Calculaton and Predcton of Energy Consumpton for Hghway Transportaton Feng Qu, Wenquan L *, Qufeng Xe, Peng Zhang, Yueyng Huo School of Transportaton, Southeast Unversty, Nanjng 210096, Chna; *E-mal: wenql@seu.edu.cn Keywords: hghway transportaton; energy consumpton; pseudo varable algorthm; energy predcton Abstract Ths paper carres out experments for energy effcency, combned wth observaton of traffc volume, and proposes calculaton model of energy consumpton for hghway system. Standard transport turnover s used to compute future energy consumpton, and, n alluson to structural changes n hstorcal data, pseudo varable algorthm s ntroduced to forecast transport turnover. The results show that ths method can calculate accurately the energy consumpton, and pseudo varable algorthm can get better predcton than conventonal methods. 1 Introducton Transportaton s the basc ndustry of socal and economc development and has an rreplaceable role n promotng economc development, mprovng people s lves and natonal defense. Because of the relatve scarcty of ol resources and rapd economc development, energy shortage has become a constrant for the sustanable development of transportaton, especally hghway transportaton. Calculaton and predcton of energy consumpton are the bass of energy conservaton work and ther functon s to provde nformaton, advce and supervson for energy management. These consumpton statstcs can reflect the true level of energy consumpton of transportaton system and offer statstcal nformaton for macro decson-makng and management. Researches on energy consumpton focus on the macro and mcro level now. At the macro level, scholars study the analyss of energy consumpton n some regons [1-5], n order to facltate regonal development. At the mcro level, some researches am at mprovng energy effcency [6-8], for the sake of optmzng the qualty of economc development. Others manly study statstcal methods and models [9-11] and nowadays analyss of energy consumpton of transportaton focuses on two aspects. One s for the entre transportaton and another s for the hghway transportaton. But the energy consumpton statstcs for hghway transportaton s lmted to commercal vehcles, wthout consderng the large number of uncommercal vehcles, so the data collected can not make a full and accurate assessment of energy consumpton of hghway transportaton and fal to provde detaled nformaton for energy conservaton. Hghway transportaton, as the major meda between mportant economc poston and ctes, has the pvotal poston n transportaton system but t s not the same as road transportaton and has a bg dfference wth urban transportaton. To solve ths problem, ths paper takes Henan Provnce as an example to study energy consumpton calculaton and predcton methods for hghway transportaton, amng to provde the necessary decson-makng bass for energy consumpton. 2 Calculaton of energy consumpton The vehcles on the hghway nclude not only passenger cars and ordnary s, but also tralers, contaner s and other specal vehcles. There are sgnfcant dfferences n the energy effcency for varous sorts of vehcles, so the total energy consumpton of hghway transportaton wll doubtlessly change wth dfferent compostons of traffc flow. The exstng survey methods just estmate the average fuel effcency of vehcles, and calculate energy consumpton wth mleage of vehcles. These methods do not take nto account the dfferences between varous vehcles, so t s dffcult to get hghly accurate results. If the calculaton of energy consumpton can consder the composton of traffc, combnng energy effcency of varous vehcles, the calculaton of energy consumpton of hghway transportaton wll no doubt be more belevable. So the total energy consumpton of hghway transportaton system s m n s j M aj b ) (1) j 1 1 100 Where, M The total energy consumpton of hghway system wth m hghways (tec);
