Abstract
This paper constructs a comprehensive value evaluation model of energy internet based on an integrated approach with system dynamics, the AHP-entropy method, and cloud model theory. Annual data from 2010 to 2019 is selected to assess the value creation of digital technology-orientated energy internet in China. By separating it with economic, energy, environmental, and social dimensions based on the process of energy internet value creation, the comprehensive value of digital technology-oriented energy internet is assessed from a macro perspective. Guided by the policy agenda, different scenarios of digital technology investment are set to simulate the change of energy internet value creation. The results show that digital technologies have a significantly positive impact on the comprehensive value of energy internet, with a 5.18% increase in comprehensive value under the high-investment scenario and a 1.75% increase under the low-investment scenario. While the excessive investment in digital technology will also lead to an increase in comprehensive energy consumption. The social value is the primary limiting factor for enhancing the comprehensive value created by the energy internet. The methodology proposed is versatile and supposed to broadly applicable framework for the comprehensive assessment.
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Data availability
The datasets generated during the current study are available in National Bureau of Statistics of China, http://energy.ckcest.cn/data.
References
Agency, I. R. E. (2016). Renewable Energy Outlook for Asean. IRENA & ACE. https://www.irena.org/publications/2016/Oct/Renewable-Energy-Outlook-for-ASEAN.
Cao, J., He, B., Qu, N., et al. (2023). Benefits evaluation method of an integrated energy system based on a fuzzy comprehensive evaluation method. Symmetry. https://doi.org/10.3390/sym15010084
Chen, F., et al. (2018). Investigations of business models under energy internet era. 2018 IEEE 2nd International Electrical and Energy Conference (CIEEC), 255–259. https://doi.org/10.1109/CIEEC.2018.8745842.
Cheng, L., & