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In the Implementation of any electrical powergeneration project, the basic requirement is the totalelectrical energy demand estimation. In order to estimatethe total electrical energy demand, various methods canbe used but neither of those methods can give the exactdemand. Therefore approximate analysis of energydemand is always taken in to the consideration. In thisstudy three villages are selected in Rajasthan state andelectrical energy demand of those villages is estimated.For the estimation of energy demands two sources of dataare taken in to consideration. i.e. survey data and bill data.Survey data is collected by a quessionaire based surveyand bill data are taken from electricity DistributionCompany for the three selected village. On the basis ofthese two data, energy consumption parameters such asEnergy consumption of village in MWh annum, Energyconsumption of family in kWh annum, Per capita Energyconsumption in kWh annum, Energy consumption ofvillage in MWh month, Energy consumption of family inkWh month, Per capita Energy consumption inkWh month and Average Power in kW month arecalculated for each village .these energy consumptionparameters are calculated in both the cases i.e. by usingsurvey data and by using bill data, and comparison hasmade in tabular manner as well as graphical manner inorder to observe deviation between the parametersproperly Vikrram Singh Meena | Dr. G.D. Agrawal "Energy data collection by survey and its comparison with bill data" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: https://www.ijtsrd.com/papers/ijtsrd5903.pdf Paper URL: http://www.ijtsrd.com/engineering/electrical-engineering/5903/energy-data-collection-by-survey-and-its-comparison-with-bill-data/vikrram-singh-meena<br>
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International Research Research and Development (IJTSRD) International Open Access Journal International Open Access Journal International Journal of Trend in Scientific Scientific (IJTSRD) ISSN No: 2456 - 6470 | www.ijtsrd.com | Volume ISSN No: 2456 | www.ijtsrd.com | Volume - 2 | Issue – 1 Energy data collection by survey and its comparison with bill data Energy data collection by survey and its comparison with bill data Energy data collection by survey and its comparison with bill data Vikrram Singh Meena Centre for Energy and Environment, Malaviya National Institute of Technology, Jaipur National Institute of Technology, Jaipur, India Dr. G. D. Agrawal Agrawal Centre for Energy and Environment, Malaviya Centre for Energy and Environment, Malaviya Centre for Energy and Environment, Malaviya National Institute of Technology, Jaipur National Institute of Technology, Jaipur, India ABSTRACT In the Implementation of any electrical power generation project, the basic requirement is the total electrical energy demand estimation. In order to estimate the total electrical energy demand, various methods can be used but neither of those methods can give the exact demand. Therefore approximate analysis of energy demand is always taken in to the consideration. In this study three villages are selected in Rajasthan state and electrical energy demand of those villages is estimated. For the estimation of energy demands two sources of data are taken in to consideration. i.e. survey data and bill data. Survey data is collected by a quessionaire based survey and bill data are taken from electricity Distribution Company for the three selected village. On the basis of these two data, energy consumption parameters such as Energy consumption of village in MWh/annum, Energy consumption of family in kWh/annum, Per capita Energy consumption in kWh/annum, Energy consumption o MWh/month, Energy consumption of family in kWh/month, Per capita Energy consumption in kWh/month and Average Power in kW/month are calculated for each village .these energy