The Seventh Advanced Forum on Transportaton of Chna a The volumes of th sort of vehcle on the jth j hghway(veh); b The energy consumpton effcency of th sort of vehcle(tec/100km); s The length of jth hghway(km). j Vehcles on the hghway run smoothly, compared wth urban roads. Less traffc dsrupton, brakes and other causal factors means hgh relablty for vehcle energy consumpton tests. Because temperature, elevaton and other external factors can affect fuel effcency, energy consumpton tests have obvously regonal dfferences. Although there are some proposed regonal fuel consumpton model, wth the development of vehcle technology and road condton, these models can not keep suffcent accuracy nowadays. So t s necessary to conduct new nvestgatons to ensure the accuracy of calculaton of energy consumpton. Fuel consumpton tests are mplemented n Henan provnce and the data of (Table 1) and passenger cars (Table 2) are as follows. Table 1: Energy consumpton test for s. Average dstance for test (km) Energy effcency (tec/100km) Classfcaton Crtera for classfcaton max mn avg max mn avg L 4 3 500 0.02 199.29 0.089 6 0.002 8 0.021 8 4 L 8 4 095.00 1.31 399.89 0.087 6 0.009 1 0.027 4 ordnary s 8 L 20 4 546.00 1.50 520.45 0.079 7 0.002 7 0.031 0 L 20 4 100.00 2.00 687.98 0.080 6 0.009 7 0.034 5 contaner 370.00 70.00 187.50 0.029 4 0.028 2 0.028 9 Specal s traler 4 700.00 5.00 736.69 0.096 7 0.008 8 0.035 6 tractor 1 279.63 0.50 56.91 0.069 1 0.004 3 0.018 6 Note: L means the length of s Table 2: Energy consumpton test for passenger cars. classfcaton Crtera for classfcaton Energy effcency tec/100km Drvng range Servce area Permtted No. of Passengers max mn avg ordnary passenger car tax bus In-county X 15 0.036 5 0.005 0 0.015 4 X 15 0.052 8 0.005 0 0.019 3 Ex-county 0.052 0 0.005 3 0.020 5 Ex-cty 0.059 0 0.005 1 0.022 6 Ex-provnce 0.057 1 0.008 2 0.027 5 X 5 0.024 3 0.005 0 0.009 1 X 5 0.020 7 0.005 0 0.009 5 X 30 0.042 1 0.005 2 0.017 2 X 30 0.037 2 0.020 2 0.027 3 A large number of observatons are conducted for hghways system n Henan provnce, and the traffc volume data are obtaned. Hghway system contans natonal hghways and provncal hghways. Because of the lmted space n ths paper, the traffc volume data of natonal hghways are lad out (Table 3).It can be seen that the model (Equaton 1)can calculate not only the energy consumpton of a sngle hghway, but also that of a hghway network.. By ths model, natonal hghway system n Henan provnce consumes 4.488 mllon tecs per year, and vehcles on provncal hghway system make use of 5.224 mllon tecs per year. It should be noted that the traffc volumes here nclude two types of vehcles, one belongng to Henan provnce and another from other provnces. In order to get the local energy consumpton, t s necessary to make sure the proporton v for local vehcles. Accordng to observatons, the paper sets v= n 0.5 for natonal hghways and v= p 0.8 for provncal hghways, and the local energy consumpton of hghway system n Henan provnce s 6.423 mllon tecs per year. 3 Predcton of energy consumpton To predct future energy demand for hghway transportaton system s an ndspensable work for energy conservaton, and the precse energy consumpton forecast can provde the bass for vehcle management and energy polcy. The commonly used methods for predcton nclude multple lnear regresson, logarthm lnear demand functon model and dstrbuton delay model [12-13]. These methods generally use traffc demand to predct future energy consumpton, but n the past 20 years, fluctuaton of economy, the external socal envronment and polcy often led to structural changes n traffc demand. The development of transportaton turnover n Henan provnce can be dvded nto three trends (Fgure 1) and the common methods often fal to accurately reflect these changes. 227
