 8 18 3 5 19 7 3 217 1 3 14 11 1 1 1 7 1 1 1 5 2 1 1 6 1
2250 1875 1500 1500 2250 1875 1875 1875 225 1875 1875 112.5 1875 1875 600 1875 1875 1875 1875 1875 1875 1875 1875 1875 1875 1250 1875 225 1875 1750 1000 1000 1000 1750 1000 600 600 600 1750 500 500 1750 1000
Table 3 Number of machine/equipment, capacity and operating hours in 2014.
2.2. Mathematical formulation Annual energy consumption by electric equipment can be calculated using Equation (1) [18,19].
AEC ¼ C hr L 0:001
(1)
where AEC ¼ annual energy consumption (kWh), C ¼ rated power, L ¼ load factor, hr ¼ yearly usage hours. Electric motors efficiency over 90% at the rated loads and very inefficient when running on part loads. Motors are more efficient at 75% of rated load and above where very inefficient when operated at lower than 50% of rated load. Many industrial sectors uses oversize motors to meet extra load demand and load also varies during operation that causes motors to work at low load and inefficiency [20]. VSD optimize the voltage and frequency supply to
Table 1 Number and types of lights, capacity and operating hours in 2014. Type
Quantity
Power (W)
Operating hours (h/y)
Tube light (single) Tube light (double) Energy saving bulb
2272 177 96
20 40 20
3000 3000 3000
Machine
Power(W)
Quantity
Operating hour (h/y)
Air compressor Boiler Lift (goods) Lift (passenger) Fridge (8.5 cft) Fridge (10 cft) Fan Exhaust fan (big) Exhaust fan (small) Stand fan Computer Laptop A/C 4.5 Ton A/C 2 Ton Window A/C
11,000 536 11,000 5500 330 610 70 210 90 350 200 150 5200 2100 1900
1 2 1 1 1 1 520 26 5 8 28 12 3 14 2
1500 1750 250 500 2920 2920 2640 3000 3000 1560 3000 2000 1080 1080 1080
the motor to match the speed for actual load demand [21]. The variable speed drives are good candidates to match the required load to work efficiently and to save energy [18]. Properly designed VSD systems can typically save energy consumption by 20%e70% [21]. Energy savings with the application of variable speed drive can be estimated as following equation (3) [18,20,22]. Percentage of
M.A. Habib et al. / Energy 112 (2016) 91e100 Table 4 Percentage energy savings using speed reduction.
Table 8 Annual energy consumption and bill for electrical motors in 2014.
Average speed reduction (%)
Potential energy saving, SSR
20 40 60
15 35 55
(%)
energy saving with speed reduction data has been directly taken from Refs. [18,20,22] that is shown in Table 4.
AESVSD ¼ W Havgusage SSR
(2)
where AESVSD ¼ annual energy saving using VSD (kWh), W ¼ Motor rated power, Haverage ¼ average yearly usage hours, Ssr ¼ percentage energy savings using speed reduction. Energy savings by using Variable speed drive or controlling speed reduction has been calculated at different speed reduction (%). High efficiency motors are more efficient than the standard motor where the typically cost 10e25% more than standard motor [18,23]. Annual energy saving by replacing standard efficient motors with high efficiency motors (HEM) can be estimated by using the following equation and efficiency related data has been taken from Table 5 [23,24]:
AESHEM ¼ W L hr
1 1 Estd Eee
100
(3)
where AES ¼ annual energy saving (kWh), W ¼ motor rated power (W), L ¼ load factor (%), hr ¼ yearly usage hours, Estd ¼ efficiency of standard motor (%), Eee ¼ efficiency of energy efficient motor (%). Table 5 Efficiency of various standard motors and energy efficient motors. Power (W)
1120 1500 2000 3000 3240 4000 4103 7460 12,000
Load (50%)
Load (75%)
Load (100%)
Estd
Eee
Estd
Eee
Estd
Eee
76.04 77.2 77.66 81.07 81.07 81.09 81.15 84.32 84.97
80.06 80.02 82.29 83.69 83.93 84.26 84.35 86.9 88.61
78.03 79.29 79.71 82.39 83.53 84.12 84.73 86.3 86.45
82.28 83.07 84.44 85.25 85.86 86.07 86.5 88.87 89.85
78.5 81 81.33 82.9 83.57 84.67 85.3 85.2 87.94
82.55 83.55 85 85.96 86.38 87.6 87.75 90.1 90.56
Table 6 Emission factor per unit energy use for various fuels. Fuels
Coal Petroleum Natural gas Hydro
93
Machine
Energy consumption (kWh)
Energy bill (BDT)
Lay Hook and bar Heat transfer Needle detector PP belt Button hole APW CAD Hand Stitch Overload Pintap Repeat Button Zigzac Auto Plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind Stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron Table Saddle stitch Tonton Vertical plane Vortex Spot remover WinDa Fabric inspection Bend knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging Total
810 563 675 225 338 2813 4594 2250 270 49,500 3000 45 844 356,250 2100 14,063 8250 14,438 8250 18,563 3094 5156 19,594 7219 3094 149,188 1031 371 14,438 10,588 1000 1000 1020 13,720 1500 1200 1800 9720 14,000 2052 3730 126,000 35,000 913,350
7760 5389 6467 2156 3233 26,944 44,008 21,555 2587 474,210 28,740 431 8083 341,2875 20,118 134,719 79,035 138,311 79,035 177,829 29,638 49,397 187,708 69,156 29,638 1,429,216 9879 3557 138,311 101,428 9580 9580 9772 131,438 14,370 11,496 17,244 93,118 134,120 19,653 35,733 1,207,080 335,300 8,749,895
Annual bill saving for using VSD or energy efficient motor can be calculated by using the following equation:
ABS ¼ AES c
(4)
Table 9 Annual energy consumption and bill for other appliances in 2014.