consumption parameters are calculated in both the cases i.e. by using survey data and by using bill data, and comparison has made in tabular manner as well as graphical manner in order to observe deviation between the parameters properly. Bassi sub division of Jaipur district in Rajasthan (latitude 26˚83’N, longitude 76 In the Implementation of any electrical power generation project, the basic requirement is the total electrical energy demand estimation. In order to estimate the total electrical energy demand, various be used but neither of those methods can give the exact demand. Therefore approximate analysis of energy demand is always taken in to the consideration. In this study three villages are selected in Rajasthan state and electrical energy demand of lages is estimated. For the estimation of energy demands two sources of data are taken in to consideration. i.e. survey data and bill data. Survey data is collected by a quessionaire based survey and bill data are taken from electricity Distribution y for the three selected village. On the basis of these two data, energy consumption parameters such as Energy consumption of village in MWh/annum, Energy consumption of family in kWh/annum, Per capita Energy consumption in kWh/annum, Energy consumption of village in MWh/month, Energy consumption of family in kWh/month, Per capita Energy consumption in kWh/month and Average Power in kW/month are calculated for each village .these energy consumption parameters are calculated in both the cases i.e. by survey data and by using bill data, and comparison has made in tabular manner as well as graphical manner in order to observe deviation Bassi sub division of Jaipur district in Rajasthan 76˚05’E, altitude 351 m). Prasad et al. [1] showed an overview about the different facets of planning of various literatures. They showed the uncertainties, errors and risks which are involved in very well manner with the energy planning and continuously affecting the planning results. presented a study in which they s slow progress of renewable energy technologies based electrification. They suggested on the basis of literature reviewed on renewable energy based electrification that better coordination is very much required between the national leve regional agencies which are actively involved in the development and the implementation of renewable energy based electrification program. Peck [3] examined the potential of Biomass planning at regional level to support the Biomas national level, European Union target achievement and addressing the concerns which are involved with increased bio energy production. a study which investigated the commercial availability of the biomass from the agricult Punjab in order to generate power from distributed power generation facilities. He estimated the total production of crop generated residues which is 55.396 Mt. Out of this total crop residue around 40.17% which is 22.315 Mt is found to be used as biomass in power plants for the generation of electricity showed an overview about the different facets of planning of energy with the help of various literatures. They showed the uncertainties, errors and risks which are involved in very well manner with the energy planning and continuously affecting the planning results. Urmee et al. [2] presented a study in which they showed the reasons of slow progress of renewable energy technologies based electrification. They suggested on the basis of literature reviewed on renewable energy based electrification that better coordination is very much required between the national level agencies and regional agencies which are actively involved in the development and the implementation of renewable energy based electrification program. Kautto and examined the potential of Biomass planning at regional level to support the Biomass planning at national level, European Union target achievement and addressing the concerns which are involved with increased bio energy production. Singh [4] presented a study which investigated the commercial availability of the biomass from the agricultural activities in Punjab in order to generate power from distributed power generation facilities. He estimated the total production of crop generated residues which is 55.396 Mt. Out of this total crop residue around 40.17% which is 22.315 Mt is found to be surplus which can be used as biomass in power plants for the generation 1. INTRODUCTION Jhar, Mansarkheri and Khijooriya jatan selected villages for the study which are located in selected villages for the study which are located in Jhar, Mansarkheri and Khijooriya jatan are the three @ IJTSRD | Available Online @ www.ijtsrd.com @ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 1 | Nov-Dec 2017 Dec 2017 Page: 164
International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 Bhandari and Jana [5] presented the impacts of characteristics of individual rural households on the priority of electrical energy from solar energy based system. This study is based upon the rural energy survey which is conducted in a coastal village of Indian sundarban. Ishan and Pallav [6] evaluated the solar power generation based on concentrating technology (CSP), technically as well as financially in India. They concluded that CSP based power generation facilities are financial feasible for selected part of India like north-western part especially Rajasthan and Gujarat states. questionnaire based survey. In each village 50 households are selected in equal proportion of lower income group, moderate income group and higher income group in order to maintain reliability of the study and for better analysis and data is collected. The population related data of villages is also collected from Census Authority of the Rajasthan in which the population of the three villages is mentioned and tabulated in table-1. Table-1: Population data Particulars/Village Jhar Mansarkheri Khi. Jatan 198 943 2. DATA COLLECTION AND COMPARISION Energy consumption data of the villages Jhar, Mansarkheri and Khi.Jatan 757 4683 513 3662 Households Population is collected by Table-2:Energy data collected by Survey Village Jhar Mansarkheri Khi. Jatan Household No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Bi-monthly Avg 100 50 100 100 200 30 100 100 300 100 100 50 200 200 100 50 100 300 150 200 100 100 250 100 100 200 500 300 Monthly Avg 50 25 50 50 100 15 50 50 150 50 50 25 100 100 50 25 50 150 75 100 50 50 125 50 50 100 250 150 Annual Bi-monthly Avg 100 300 100 500 200 200 100 300 150 200 500 100 200 100 500 200 150 500 100 200 500 50 50 100 100 100 100 50 Monthly Avg 50 150 50 250 100 100 50 150 75 100 250 50 100 50 250 100 75 250 50 100 250 25 25 50 50 50 50 25 Annual Bi-monthly Avg 100 100 200 100 100 400 100 150 100 100 100 100 100 300 50 100 100 100 100 100 50 100 100 100 200 100 150 150 Monthly Avg 50 50 100 50 50 200 50 75 50 50 50 50 50 150 25 50 50 50 50 50 25 50 50 50 100 50 75 75 Annual 600 300 600 600 1200 180 600 600 1800 600 600 300 1200 1200 600 300 600 1800 900 1200 600 600 1500 600 600 1200 3000 1800 600 1800 600 3000 1200 1200 600 1800 900 1200 3000 600 1200 600 3000 1200 900 3000 600 1200 3000 300 300 600 600 600 600 300 600 600 1200 600 600 2400 600 900 600 600 600 600 600 1800 300 600 600 600 600 600 300 600 600 600 1200 600 900 900 @ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 1 | Nov-Dec 2017 Page: 165