Names of hghways length (km) Table 3: The traffc volumes of natonal hghways n Henan provnce. Average daly traffc volumes(veh/d) small Med Large Super trcuk traler Conta-ner Small passenger car large passenger car Jng Guang 507.29 1 312 481 155 102 212 6 1 791 283 247 Jng Shen 578.43 2 742 1 568 506 351 654 17 4 868 581 191 Jng Zhu 578.43 2 006 875 325 132 419 0 1 530 214 247 R Lan 43.08 426 1 142 453 163 2 868 78 2 238 505 0 X Ha 415.83 591 247 131 136 112 0 1 330 159 86 Hu Be 292.48 522 26 114 100 203 0 1 093 129 90 Dong Zheng 143.04 1 535 1 168 262 113 254 1 1 334 416 86 Lan Huo 610.09 688 1 772 718 307 3 502 54 5 800 692 0 Rao Cheng 52.02 309 462 143 56 709 2 3 795 203 0 Lan Tan 643.50 1 091 702 323 202 303 9 2 619 239 144 Xu X 619.52 993 514 188 64 80 1 1 748 205 137 Shang Huo 555.62 1 071 550 273 173 400 2 1 962 383 193 J Guang 57.45 131 337 74 27 499 23 706 169 0 Nng Luo 368.28 389 943 261 133 2 023 38 3 156 465 0 Be Gang 530.53 738 1 916 882 506 4 423 251 7 905 985 0 Shang X 518.72 180 327 121 40 755 105 1 922 377 0 Da Guang 544.09 132 232 50 24 255 21 1 425 205 0 Er Guang 355.61 232 393 107 117 737 27 1 912 185 0 Jn Xn 107.27 351 876 315 188 1 395 100 2 941 263 0 tractor Fgure 1: The development of standard transportaton turnover. To avod potental error, pseudo varable algorthm based on nterval s recommended to predct future transport turnover. Hstorcal data wll be classfed accordng to trend analyss and ths algorthm can create pseudo varable to reach hgh accuracy. Takng nto account the short hstory record for energy statstcs of hghway system, t s supposed that the energy consumpton of hghway system grows n step wth the transport turnover of overall transportaton system n Henan provnce, so transportaton turnover can be used to predct energy consumpton. After analyss, the model selects the total populaton and regonal gross domestc product (GDP) Z as explanatory varables and standard transportaton turnover Y s chosen as a dependent varable: Y 0 1X 2Z 3D 4DX 5DZ (2) where D Pseudo varable, 0, 1, 2 3 4 Varable for regresson model, 5 Stochastc error. X 228
The Seventh Advanced Forum on Transportaton of Chna Pseudo varable does not take actual value and need to be assgned facttous value based on trend analyss. In ths model, D s 0 f year belong to trend 1 D 1 f year belong to trend 2 2 f year belong to trend 3 If D 0, then Y 0 1X 2Z If D 1, then Y 0 1X 2Z 3 4X 5Z If D 2, then Y X Z 2 2 X 2 Z 0 1 2 3 4 5 Ths model contans only one formula nstead of three equatons. In addton to facltatng calculaton, the man reason s to ncrease the degree of freedom and enhance the precson of parameter estmaton. In ths case, the number of samples ncreases almost 3 tmes but the number of varables s much less than the amount of samples ncreased. Therefore there s a sgnfcant rse n the degrees of freedom. The transport turnover, the total populaton, GDP and pseudo varable (Table 4) are put nto the equaton 2 and the predcton model s Y 645.866 807 0.092 584* X 0.044 858* Z 2 833.361 858* D 0.307 819* D* X 0.007 155* D* Z 2 Ths model passes F test and T test ( R 0.9965 ) and the data from ths model are consstent wth real data, wth the maxmum error 6.5% and the mnmum error 0.04%. Then the lnear regresson model s used to do the same predcton and the paper compares the results form lnear regresson model and pseudo varable method (Fgure 2). It can be seen that pseudo varable method can get better accuracy than ordnary lnear regresson. It s assumed that natural populaton growth n Henan provnce s 6.5 and GDP growth remans 10%. If n the future t grows compled wth dfferent trends, predcton for energy consumpton of hghway transportaton system can be obtaned (Table 5). year populaton (10 thousand