Volume 24 Issue 4
Aug.  2024
Turn off MathJax
Article Contents
HUANG Xian, YE Xiao-rong, JI Wen-tong, FENG Zhang-jie. Economic characteristics of highway self-consistent energy system planning[J]. Journal of Traffic and Transportation Engineering, 2024, 24(4): 56-70. doi: 10.19818/j.cnki.1671-1637.2024.04.005
Citation: HUANG Xian, YE Xiao-rong, JI Wen-tong, FENG Zhang-jie. Economic characteristics of highway self-consistent energy system planning[J]. Journal of Traffic and Transportation Engineering, 2024, 24(4): 56-70. doi: 10.19818/j.cnki.1671-1637.2024.04.005

Economic characteristics of highway self-consistent energy system planning

doi: 10.19818/j.cnki.1671-1637.2024.04.005
Funds:

National Key Research and Development Program of China 2021YFB2601300

More Information
  • Author Bio:

    HUANG Xian(1966-), male, professor, PhD, hx@ncepu.edu.cn

  • Received Date: 2024-03-25
    Available Online: 2024-09-26
  • Publish Date: 2024-08-28
  • To promote the integrated development of transportation and energy, an architecture of highway self-consistent energy system was constructed, with wind-photovoltaic-storage as the power supply side and highway electricity equipment as the demand side. The architecture was equipped with reasonable operation rules. Besides, a planning model for the self-consistent energy system was built with the number of wind-photovoltaic-storage equipment as the planning variable, the equivalent annual cost of system as the optimization objective, the probability of power shortage and the amount of curtailed wind and photovoltaic power as the constraints. Simulations were performed with wind and solar historical data and load demand data in a certain western region as inputs after the operation rules being transformed into specific strategies. Research results indicate that the upper limit increase in microgrid interconnection power can significantly reduce the cost of the self-consistent energy system. When the upper limit of microgrid interconnection power increases from 0 to 1 000 kW, the equivalent annual cost of the system decreases by 8.53%. A new energy accommodation rate increase will lead to rising cost. Too high pursuit of new energy accommodation rates can even result in a sharp cost rise. The strengthening of constraints on curtailed wind and photovoltaic power leads to a 9.05% increase in new energy accommodation rate, while the equivalent annual cost increases by 73.86%. The application of hierarchical load management can significantly reduce the economic cost of the system. When the upper limit of the loss of load probability for primary load remains unchanged, and tertiary loads change respectively from 0 to 0.05 and 0.20, the equivalent annual cost of self-consistent energy system even reduces by 90.97%. Based on these findings, it can be concluded that the application of microgrid interconnection and hierarchical load management, and the appropriate new energy accommodation rate requirements can make the cost of highway self-consistent energy system planning more reasonable. 10 tabs, 11 figs, 46 refs.

     