International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 50 100 50 50 150 100 150 150 350 400 500 350 250 500 100 300 150 200 100 200 50 100 8630 172.6 130.66 27.90 25 50 25 25 75 50 75 75 175 200 250 175 125 250 50 150 75 100 50 100 25 50 4315 86.3 65.33 13.95 300 600 300 300 900 600 900 900 2100 2400 3000 2100 1500 3000 600 1800 900 1200 600 1200 300 600 51780 1035.6 783.95 167.40 100 100 100 50 50 300 150 50 150 100 400 50 150 1000 100 100 50 50 50 50 100 50 9050 181 92.85 25.36 50 50 50 25 25 150 75 25 75 50 200 25 75 500 50 50 25 25 25 25 50 25 4525 90.5 46.43 12.68 600 600 600 300 300 1800 900 300 900 600 2400 300 900 6000 600 600 300 300 300 300 600 300 54300 1086 557.12 152.13 100 150 100 150 300 100 400 300 200 100 50 100 100 50 100 100 100 100 100 100 100 100 6550 131 25.94 27.51 50 75 50 75 150 50 200 150 100 50 25 50 50 25 50 50 50 50 50 50 50 50 3275 65.5 12.97 13.75 600 900 600 900 1800 600 2400 1800 1200 600 300 600 600 300 600 600 600 600 600 600 600 600 39300 786 155.63 165.03 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 P Q R S P-Consumptions of 50 households in kWh, Q-kWh per family, R-Total consumption of village in MWh, S-Per capita consumption in kWh Table-3: Bill data for village Jhar Household No. Jan-Feb Mar-Apr May-Jun Jul-Aug Sep-Oct Nov-Dec Annual Monthly Avg 96 43 40 80 237 6 100 100 276 30 61 0 241 209 100 100 109 95 28 30 89 104 12 100 100 189 82 48 0 61 512 100 51 101 98 74 79 122 393 10 100 100 440 55 142 0 227 223 100 32 51 17 32 100 105 92 30 100 100 333 45 173 100 423 48 100 8 98 100 40 100 215 192 22 100 100 248 67 84 100 198 233 100 33 72 100 52 100 401 279 17 100 100 549 826 237 1 274 408 100 40 150 506 269 449 1012 1297 97 600 600 2035 1105 745 201 1424 1633 600 264 581 42.17 22.42 37.42 84.33 108.08 8.08 50.00 50.00 169.58 92.08 62.08 16.75 118.67 136.08 50.00 22.00 48.42 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 @ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 1 | Nov-Dec 2017 Page: 166
International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 100 97 42 117 9 193 31 109 88 254 228 32 100 5 36 137 0 100 114 253 126 79 174 105 403 82 219 100 343 100 63 68 44 5779 115.58 87.49 18.68 134 33 15 100 75 132 150 149 52 208 32 100 100 30 75 150 200 49 167 120 260 121 87 105 364 88 87 100 447 100 80 18 52 5682 113.64 86.03 18.37 100 40 117 117 100 524 108 164 324 1170 434 84 100 39 46 150 100 152 129 673 912 101 704 375 651 150 342 100 756 100 69 51 38 11266 225.32 170.57 36.42 400 186 198 117 100 211 9 41 303 873 233 27 100 3 33 150 115 299 127 242 586 111 470 387 339 47 80 255 97 75 82 45 100 8345 166.9 126.34 26.98 947 186 617 117 100 412 208 123 206 1124 150 52 100 35 134 150 99 225 150 597 391 100 219 339 1065 171 394 146 79 100 100 62 100 11002 220.04 166.57 35.57 350 216 54 117 100 406 84 153 141 713 1075 34 100 98 143 150 107 87 150 756 391 2400 462 257 411 210 237 108 117 100 1050 37 390 14938 298.76 226.16 48.29 2031 758 1043 685 484 1878 590 739 1114 4342 2152 329 600 210 467 887 621 912 837 2641 2666 2912 2116 1568 3233 748 1359 809 1839 575 1444 281 724 57012 1140.2 863.16 184.32 169.25 63.17 86.92 57.08 40.33 156.50 49.17 61.58 92.83 361.83 179.33 27.42 50.00 17.50 38.92 73.92 51.75 76.00 69.75 220.08 222.17 242.67 176.33 130.67 269.42 62.33 113.25 67.42 153.25 47.92 120.33 23.42 60.33 4751 95.02 71.93 15.36 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 P Q R S @ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 1 | Nov-Dec 2017 Page: 167
International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 Table-4: Bill data for village Mansarkheri Household No. Jan-Feb Mar-Apr May-Jun Jul-Aug Sep-Oct Nov-Dec Annual Monthly Avg 99 192 69 280 106 411 145 243 114 204 185 33 98 172 1494 128 302 583 100 251 395 92 52 96 87 152 63 91 27 65 150 42 28 379 80 5 180 15 380 74 156 85 95 82 23 95 42 99 131 149 282 123 214 79 152 92 183 596 10 459 31 187 133 240 312 100 178 121 47 35 65 66 19 23 100 118 47 150 21 37 186 71 13 179 100 888 81 115 3630 68 60 39 1 10 90 58 39 202 152 272 73 71 99 90 390 11 35 40 70 158 255 257 100 154 282 71 30 15 74 18 37 35 15 46 100 7 20 54 44 6 122 100 387 27 58 1858 53 83 64 69 26 99 504 142 654 354 80 274 612 176 209 625 73 295 150 683 510 0 508 135 222 887 62 100 119 100 94 191 36 119 266 127 16 18 578 292 62 99 100 820 47 206 90 100 91 138 213 23 67 275 102 706 116 414 125 490 116 422 900 97 139 150 608 94 300 754 66 105 409 88 68 83 96 100 227 2 46 104 8 10 9 242 91 18 121 100 238 6 145 15 62 8 59 29 72 100 777 19 979 488 336 124 466 206 274 878 138 226 233 316 302 150 588 206 300 930 52 82 129 56 175 166 49 68 147 150 10 22 583 270 7 167 100 134 39 204 49 332 201 82 121 21 554 1937 520 3103 1339 1727 820 2034 803 1382 3574 362 1252 776 3358 1325 1247 3002 707 1210 3024 412 367 507 479 558 707 313 393 675 685 106 134 2022 848 111 868 515 2847 274 884 5727 710 525 405 528 194 46.17 161.42 43.33 258.58 111.58 143.92 68.33 169.50 66.92 115.17 297.83 30.17 104.33 64.67 279.83 110.42 103.92 250.17 58.92 100.83 252.00 34.33 30.58 42.25 39.92 46.50 58.92 26.08 32.75 56.25 57.08 8.83 11.17 168.50 70.67 9.25 72.33 42.92 237.25 22.83 73.67 477.25 59.17 43.75 33.75 44.00 16.17 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 @ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 1 | Nov-Dec 2017 Page: 168
International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 99 16 36 8391 167.82 86.09 23.51 72 58 150 10320 206.4 105.88 28.91 29 55 7 6408 128.16 65.75 17.95 90 100 65 11554 231.08 118.54 32.37 33 100 43 8678 173.56 89.04 24.31 13 100 63 11628 232.56 119.30 32.58 336 429 364 56979 1139.6 584.60 159.64 28.00 35.75 30.33 4748 94.97 48.72 13.30 48 49 50 P Q R S Table-5: Bill data for village Khijooriya jatan Household No. Jan-Feb Mar-Apr May-Jun Jul-Aug Sep-Oct Nov-Dec Annual Monthly Avg 152 295 100 100 100 887 1 95 1 100 100 100 146 888 100 150 1 100 100 150 100 100 100 100 478 100 100 61 60 100 100 150 100 100 1034 1146 722 100 66 65 100 100 225 38 278 43 9 100 100 100 150 74 100 100 33 100 100 84 94 100 100 100 62 100 100 48 43 100 100 153 100 100 91 69 83 150 59 48 100 100 26 1009 322 305 100 100 100 100 36 436 250 100 100 100 100 117 100 100 2 100 391 0 100 100 150 444 100 152 1404 100 770 289 402 90 93 63 178 100 55 487 87 174 100 100 100 50 150 171 1 100 100 100 100 111 9 100 100 100 77 242 100 230 279 162 100 124 79 45 415 179 0 32 172 65 1012 100 381 537 130 134 100 100 177 100 98 213 1 100 100 100 100 111 47 100 100 100 80 59 453 172 86 48 100 124 45 68 98 150 88 76 126 82 236 100 218 423 108 52 100 100 138 79 80 257 1 100 100 100 100 111 64 100 100 100 83 52 127 172 84 78 100 124 74 50 58 150 103 27 668 618 1726 600 1005 3381 926 803 410 600 715 529 660 2039 453 650 434 600 600 684 414 600 502 600 1171 553 980 783 702 932 600 827 1802 463 2466 1983 1398 475 55.67 51.50 143.83 50.00 83.75 281.75 77.17 66.92 34.17 50.00 59.58 44.08 55.00 169.92 37.75 54.17 36.17 50.00 50.00 57.00 34.50 50.00 41.83 50.00 97.58 46.08 81.67 65.25 58.50 77.67 50.00 68.92 150.17 38.58 205.50 165.25 116.50 39.58 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 @ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 1 | Nov-Dec 2017 Page: 169
International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 1 21 50 100 0 42 100 150 84 59 100 100 150 4614 92.28 18.27 19.38 41 223 100 0 63 0 150 87 78 91 100 39 9374 187.48 37.12 39.36 26 69 100 0 100 100 150 150 92 33 100 26 5739 114.78 22.73 24.10 64 54 100 0 100 100 122 110 128 44 100 66 6813 136.26 26.98 28.61 47 86 143 100 100 100 1 30 62 139 100 16 5181 103.62 20.52 21.76 200 613 643 200 451 500 673 521 514 507 600 397 41171 823.42 163.04 172.89 16.67 51.08 53.58 16.67 37.58 41.67 56.08 43.42 42.83 42.25 50.00 33.08 3431 68.62 13.59 14.41 39 40 41 42 43 44 45 46 47 48 49 50 P Q R S 131 100 100 46 100 100 60 95 100 100 100 9450 189 37.42 39.68 The data collected by the survey is the primary data of energy consumption of villages and approximate also therefore energy consumption data is also collected from electricity bills provided by the local electricity distribution company. The data collected by survey is tabulated in Table-2 and bill data are tabulated in table-3 to table-5. Sample calculation for Jhar Village is as follows- Total number