p) Table 4: The socal and economc data of Henan provnce and the predcton from ths model. GDP pseudo Standard Transportaton (100 mllon yuan) varable turnover D (100 mllon ton-km) predcton (100 mllon ton-km) 1988 8 317 749.09 0 159.06 148.76 6.5 1989 8 491 850.71 0 163.52 169.43 3.6 1990 8 649 934.65 0 179.97 187.82 4.3 1991 8 763 1 045.73 0 190.99 203.36 6.5 1992 8 861 1 279.75 0 232.59 222.93 4.2 1993 8 946 1 660.18 0 251.59 247.86 1.5 1994 9 027 2 216.83 0 284.48 280.33 1.5 1995 9 100 2 988.37 0 321.39 321.70 0.1 1996 9 172 3 634.69 0 355.13 357.36 0.6 1997 9 243 4 041.09 0 384.17 382.16 0.5 1998 9 315 4 308.24 1 387.57 397.67 2.6 1999 9 387 4 517.94 1 397.82 393.07 1.2 2000 9 488 5 052.99 1 399.32 399.17 0.04 2001 9 555 5 533.01 1 412.72 409.71 0.7 2002 9 613 6 035.48 1 437.87 423.36 3.3 2003 9 667 6 867.70 1 440.20 455.02 3.3 2004 9 717 8 553.79 2 461.56 435.45 3.5 2005 9 768 10 587.42 2 510.78 529.10 3.6 2006 9 820 12 362.79 2 588.03 606.95 3.2 2007 9 869 15 012.46 2 742.03 738.09 0.5 2008 9 918 18 407.78 2 921.71 913.36 0.9 2009 9 967 19 480.46 2 1 037.85 997.55 4.0 error (%) 229
Fgure 2: Comparson between lnear regresson model and pseudo varable method. Table 5: The energy consumpton predcton for hghway system n Henan provnce. year Classfcaton 2010 2011 2012 2013 2014 2015 2020 energy consumpton(1000 tecs) trend 1 7 507.6 8 127.1 8 805.5 9 548.5 10 362.4 11 254.3 17 185.5 energy consumpton(1000 tecs) trend 2 7 524.3 8 171.5 8 891.8 9 692.5 10 581.7 11 568.5 18 343.0 energy consumpton(1000 tecs) trend 3 7 544.6 8 224.4 8 994.5 9 864.0 10 842.9 11 942.4 19 721.2 4 Concluson Because nowadays energy consumpton calculaton can only consder the commercal vehcles, the paper proposes a new method to get the energy consumpton for hghway system, and, takng Henan provnce as an example, computes the energy consumpton for natonal hghways and provncal hghways. Thnkng over that conventonal methods can not reflect the structural changes, pseudo varable algorthm s used to predct standard traffc turnover and then calculate future energy consumpton. Accordng to hstorcal data, the forecast has been dvded nto slow, secondary and fast mode, and ths method proves to be effectve. Acknowledgements Ths research s funded by the Natonal Natural Scence Foundaton of Chna (No.50978057). References [1] Q. P. Sun, Q. Y. Wang, B. H. Mao. Framework desgn of dfferent transportaton modes Energy consumpton factors and comparablty study. Journal of Transportaton Systems Engneerng and Informaton Technology, Vol. 9, No. 4, pp. 10-14, (2009). [2] L. P. Wang, Y. L. Sh, Y. Z. Chang, et al. Decomposton analyss of energy consumpton n shangha based on AWD. 2009 Internatonal Conference on Informaton Management, Innovaton Management and Industral Engneerng, pp. 423-426, (2009). [3] S. W. Zhang, K. J. Jang, D. S. Lu. Energy consumpton of chna s transport development and ts polcy mplcatons. Chna Soft Scence, Vol. 5, pp. 58-62, (2006),. [4] J. Xa, S. Y. Zhu. Coordnaton analyss between Chnese transportaton energy consumpton and soco-economc development. Storage Transportaton Preservaton of Commodtes, Vol.30 No. 9, pp. 1-3, (2008). [5] M. Zhang, H. N. L, M. Zhou, et al. Decomposton analyss of energy consumpton n Chnese transportaton sector. Appled Energy, Vol.88, pp. 2279-2285, (2011). [6] S. Z. Chen, Q. X. Ca. Energy consumpton comparson and energy savng measures of open pt development. 2011 Internatonal Conference on Computer Dstrbuted Control and Intellgent Envronmental Montorng, pp. 712-715, (2011). [7] R. Sadur, M. A. Sattar, H. H. Masjuk, et al. An estmaton of the energy and energy effcences for the energy resources consumpton n the transportaton sector n Malaysa. Energy Polcy, Vol. 35, pp. 4018-4026, (2007). 230
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