Emission factors (kg/kWh) CO2
SO2
CO
1.18 0.85 0.53 0
0.0139 0.0164 0.0005 0
0.002 0.002 0.005 0
Table 7 Annual energy consumption and bill for lights in 2014. Type
Energy consumption (kWh)
Energy bill (BDT)
Tube light (single) Tube light (double) Energy saving bulb Total
136,320 21,240 5760 163,320
1,305,946 203,479 55,181 1,564,606
Machine
Energy consumption (kWh)
Energy bill (BDT)
Air compressor Boiler Lift (goods) Lift (passenger) Fridge (8.5 cft) Fridge (10 cft) Fan Exhaust fan (big) Exhaust fan (small) Stand fan Computer Laptop A/C 4.5 Ton A/C 2 Ton Window A/C Total
16,500 1876 2750 2750 964 1781 96,096 16,380 1350 4368 16,800 3600 16,848 31,752 4104 217,919
158,070 17,972 26,345 26,345 9231 17,064 920,600 156,920 12,933 41,845 160,944 34,488 161,404 304,184 39,316 2,087,662
94
M.A. Habib et al. / Energy 112 (2016) 91e100
Simple payback period has been calculated by using following equation:
PBP ¼
Fig. 1. Percentage of energy consumption by the different types of appliances.
where ABS ¼ annual bill saving, AES ¼ annual energy saving, c ¼ average energy cost (BDT/kWh).
IC ABS
(5)
where ABS ¼ annual bill saving (BDT), AES ¼ annual energy saving (kWh), IC ¼ incremental cost (BDT). It is known that emission of greenhouse gases (GHGs) (i.e. CO2, SO2, CO) are emitted when fossil fuels are burned [25]. The amount of GHGs reduction for energy savings strategies in this garment is based on the percentages of the generation of electricity from different fuels mix, emission factors for power generation of power plant for the specific fuels and percentages of electricity generated by each type of fuels (i.e. coal, petroleum, natural gas etc.) [18,25]. Emission reductions associated with energy savings strategies are estimated based on fuel type, percentage of electricity generated by the specific fuel and the emission factor of fuels to produce the electricity by using equation (6) [18,25,26]. The emission factor per unit electricity generation for various fuels has been considered same as Malaysian power plant emissions factor that has been taken from Refs. [18,20] and shown in Table 6. The fuel mix electricity generation of Bangladesh has been taken from the presentation of Secretary Power Division in a Seminar in Dhaka, March
Table 10 Energy and bill saving using VSD at certain speed reduction. Machine
Lay Hook and bar Heat transfer Needle detector PP belt Button hole APW CAD Hand stitch Overload Pintap Repeat button Zigzac Auto plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron table Saddle stitch Tonton Vertical plane Vortex Spot remover WinDa Fabric inspection Bend Knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
Annual energy saving (kWh) for speed reduction
Annual bill saving (BDT) for speed reduction
20%
40%
60%
20%
40%
60%
122 84 101 34 51 422 689 338 41 7425 450 7 127 53,438 315 2109 1238 2166 1238 2784 464 773 2939 1083 464 22,378 155 56 2166 1588 150 150 153 2058 225 180 270 1458 2100 308 560 18,900 5250
284 197 236 79 118 984 1608 788 95 17,325 1050 16 295 124,688 735 4922 2888 5053 2888 6497 1083 1805 6858 2527 1083 52,216 361 130 5053 3706 350 350 357 4802 525 420 630 3402 4900 718 1306 44,100 12,250
446 309 371 124 186 1547 2527 1238 149 27,225 1650 25 464 195,938 1155 7734 4538 7941 4538 10,209 1702 2836 10,777 3970 1702 82,053 567 204 7941 5823 550 550 561 7546 825 660 990 5346 7700 1128 2052 69,300 19,250
1164 808 970 323 485 4042 6601 3233 388 71,132 4311 65 1212 511,931 3018 20,208 11,855 20,747 11,855 26,674 4446 7410 28,156 10,373 4446 214,382 1482 533 20,747 15,214 1437 1437 1466 19,716 2156 1724 2587 13,968 20,118 2948 5360 18,1062 50,295
2716 1886 2263 754 1132 9430 15,403 7544 905 165,974 10,059 151 2829 1,194,506 7041 47,152 27,662 48,409 27,662 62,240 10,373 17,289 65,698 24,204 10,373 500,226 3458 1245 48,409 35,500 3353 3353 3420 46,003 5030 4024 6035 32,591 46,942 6879 12,507 422,478 117,355
4268 2964 3557 1186 1778 14,819 24,204 11,855 1423 260,816 15,807 237 4446 1,877,081 11,065 74,095 43,469 76,071 43,469 97,806 16,301 27,168 103,239 38,036 16,301 786,069 5434 1956 76,071 55,786 5269 5269 5374 72,291 7904 6323 9484 51,215 73,766 10,809 19,653 663,894 184,415
M.A. Habib et al. / Energy 112 (2016) 91e100
95
Table 11 Payback periods by using VSD at a certain speed reduction. Machine
Power (W)
Lay Hook and Bar Heat Transfer Needle Detector PP belt Button hole APW CAD Hand Stitch Overload Pintap Repeat Button Zigzac Auto Plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind Stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron Table Saddle stitch Tonton Vertical Plane Vortex Spot Remover WinDa Fabric Inspection Bend Knife Spot Remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
90 150 150 150 150 300 350 400 400 400 400 400 450 500 500 500 550 550 550 550 550 550 550 550 550 550 550 550 550 550 1000 1000 1020 1120 1500 2000 3000 3240 4000 4103 7460 12,000 35,000
Incremental cost (BDT)
134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 134,400 141,120 141,120 141,120 165,375 165,375 225,057 280,623 798,231
Payback period (y) 20%
40%
60%
461.9 332.5 415.7 415.7 277.1 166.3 142.5 124.7 1039.2 124.7 124.7 2078.4 110.8 99.8 311.8 99.8 90.7 90.7 90.7 90.7 90.7 90.7 90.7 90.7 90.7 136.0 90.7 755.8 90.7 97.2 93.5 93.5 91.7 47.7 62.4 81.8 54.6 50.5 16.4 56.1 42.0 9.3 15.9
197.9 142.5 178.1 178.1 118.8 71.3 61.1 53.4 445.4 53.4 53.4 890.7 47.5 42.8 133.6 42.8 38.9 38.9 38.9 38.9 38.9 38.9 38.9 38.9 38.9 58.3 38.9 323.9 38.9 41.6 40.1 40.1 39.3 20.5 26.7 35.1 23.4 21.7 7.0 24.0 18.0 4.0 6.8
126.0 90.7 113.4 113.4 75.6 45.3 38.9 34.0 283.4 34.0 34.0 566.8 30.2 27.2 85.0 27.2 24.7 24.7 24.7 24.7 24.7 24.7 24.7 24.7 24.7 37.1 24.7 206.1 24.7 26.5 25.5 25.5 25.0 13.0 17.0 22.3 14.9 13.8 4.5 15.3 11.5 2.5 4.3
EMi ¼ EPi (PEi1 Em1p þ PE2i Em2pþ PE3i Em3pþ … … … PEni Emnp)
(6)
where Emi ¼ total amount of emission (ton), Epi ¼ electricity production in the year i, PEin ¼ percentage of electricity generation in a year i of fuel type n recommended, Empn ¼ fossil fuel emission for a unit of electricity generation of fuel type n. 3. Results and discussion 3.1. Energy consumption and annual bills
Fig. 2. Annual energy and bill saving by using VSD.
2015. According to the presentation, fuel mix electricity generation are about 2%, 29%, 62%, 2% from coal, petroleum, natural gas, hydro respectively [27].
Energy consumption data has been collected by a walk through energy audit in Kojima Lyric Garments, Bangladesh. The survey investigated and collected types of equipment, number of equipment, rating of each equipment for energy consumption, usage behaviour etc. Energy consumption of equipment's has been calculated by using Equation (1) and data from Tables 1e3 that are shown in Tables 7e9. The percentage of energy consumption by the different types of appliances are shown in Fig. 1. Energy bill has been calculated based on the energy consumption and unit energy cost. Table 7 shows that lights consume about
96
M.A. Habib et al. / Energy 112 (2016) 91e100
Table 12 Energy and bill savings by using HEMs at different loadings. Machine
Lay Hook and bar Heat transfer Needle detector PP belt Button hole APW CAD Hand stitch Overload Pintap Repeat button Zigzac Auto Plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron table Saddle stitch Tonton Vertical plane Vortex Spot remover WinDa Fabric inspection Bend knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
Annual energy saving (kWh) for loading
Annual bill saving (BDT) for loading
50%
75%
100%
50%
75%
100%
27 19 22 7 11 93 152 74 9 1634 99 1 28 11,762 69 464 272 477 272 613 102 170 647 238 102 4926 34 12 477 350 33 33 34 453 46 43 35 321 462 68 114 2218 1288
40 28 34 11 17 140 228 112 13 2458 149 2 42 17,687 104 698 410 717 410 922 154 256 973 358 154 7407 51 18 717 526 50 50 51 681 74 60 55 299 430 63 115 3873 1076
51 35 42 14 21 176 287 141 17 3094 187 3 53 22,265 131 879 516 902 516 1160 193 322 1225 451 193 9324 64 23 902 662 62 62 64 857 94 75 112 607 875 128 233 7875 2187
256 178 214 71 107 890 1453 712 85 15,657 949 14 267 112,683 664 4448 2610 4567 2610 5871 979 1631 6198 2283 979 47,189 326 117 4567 3349 316 316 323 4340 439 416 333 3074 4428 649 1092 21,251 12,341
385 268 321 107 161 1338 2185 1070 128 23,543 1427 21 401 169,440 999 6688 3924 6867 3924 8829 1471 2452 9319 3433 1471 70,957 490 177 6867 5036 476 476 485 6526 713 571 530 2862 4123 604 1098 37,104 10,307
485 337 404 135 202 1684 2750 1347 162 29,637 1796 27 505 213,299 1257 8420 4940 8644 4940 11,114 1852 3087 11,731 4322 1852 89,324 617 222 8644 6339 599 599 611 8215 898 718 1078 5820 8382 1228 2233 75,440 20,956
163,320 kWh (about 13% of total energy consumption, Fig. 1) energy and energy bill about BDT 1,564,606. It is also shown that single tube lights are the major energy consumer in the garment where consume about 136,320 kWh (83% of total lighting) energy and energy bill about BDT 1,305,946. Table 8 shows that electric motors are the major energy consumer and consume about 913,350 kWh (about 70% of total energy consumption, Fig. 1) energy and energy bill about BDT 8,749,895. From Table 9, it is found that others appliances consume about 21, 7919 kWh (about 17% of total energy consumption, Fig. 1) energy and energy bill about BDT 2,087,662. 3.2. Energy savings, bill savings and payback period by using variable speed drive Electric motors are efficient at 75% of rated load and above where very inefficient at lower than 50% of rated load due to the reactive current increase, power factors etc [28]. In such cases, variable speed drive can be the potential candidates to match the load requirements and consequently save a huge amount of energy, lower utility bills and protect the environment from harmful
pollutants [22]. Energy savings of electric motors have been calculated by using Equation (2) and data from Tables 2 and 4 that are shown in Table 10. Energy bill savings and payback period of electric motors have been calculated by using Equations (4) and (5) that are shown in Tables 10 and 11. Fig. 2 shows the total annual energy and bill savings by using VSD. From Fig. 2, it is found that about 137,003 kWh, 319,673 kWh and 502,343 kWh of energy can be saved for a 20%, 40% and 60% speed reduction by using a variable speed drive respectively. It is also found that the energy saving is high at the higher percentage of speed reduction. The annual bill savings for the energy savings of BDT 1,312,484, BDT 3,062,463 and BDT 4,812,442 for 20%, 40% and 60%, respectively. Fig. 2 also shows that energy and bill savings increase with increases the percentage of motor speed reduction. From Table 11, it is found that payback periods are shorter for a higher percentage of speed reduction (for example 60% speed reduction). It also found that payback periods are shorter for larger motors (i.e. 4 kW and above) that also depend on the operating hours. Saidur et al. [18] found that the payback periods for using a variable speed drive for larger motors (i.e. about 7.5 kW and above) are reasonable (i.e. within 1e3 years).
M.A. Habib et al. / Energy 112 (2016) 91e100
97
Table 13 Payback period for replacing by HEMs. Machine
Power (W)
Lay Hook and Bar Heat Transfer Needle Detector PP belt Button hole APW CAD Hand Stitch Overload Pintap Repeat Button Zigzac Auto Plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind Stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron table Saddle stitch Tonton Vertical plane Vortex Spot remover WinDa Fabric inspection Bend knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
90 150 150 150 150 300 350 400 400 400 400 400 450 500 500 500 550 550 550 550 550 550 550 550 550 550 550 550 550 550 1000 1000 1020 1120 1500 2000 3000 3240 4000 4103 7460 12,000 35,000
Incremental cost (BDT)
1000 1000 1000 1000 1000 1000 1000 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1680 1806 4032 4200 4578 4578 4578 6500 7000 17,000
Payback period (y) 50% load
75% load
100% load
15.6 11.2 14.1 14.1 9.4 5.6 4.8 7.1 59.0 7.1 7.1 118.0 6.3 5.7 17.7 5.7 5.2 5.2 5.2 5.2 5.2 5.2 5.2 5.2 5.2 7.7 5.2 42.9 5.2 5.5 5.3 5.3 5.2 2.7 4.1 9.7 12.6 7.4 2.1 7.1 6.0 2.0 1.4
10.4 7.5 9.3 9.3 6.2 3.7 3.2 4.7 39.2 4.7 4.7 78.5 4.2 3.8 11.8 3.8 3.4 3.4 3.4 3.4 3.4 3.4 3.4 3.4 3.4 5.1 3.4 28.5 3.4 3.7 3.5 3.5 3.5 1.8 2.5 7.1 7.9 8.0 2.2 7.6 5.9 1.1 1.6
8.2 5.9 7.4 7.4 4.9 3.0 2.5 3.7 31.2 3.7 3.7 62.4 3.3 3.0 9.4 3.0 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 4.1 2.7 22.7 2.7 2.9 2.8 2.8 2.8 1.4 2.0 5.6 3.9 3.9 1.1 3.7 2.9 0.6 0.8
Table 12. Energy bill savings and payback period of electric motors have been calculated by using Equations (4) and (5) that are shown in Table 13. Fig. 3 shows the total annual energy and bill savings. From Fig. 3, it is found that 28,311 kWh, 41,713 kWh and 57,080 kWh of energy can be saved for motor loadings of 50%, 75% and 100%, respectively. This will translate into bill savings of BDT 271,242, BDT 399,574 and BDT 546,852 for motor loadings of 50%, 75% and 100% respectively. Fig. 3 also shows that energy and bill savings increase with increases the percentage of motor loading. The payback period of the HEM varies from motor to motor depends on capacity and operation hours that are less than 6 years for capacity more than 500 W motors in most of the cases. Even the PBPs are less than 1 year for some of the motors with higher capacity and higher operating load. Fig. 3. Annual energy and bill savings by using HEMs.
3.3. Energy savings, bill savings and payback period by using high efficiency motor Energy savings of electric motors have been calculated by using Equation (3) and data from Tables 2 and 5 that are shown in
3.4. Comparison the effectiveness of common energy saving measure Energy conservation and management are very important because of the energy consumption has direct social, economic and environmental impacts. Energy efficient use and energy savings in the end-use section are the easiest ways to reduce costs in any
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M.A. Habib et al. / Energy 112 (2016) 91e100
organization. Using best practice methodologies and proper energy management can reduce costs, lower emissions and increase profitability [21]. Electric motor is one of the major energy consumer in any commercial and industrial sectors. These PBPs indicate the implementation of energy-efficient motors seems very cost-effective as their PBPs are less than one-third of the motor life (if an average motor life of 20 years is considered) particularly for large motors. Energy efficient also depends on operating conditions. The energy efficiency motors are most cost effective when replacing motors with operation more than 2000 h annually [29]. This analysis found that the PBPs of VSD varies from motor to motor depends on capacity and operation hours. Most of the cases, the PBPs are more than 10 years for capacity less than 7.5 kW motors. But the PBPs are less than 10 years for some of the motors with higher capacity and higher operating load. Tolvanen [30,31] found that VSD is not cost effect for smaller motor. Saidur [20] found also that VSD is cost effect for motor capacity more 10 kW at higher speed reduction. This analysis found that the PBPs of HEM varies from motor to motor depends on capacity and operation hours. Most of the cases, the PBPs are less than 6 years for capacity more than 500 W motors. Even the PBPs are less than 1 years for some of the motors with higher capacity and higher operating load. According to the Copper
Development Association, the HEMs replacement compared to the minimum motors efficiency have PBPs of less than 15 months for 37.3 kW (50 hp) motors [29,32]. Saidur [20], Hasanuzzaman et al. [24] and Almeida et al. [33] also analyzed the energy savings, costeffectiveness and found that HEM is cost effective. Many end users routinely replace failed motors rated up to 75 kW with HEMs [21]. In some cases, rewind of an existing HEM is cost effective compared to purchase a new motor [29,34]. An analysis also found that industrial end users rewind 40% of the motors that fail each year and the percentage of rewinding increases with increasing the capacity of the motors [35]. Hasanuzzman et al. [24] found about 81% of motors with more than 15 kW (20 hp) are rewound and the rewinding percentage increases with increasing motor's capacity. But if rewinding costs more than 60% of the new HEM, then better choice to buy new motor [29,34]. 3.5. Emission reduction By introducing high DSV, HEMs, and energy efficient light, not only saved energy, but also saved huge amount of emission of various gaseous pollutants. Emissions reduction have been calculated by using Equation (6) and energy savings data from Tables 10 and 12 that are shown in Tables 14 and 15. The emission reduction
Table 14 Emission reduction at a certain speed reduction for using VSD. Machine
20% SR emission reduction (Kg)
40% SR emission reduction (Kg)
60% SR emission reduction (Kg)
CO2
SO2
CO
CO2
SO2
CO
CO2
SO2
CO
Lay Hook and bar Heat transfer Needle detector PP belt Button hole APW CAD Hand stitch Overload Pintap Repeat button Zigzac Auto plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron table Saddle stitch Tonton Vertical plane Vortex Spot remover WinDa Fabric inspection Bend knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
7274 5052 6062 2021 3031 25,258 41,254 20,206 2425 444,535 26,942 404 7577 3,199,303 18,859 126,288 74,089 129,656 74,089 166,701 27,783 46,306 175,962 64,828 27,783 1,339,778 9261 3334 129,656 95,081 8981 8981 9160 123,212 13,471 10,777 16,165 87,290 125,727 18,423 33,497 1,131,543 314,318