of families = 757 Therefore annual electricity consumption of whole village=1035.60 x 757 = 783949.20 kWh = 783.95 MWh Total population = 4683 Therefore annual per capita electricity consumption = ???.?? ???? = 167.40 kWh Some deviation is observed between collected data by the survey and collected data from electricity bills. To observe that deviation the consolidated data of electricity consumption both by electricity bills and survey are arranged in tabulated format in Table-6. Annual electricity consumption of 50 households = 51780 kWh. Therefore annual electricity consumption per family =????? ?? =1035.60 kWh Table-6: Consolidated electricity consumption data of villages Particulars X Bill X survey Y Bill Y Survey Z Bill Z Survey 863.16 1140.20 184.32 71.93 95.02 15.36 337.83 783.95 1035.60 167.40 65.33 86.30 13.95 306.83 584.60 1139.58 159.64 48.72 94.97 13.30 228.81 557.12 1086 152.13 46.43 90.50 12.68 218.06 163.04 823.42 172.89 13.59 68.62 14.41 63.81 155.63 786 165.03 12.97 65.50 13.75 60.91 A B C D E F G A-Energy consumption of villages in MWh/annum, B-Energy consumption of family in kWh/annum, C- Per capita Energy consumption in kWh/annum, D- Energy consumption of villages in MWh/month, E- Energy consumption of family in kWh/month, F- Per capita Energy consumption in kWh/month, G- Average Power in kW/month, X-Jhar, Y-Mansarkheri and Z-Khijooriya jatan @ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 1 | Nov-Dec 2017 Page: 170
International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 Khi.Jatan(Survey) Khi.Jatan(Survey) 155.63 65.50 Khi.Jatan(Bill) Khi.Jatan(Bill) 163.04 68.62 Mansarkheri(Survey) Mansarkheri(Survey) 557.12 90.50 90.50 Mansarkheri(Bill) Mansarkheri(Bill) 584.60 94.97 Jhar(Survey) Jhar(Survey) 783.95 86.30 86.30 Jhar(Bill) Jhar(Bill) 863.16 95.02 0 200 400 600 800 1000 0 20 40 60 80 100 Energy consumption of family in kWh/month Energy consumption of family in kWh/month Energy consumption of village in MWh/annum Energy consumption of village in MWh/annum Figure -1: Energy consumption of village in MWh/annum : Energy consumption of village in MWh/annum Figure -5 Energy consumption of family in kWh/month Energy consumption of family in kWh/month Khi.Jatan(Survey) Khi.Jatan(Survey) 786 13.75 13.75 Khi.Jatan(Bill) Khi.Jatan(Bill) 823.42 14.41 14.41 Mansarkheri(Survey) Mansarkheri(Survey) 1086 12.68 12.68 Mansarkheri(Bill) Mansarkheri(Bill) 1139.58 13.30 13.30 Jhar(Survey) Jhar(Survey) 1035.60 13.95 13.95 Jhar(Bill) Jhar(Bill) 1140.20 15.36 15.36 0.00 200.00 400.00 600.00 800.00 1000.00 1200.00 0 2 4 6 8 10 12 14 16 18 Per capita Energy consumption in kWh/month Per capita Energy consumption in kWh/month Energy consumption of family in kWh/annum Energy consumption of family in kWh/annum Figure-2: Energy consumption of family in kWh/annum family in kWh/annum Figure-6: Per capita energy consumption in kWh/month Per capita energy consumption in kWh/month Khi.Jatan(Survey) Khi.Jatan(Survey) 165.03 60.91 Khi.Jatan(Bill) Khi.Jatan(Bill) 172.89 63.81 Mansarkheri(Survey) Mansarkheri(Survey) 152.13 218.06 Mansarkheri(Bill) Mansarkheri(Bill) 159.64 228.81 Jhar(Survey) Jhar(Survey) 167.40 306.83 306.83 Jhar(Bill) Jhar(Bill) 184.32 337.83 337.83 0 50 100 150 200 0 50 100 150 200 250 300 350 400 Per capita Energy consumption in kWh/annum Per capita Energy consumption in kWh/annum Avg Power in kW/month Avg Power in kW/month Figure-7: Average power requirement in kW/month Average power requirement in kW/month Figure-3: Per capita energy consumption in kWh/annum Per capita energy consumption in kWh/annum 3. CONCLUSIONS Khi.Jatan(Survey) 12.97 Khi.Jatan(Bill) 13.59 In this study electricity consumption data is collected by survey as well as local electricity Distribution Company. On the basis of these data, energy consumption parameters i.e. of villages in MWh/annum, B family in kWh/annum, C consumption in kWh/annum, D of villages