  • loading
  • [1]
    ZHANG You-min, MA Dong-dong. Research on the development of green electricity on highways under the background of traffic energy integration[J]. Lamps and Lighting, 2022, 175(12): 177-179. (in Chinese)
    [2]
    YUE Dan, LI Ming-jun, LI Na, et al. Discussion on the concept and realization of green highway construction under the background of emission peak and carbon neutrality[J]. Transport Energy Conservation and Environmental Protection, 2022, 18(4): 40-44, 65. (in Chinese)
    [3]
    CANG Ding-bang, CHEN Cang, CHEN Qing, et al. Does new energy consumption conducive to controlling fossil energy consumption and carbon emissions?—Evidence from China[J]. Resources Policy, 2021, 74: 102427. doi: 10.1016/j.resourpol.2021.102427
    [4]
    HONG Zi-wei, SU Hong-li, LIU Hai-yang, et al. Research on key technologies and business models of low-carbon transformation of power industry under the "double carbon" trend[C]//IEEE. 2021 11th International Conference on Power and Energy Systems (ICPES). New York: IEEE, 2021: 643-647.
    [5]
    JIA Li-ming, MA Jing, CHENG Peng, et al. A perspective on solar energy-powered road and rail transportation in China[J]. CSEE Journal of Power and Energy Systems, 2020, 6(4): 760-771.
    [6]
    NGUYEN V C, WANG C T, HSIEH Y J. Electrification of highway transportation with solar and wind energy[J]. Sustainability, 2021, 13(10): 5456. doi: 10.3390/su13105456
    [7]
    ZHOU Peng-zhan, WANG Cong, YANG Yuan-yuan. Design and optimization of solar-powered shared electric autonomous vehicle system for smart cities[J]. IEEE Transactions on Mobile Computing, 2023, 22(4): 2053-2068. doi: 10.1109/TMC.2021.3116805
    [8]
    GARCÍA-OLIVARES A, SOLÉ J, OSYCHENKO O. Transportation in a 100% renewable energy system[J]. Energy Conversion and Management, 2018, 158: 266-285. doi: 10.1016/j.enconman.2017.12.053
    [9]
    HOSSAIN M F. Implementation of hybrid wind and solar energy in the transportation sector to mitigate global energy and environmental vulnerability[J]. Clean Technologies and Environmental Policy, 2023, 25(4): 1195-1210. doi: 10.1007/s10098-022-02437-4
    [10]
    SUBRAMANIAN R. The current status of roadways solar power technology: a review[C]//ASCE. Environmental Sustainability in Transportation Infrastructure. Reston: ASCE, 2015: 177-187.
    [11]
    TANG Ming-tao, CHEN Zhi-qiang, WANG Zhi-gang, et al. Application of distributed photovoltaic power generation in expressway traffic facilities[J]. Solar Energy, 2016(9): 28-31. (in Chinese)
    [12]
    LIDULA N W A, RAJAPAKSE A D. Microgrids research: a review of experimental microgrids and test systems[J]. Renewable and Sustainable Energy Reviews, 2011, 15(1): 186-202. doi: 10.1016/j.rser.2010.09.041
    [13]
    SHUAI Z K, SUN Y Y, SHEN Z J, et al. Microgrid stability: classification and a review[J]. Renewable and Sustainable Energy Reviews, 2016, 58: 167-179. doi: 10.1016/j.rser.2015.12.201
    [14]
    CHANDAK S, ROUT P K. The implementation framework of a microgrid: a review[J]. International Journal of Energy Research, 2020, 45(3): 3523-3547.
    [15]
    KAMAL M M, ASHRAF I, FERNANDEZ E. Planning and optimization of microgrid for rural electrification with integration of renewable energy resources[J]. Journal of Energy Storage, 2022, 52: 104782. doi: 10.1016/j.est.2022.104782
    [16]
    SALMAN U, KHAN K, ALISMAIL F, et al. Techno-economic assessment and operational planning of wind-battery distributed renewable generation system[J]. Sustainability, 2021, 13(12): 6776. doi: 10.3390/su13126776
    [17]
    EGAN T, GABBAR H A, OTHMAN A M, et al. Design and control of resilient interconnected microgrid for sustained railway[C]//IEEE. 2017 IEEE International Conference on Smart Energy Grid Engineering (SEGE). New York: IEEE, 2017: 131-136.
    [18]
    WANG Cheng-shan, JIAO Bing-qi, GUO Li, et al. Optimal planning of stand-alone microgrids incorporating reliability[J]. Journal of Modern Power Systems and Clean Energy, 2014, 2(3): 195-205. doi: 10.1007/s40565-014-0068-9
    [19]
    DING Ming, WANG Bo, ZHAO Bo, et al. Configuration optimization of capacity of standalone PV-wind-diesel-battery hybrid microgrid[J]. Power System Technology, 2013, 37(3): 575-581. (in Chinese)
    [20]
    DAWOOD F, SHAFIULLAH G M, ANDA M. Stand-alone microgrid with 100% renewable energy: a case study with hybrid solar PV-battery-hydrogen[J]. Sustainability, 2020, 12(5): 2047. doi: 10.3390/su12052047
    [21]
    ELMORSHEDY M F, ELKADEEM M R, KOTB K M, et al. Feasibility study and performance analysis of microgrid with 100% hybrid renewables for a real agricultural irrigation application[J]. Sustainable Energy Technologies and Assessments, 2022, 53: 102746. doi: 10.1016/j.seta.2022.102746
    [22]
    BANDEIRAS F, PINHEIRO E, GOMES M, et al. Review of the cooperation and operation of microgrid clusters[J]. Renewable and Sustainable Energy Reviews, 2020, 133: 110311. doi: 10.1016/j.rser.2020.110311
    [23]
    ZHAO Bo, LI De-min, WU Zai-jun, et al. Capacity optimal sizing of island microgrid clusters based on the target of 100% green energy power supply[J]. Proceedings of the CSEE, 2021, 41(3): 932-945. (in Chinese)
    [24]
    SHI Meng-shu, HUANG Yuan-sheng, LIN Hong-yu. Research on power to hydrogen optimization and profit distribution of microgrid cluster considering shared hydrogen storage[J]. Energy, 2023, 264: 126113. doi: 10.1016/j.energy.2022.126113