65 45 54 18 27 225 368 180 22 3968 240 4 68 28,557 168 1127 661 1157 661 1488 248 413 1571 579 248 11,959 83 30 1157 849 80 80 82 1100 120 96 144 779 1122 164 299 10,100 2806
45 31 38 13 19 157 256 126 15 2762 167 3 47 19,879 117 785 460 806 460 1036 173 288 1093 403 173 8325 58 21 806 591 56 56 57 766 84 67 100 542 781 114 208 7031 1953
16,973 11,787 14,144 4715 7072 58,935 96,260 47,148 5658 1,037,248 62,864 943 17,680 7,465,041 44,004 294,673 172,875 302,531 172,875 388,968 64,828 108,047 410,577 151,265 64,828 3,126,149 21,609 7779 302,531 221,856 20,955 20,955 21,374 287,496 31,432 25,145 37,718 203,678 293,363 42,988 78,160 2,640,267 733,408
152 105 126 42 63 526 859 421 51 9258 561 8 158 66,633 393 2630 1543 2700 1543 3472 579 964 3665 1350 579 27,904 193 69 2700 1980 187 187 191 2566 281 224 337 1818 2619 384 698 23,567 6546
105 73 88 29 44 366 598 293 35 6445 391 6 110 46,384 273 1831 1074 1880 1074 2417 403 671 2551 940 403 19,424 134 48 1880 1378 130 130 133 1786 195 156 234 1266 1823 267 486 16,405 4557
26,672 18,522 22,227 7409 11,113 92,611 151,265 74,089 8891 1,629,961 98,786 1482 27,783 11,730,778 69,150 463,057 271,660 475,405 271,660 611,235 101,873 169,788 645,193 237,703 101,873 4,912,521 33,958 12,225 475,405 348,630 32,929 32,929 33,587 451,779 49,393 39,514 59,271 320,065 460,999 67,553 122,823 4,148,991 1,152,498
238 165 198 66 99 827 1350 661 79 14,549 882 13 248 104,709 617 4133 2425 4243 2425 5456 909 1516 5759 2122 909 43,849 303 109 4243 3112 294 294 300 4033 441 353 529 2857 4115 603 1096 37,034 10,287
166 115 138 46 69 575 940 460 55 10,128 614 9 173 72,889 430 2877 1688 2954 1688 3798 633 1055 4009 1477 633 30,524 211 76 2954 2166 205 205 209 2807 307 246 368 1989 2864 420 763 25,780 7161
M.A. Habib et al. / Energy 112 (2016) 91e100
99
Table 15 Emission reduction at a certain loading by using HEMs. Machine
Lay Hook and bar Heat transfer Needle detector PP belt Button hole APW CAD Hand Stitch Overload Pintap Repeat Button Zigzac Auto plain Stopper Shearing ABLE pad joint ABLE sleeve joint ABLE vertical Blind stitch Button stitch Double needle (angular) Double needle (fixed bar) Eyelet hole Fladlock loop Iron table Saddle stitch Tonton Vertical plane Vortex Spot Remover WinDa Fabric inspection Bend knife Spot remover Hydarulic Hydraulic Cintel Fusion Pump (sub-mersible) Pump Fusion Sponging
50% load emission reduction (kg)
75% load emission reduction (kg)
100% load emission reduction (kg)
CO2
SO2
CO
CO2
SO2
CO
CO2
SO2
CO
16 11 13 4 7 56 91 44 5 978 59 1 17 7042 42 278 163 285 163 367 61 102 387 143 61 2949 20 7 285 209 20 20 20 271 27 26 21 192 277 41 68 1328 771
0.1 0.1 0.1 0.0 0.1 0.5 0.8 0.4 0.0 8.7 0.5 0.0 0.1 62.9 0.4 2.5 1.5 2.5 1.5 3.3 0.5 0.9 3.5 1.3 0.5 26.3 0.2 0.1 2.5 1.9 0.2 0.2 0.2 2.4 0.2 0.2 0.2 1.7 2.5 0.4 0.6 11.9 6.9
0.1 0.1 0.1 0.0 0.0 0.3 0.6 0.3 0.0 6.1 0.4 0.0 0.1 43.8 0.3 1.7 1.0 1.8 1.0 2.3 0.4 0.6 2.4 0.9 0.4 18.3 0.1 0.0 1.8 1.3 0.1 0.1 0.1 1.7 0.2 0.2 0.1 1.2 1.7 0.3 0.4 8.3 4.8
24 17 20 7 10 84 137 67 8 1471 89 1 25 10,589 62 418 245 429 245 552 92 153 582 215 92 4434 31 11 429 315 30 30 30 408 45 36 33 179 258 38 69 2319 644
0.2 0.1 0.2 0.1 0.1 0.7 1.2 0.6 0.1 13.1 0.8 0.0 0.2 94.5 0.6 3.7 2.2 3.8 2.2 4.9 0.8 1.4 5.2 1.9 0.8 39.6 0.3 0.1 3.8 2.8 0.3 0.3 0.3 3.6 0.4 0.3 0.3 1.6 2.3 0.3 0.6 20.7 5.7
0.1 0.1 0.1 0.0 0.1 0.5 0.8 0.4 0.0 9.1 0.6 0.0 0.2 65.8 0.4 2.6 1.5 2.7 1.5 3.4 0.6 1.0 3.6 1.3 0.6 27.6 0.2 0.1 2.7 2.0 0.2 0.2 0.2 2.5 0.3 0.2 0.2 1.1 1.6 0.2 0.4 14.4 4.0
30 21 25 8 13 105 172 84 10 1852 112 2 32 13,330 79 526 309 540 309 695 116 193 733 270 116 5582 39 14 540 396 37 37 38 513 56 45 67 364 524 77 140 4715 1310
0.3 0.2 0.2 0.1 0.1 0.9 1.5 0.8 0.1 16.5 1.0 0.0 0.3 119.0 0.7 4.7 2.8 4.8 2.8 6.2 1.0 1.7 6.5 2.4 1.0 49.8 0.3 0.1 4.8 3.5 0.3 0.3 0.3 4.6 0.5 0.4 0.6 3.2 4.7 0.7 1.2 42.1 11.7
0.2 0.1 0.2 0.1 0.1 0.7 1.1 0.5 0.1 11.5 0.7 0.0 0.2 82.8 0.5 3.3 1.9 3.4 1.9 4.3 0.7 1.2 4.6 1.7 0.7 34.7 0.2 0.1 3.4 2.5 0.2 0.2 0.2 3.2 0.3 0.3 0.4 2.3 3.3 0.5 0.9 29.3 8.1
Fig. 4. Annual emission reduction by using VSD.
has been presented in Tables 14 and 15 for variable speed drive and high efficiency motors respectively. Figs. 4 and 5 show the annual emissions reduction for variable speed drive and high efficiency motors respectively. From Figs. 4 and 5, it is found that about 100,304.91 kg, 175,677.73 kg and 276,065 kg of CO2 emissions can
Fig. 5. Annual emission reduction by using HEMs.
be reduced by using a variable speed drive for 20%, 40% and 60% of motor speed reductions respectively. Similarly about 2431.5 kg, 3230.06 kg and 3679.31 kg of CO2 emissions can be reduced by using energy-efficient motors at 50%, 75% and 100% loadings respectively. Besides CO2, huge amount of SO2, CO can be reduced
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that is also shown in Figs. 4 and 5. Figs. 3 and 5 also show that emissions reduction increase with increases the percentage of speed reduction and motor loading. The coal will be the main fuel after 2015 because Bangladesh has finalized a plan to establish coalbased power plants (i.e. 1320 MW at Rampal, 1200 MW at Matarbari, 4800 MW 4 at Moheskhali, 1320 MW at Payra in Patuakhali) and agreements have also been signed to establish coal power plant to generate 1411 MW electricity under public-private partnership [27]. So, emissions reduction will be the one of the issue for sustainable environment in Bangladesh. 4. Conclusion Based on end-use energy breakdown, it is found that about 70% of energy consumption by electric motors. It is also found that about 137,003 kWh, 319,673 kWh and 502,343 kWh of energy and BDT 1,312,484, BDT 3,062,463 and BDT 4,812,442 of bill savings for 20%, 40% and 60% speed reduction by using variable speed drive respectively. The payback periods are shorter for a higher percentage of speed reduction (for example 60% speed reduction) for larger motors (i.e. 4 kW and above) that also depend on the operating hours. By using high efficiency motors, about 28,311 kWh, 41,713 kWh and 57,080 kWh of energy and BDT 271,242, BDT 399,574 and BDT 546,852 of bill can be saved for motor loadings of 50%, 75% and 100% respectively. These payback periods indicate the implementation of HEMs seems very cost-effective as their payback periods are less than one-third of the motor life especially for large motors. By using VSD, about 100,304.91 kg, 175,677.73 kg and 276,065 kg of CO2 emissions can be reduced for 20%, 40% and 60% of motor speed reductions respectively. Similarly about 2431.5 kg, 3230.06 kg and 3679.31 kg of CO2 emissions can be reduced by using energy-efficient motors at 50%, 75% and 100% loadings respectively. Acknowledgement The authors would like to acknowledge the financial support from the University Malaya Research Grant scheme (Project No: RP016A-15SUS) to carry out this research. References [1] Mathur R, Chand S, Tezuka T. Optimal use of coal for power generation in India. Energy Policy 2003;31(4):319e31. [2] Abdelaziz EA, Saidur R, Mekhilef S. A review on energy saving strategies in industrial sector. Renew Sustain Energy Rev 2011;15(1):150e68. [3] Hasanuzzaman M, Rahim NA, Hosenuzzaman M, Saidur R, Mahbubul IM, Rashid MM. Energy savings in the combustion based process heating in industrial sector. Renew Sustain Energy Rev 2012;16(7):4527e36. [4] Saidur R, Mahlia TMI, Hasanuzzaman M. Developing energy performance standard, label and test procedures and impacts analysis for commercial chillers. Energy Educ Sci Technol Part A Energy Sci Res 2011;27(1):175e90. [5] Gielen D, Taylor P. Indicators for industrial energy efficiency in India. Energy Build 2009;34(8):962e9. [6] IEEOCB. Industrial energy efficiency opportunities and challenges in Bangladesh. 2014. Final Report, http://www.adb.org/sites/default/files/ project-document/80742/45916-014-tacr-01.pdf. [7] Hasanuzzaman M, Al-Amin AQ, Khanam S, Hosenuzzaman M. Photovoltaic power generation and its economic and environmental future in Bangladesh. J Renew Sustain Energy 2015;7(1):013108.