in MWh/month, E- family in kWh/month, F- consumption in kWh/month, G kW/month, have been representations also have been plotted between survey data and bill data for the purpose of comparative view. By viewing the graphical plots of energy consumption parameters it can be concluded that consumption parameters it can be concluded that In this study electricity consumption data is collected by survey as well as local electricity Distribution Company. On the basis of these data, energy consumption parameters i.e. A-Energy consumption of villages in MWh/annum, B-Energy consumption of y in kWh/annum, C-Per capita Energy consumption in kWh/annum, D-Energy consumption Mansarkheri(Survey) 46.43 Mansarkheri(Bill) 48.72 Jhar(Survey) 65.33 Jhar(Bill) 71.93 0.00 10.00 20.00 30.00 40.00 50.00 60.00 60.00 70.00 80.00 Energy consumption of village in MWh/month Energy consumption of village in MWh/month Figure-4: Energy consumption of village in MWh/month Energy consumption of village in MWh/month - Energy consumption of - Per capita Energy The plots between survey data and bill data have also been plotted for each energy consumption parameters and shown in figures-1 to figure-7. The plots between survey data and bill data have also been plotted for each energy consumption parameters and consumption in kWh/month, G-Average Power in kW/month, have been representations also have been plotted between survey data and bill data for the purpose of comparative By viewing the graphical plots of energy calculated. calculated. Gra Graphical @ IJTSRD | Available Online @ www.ijtsrd.com @ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 1 | Nov-Dec 2017 Dec 2017 Page: 171
International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 Energy consumption parameters A, B, C, D, E, F, G calculated by survey data are found to be less for each village as compared to energy parameters calculated by bill data. Bill data therefore should be taken as reference data for designing any electrical power generation facility for the villages, instead of survey data because bill data are based on the meter readings of the individual households which shows the actual electricity consumed by the household. empirical study in a coastal village of Indian Sundarban, Renewable Energy 35 (2010) 2835-2838. consumption [6] I.Purohit and P.Purohit, Techno-economic evaluation of concentrating solar power generation in India, Energy Policy 38 (2010) 3015–3029 [7] Population census data of villages Jhar, Mansarkheri and Khijooriya http://censusindia.gov.in/, accessed on March 2015. Jatan, website, BIOGRAPHIES REFERENCES Vikrram Singh Meena M.Tech- Renewable Energy Malaviya National Institute Of Technology, Jaipur, India B.Tech- Electrical Engineering Jamia Millia Islamia, New Delhi, India Dr. G. D. Agrawal Associate Professor Dept. of Mechanical Engineering, Malaviya National Institute Of Technology, Jaipur, India Ph.D.-Energy Recovery From MSW M.Tech.-Thermal Engineering B.E.-Mechanical Engineering [1] R.D.Prasad, R.C.Bansal and A.Raturi, Multi- faceted energy planning: A review, Renewable and Sustainable Energy Reviews 38 (2014) 686–699. [2] T.Urmee, D.Harries and A.Schlapfer, Issues related to rural electrification using renewable energy in developing countries of Asia and Pacific, Renewable Energy 34 (2009) 354–357. [3] N.Kautto and P.Peck, Regional biomass planning- Helping to realise national renewable energy goals, Renewable Energy 46 (2012) 23-30. [4] J.Singh, Overview of electric power potential of surplus agricultural biomass from economic, social, environmental and technical perspective—A case study of Punjab, Renewable and Sustainable Energy Reviews 42 (2015) 286–297. [5] A.K.Bhandari and C.Jana, A comparative evaluation of household preferences for solar photovoltaic standalone and mini-grid system: An @ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 1 | Nov-Dec 2017 Page: 172