    [25]
    CHE Liang, ZHANG Xia-ping, SHAHIDEHPOUR M, et al. Optimal interconnection planning of community microgrids with renewable energy sources[J]. IEEE Transactions on Smart Grid, 2017, 8(3): 1054-1063. doi: 10.1109/TSG.2015.2456834
    [26]
    LIU Yang, LIU Tian-yu, HE Shu-sen. Coordination and optimization of CCHP microgrid group game based on the interaction of electric and thermal energy considering conditional value at risk[J]. IEEE Access, 2021, 9: 88664-88673. doi: 10.1109/ACCESS.2021.3089591
    [27]
    HARMON E, OZGUR U, CINTUGLU M H, et al. The internet of microgrids: a cloud-based framework for wide area networked microgrids[J]. IEEE Transactions on Industrial Informatics, 2018, 14(3): 1262-1274. doi: 10.1109/TII.2017.2785317
    [28]
    LI Zhi-yi, SHAHIDEHPOUR M, AMINIFAR F, et al. Networked microgrids for enhancing the power system resilience[J]. Proceedings of the IEEE, 2017, 105(7): 1289-1310. doi: 10.1109/JPROC.2017.2685558
    [29]
    ALI AREFIFAR S, ORDONEZ M, MOHAMED Y A R I. Energy management in multi-microgrid systems—development and assessment[J]. IEEE Transactions on Power Systems, 2017, 32(2): 910-922. doi: 10.1109/TPWRD.2016.2578941
    [30]
    CHEN Jie, YU Zhong-hui, CHEN Guo-yan, et al. Calculation of carbon emission during expressway operation period based on energy consumption analysis[J]. IOP Conference Series: Earth and Environmental Science, 2021, 647(1): 012190. doi: 10.1088/1755-1315/647/1/012190
    [31]
    FAN Xiang-ran. Research on location and capacity determination of distributed generation in expressway DC microgrid[D]. Harbin: Harbin Institute of Technology, 2018. (in Chinese)
    [32]
    WANG Hua-cheng, ZHU Xin-chun, WANG Zi-fu, et al. Research on online monitoring technology system of green highway during operation period——environmental, meteorological and energy consumption monitoring[J]. Transport Energy Conservation and Environmental Protection, 2022, 18(1): 139-144. (in Chinese)
    [33]
    CAI Ye, LIU Ying, TANG Xia-fei, et al. Increasing renewable energy consumption coordination with the monthly interprovincial transaction market[J]. Frontiers in Energy Research, 2021, 9: 719419. doi: 10.3389/fenrg.2021.719419
    [34]
    LIU Gang-lou. Importance and application of power load classification management in islanded power station[J]. Electrical Equipment and Economy, 2017(4): 72-73. (in Chinese)
    [35]
    REN Yin-ze, WU Hong-bin, YANG He-jun, et al. A method for load classification and energy scheduling optimization to improve load reliability[J]. Energies, 2018, 11(6): 1558. doi: 10.3390/en11061558
    [36]
    SHUVRA M A, CHOWDHURY B. Load management system and control strategies of distributed energy resources in an islanded microgrid[C]//IEEE. 2019 IEEE 16th International Conference on Smart Cities: Improving Quality of Life Using ICT and IoT and AI (HONET-ICT). New York: IEEE, 2019: 100-104.
    [37]
    DAI Liang, ZHANG Cheng-yin, HUANG-Yun, et al. Feasibility analysis of supply-demand matching between highway operational energy consumption and renewable energy integration: a case study of Panzhihua-Dali Highway within Sichuan Province[C]//IEEE. 2022 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia). New York: IEEE, 2022: 1989-1993.
    [38]
    MA Shu-hong, XIANG Qian-zhong, TANG Ke, et al. Research on energy consumption system and statistical indicators of expressway in operation period[J]. Highway, 2013, 58(10): 146-150. (in Chinese)
    [39]
    SALEHI N, MARTÍNEZ-GARCÍA H, VELASCO-QUESADA G, et al. A comprehensive review of control strategies and optimization methods for individual and community microgrids[J]. IEEE Access, 2022, 10: 15935-15955. doi: 10.1109/ACCESS.2022.3142810
    [40]
    XU Chuan-bo, KE Yi-ming, LI Yan-bin, et al. Data-driven configuration optimization of an off-grid wind/PV/hydrogen system based on modified NSGA-Ⅱ and CRITIC-TOPSIS[J]. Energy Conversion and Management, 2020, 215: 112892. doi: 10.1016/j.enconman.2020.112892
    [41]
    YU J, RYU J H, LEE I B. A stochastic optimization approach to the design and operation planning of a hybrid renewable energy system[J]. Applied Energy, 2019, 247: 212-220. doi: 10.1016/j.apenergy.2019.03.207
    [42]
    BILLINTON R, CHU K. Early evolution of LOLP: evaluating generating capacity requirements[history][J]. IEEE Power and Energy Magazine, 2015, 13(4): 88-98. doi: 10.1109/MPE.2015.2417475
    [43]
    GAO Lei, SU Xin-yi, LIU Shi-yu. Study on reasonable curtailment rate of renewables under certain renewable energy consumption quota obligation[J]. Electric Power, 2020, 53(12): 136-142. (in Chinese)
    [44]
    ZHANG Jin-jin, WANG Tao, WU Jun-yong, et al. Short-term load forecasting method based on artificial intelligence highway neural network[C]//IEEE. 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2). New York: IEEE, 2021: 2999-3003.
    [45]
    TANG Ke. Energy consumption analysis and calculation method study of expressway operation period[D]. Xi'an: Chang'an University, 2013. (in Chinese)
    [46]
    SUN Guang-hui, SHEN Guo-rong. Enhancing three-defense lines for insuring the security and stability of the power system of China[J]. Jiangsu Electrical Engineering, 2004(5): 4-7. (in Chinese)

Catalog

    Article Metrics

    Article views (421) PDF downloads(51) Cited by()
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return