[8] Nguyen AT, Reiter S, Rigo P. A review on simulation-based optimization methods applied to building performance analysis. Appl Energy 2014;113: 1043e58. [9] Li X, Wen J. Review of building energy modeling for control and operation. Renew Sustain Energy Rev 2014;37:517e37. [10] Energy efficiency NAMA in the garment industry in Cambodia. United Nations Development Programme; 2015. http://www.undp.org/content/dam/undp/ library/Environment%20and%20Energy/MDG%20Carbon%20Facility/NAMA% 20Final%20Cambodia%202.pdf? (09/06/2016). [11] Nguyen DAT. Energy efficiency in the food processing and garment sector in Vietnam. 2012. https://www.giz.de/fachexpertise/downloads/2012-en-thipep-informationswork-vietnam-enereff.pdf (09/06/2016). [12] Yanti PAA, Mahlia TMI. Considerations for the selection of an applicable energy efficiency test procedure for electric motors in Malaysia: lessons for other developing countries. Energy Policy 2009;37:3467e74. [13] Delgado MAP, Tolmasquim MT. Analysis of a feasible tariff policy for the introduction of high efficiency electric motors in Brazil. Energy Convers Manag 2002;43:827e44. [14] Almeida ATD, Ferreira FJTE, Fong JAC, Brunner CU. Electric motor standards, ecodesign and global market transformation. In: Industrial and commercial power systems technical conference, Clear water Beach, FL, USA; 2008. Article number 4606292. [15] Bortoni EDC. Are my motors oversized? Energy Convers Manage 2009;50(9): 2282e7. [16] Capehart BL, Turner WC, Kennedy WJ. Guide to energy management. fifth ed. The Fairmont Press; 2005. [17] Jayamaha L. Energy efficient building systems. McGraw Hill; 2008. [18] Saidur R, Hasanuzzaman M, Yogeswaran S, Mohammed HA, Hossain MS. An end-use energy analysis in a Malaysian public hospital. Energy 2010;35(12): 4780e5. [19] Saidur R, Sambandam M, Hasanuzzaman M, Devaraj D, Rajakarunakaran S, Islam MD. An energy flow analysis in a paper-based industry. Clean Technol Environ Policy 2012;14(5):905e16. [20] Saidur R. Energy consumption, energy savings, and emission analysis in Malaysian office buildings. Energy Policy 2009;37(10):4104e13. [21] Siemens. Energy saving technology to deliver the fastest returns. 2011. Top 10 energy saving options, https://w3.siemens.co.uk/home/uk/en/aboutus/ Documents/Top10_energy_saving%20options_0911UK.pdf. [22] Saidur R, Rahim NA, Hasanuzzaman M. A review on compressed-air energy use and energy savings. Renew Sustain Energy Rev 2010;14(4):1135e53. [23] Garcia AGP, Szklo AS, Schaeffer R, McNeil MA. Energy-efficiency standards for electric motors in Brazilian industry. Energy Policy 2007;35(6):3424e39. [24] Hasanuzzaman M, Rahim NA, Saidur R, Kazi SN. Energy savings and emissions reductions for rewinding and replacement of industrial motor. Energy 2011;36(1):233e40. [25] Saidur R, Hasanuzzaman M, Mahlia TMI, Rahim NA, Mohammed HA. Chillers energy consumption, energy savings and emission analysis in an institutional buildings. Energy 2011;36(8):5233e8. [26] Mahlia TMI. Emissions from electricity generation in Malaysia. Renew Energy 2002;27(2):293e300. [27] Sufi S. Budget 2015-2016, allocation energy & power sectors. 2015. http:// www.en.banglanews24.com/fullnews/bn/111543.html (5 June 2015). [28] Kaya D, Yagmur EA, Yigit KS, Kilic FC, Eren AS, Celik C. Energy efficiency in pumps. Energy Convers Manag 2008;49(6):1662e73. [29] Hasanbeigi A. Energy-efficiency improvement opportunities for the textile industry. 2010. https://www.energystar.gov/sites/default/files/buildings/ tools/EE_Guidebook_for_Textile_industry.pdf. [30] Tolvanen J. LCC approach for big motor-driven systems savings. World Pumps 2008;2008(506):24e7. [31] Tolvanen J. Saving energy with variable speed drives. World Pumps 2008;2008(501):32e3. [32] CDA. Copper development association, high-efficiency copper-wound motors mean energy and dollar savings. 2001. http://energy.copper.org/motorad. html. [33] Almeida AT, Fonseca P, Bertoldi P. Energy-efficient motor systems in the industrial and in the services sectors in the European Union: characterisation, potentials, barriers and policies. Energy 2003;28(7):673e90. [34] MDM. Motor decisions matter, consortium for energy efficiency (CEE). 2007. Motor Planning Kit, Version 2.1. Strategies, Tools, and Resources for Developing a Comprehensive Motor Management Plan, http://www.motorsmatter. org/tools/mpkv21.pdf. 2007. [35] Xenergy. Evaluation of the motor challenge program. Oak Ridge, Tennessee: U.S: Department of Energy and Oak Ridge National Laboratory; 2000. http:// www.unido.org/fileadmin/import/userfiles/timminsk/usdoe_ motorchallengeprogram_evaluation.pdf.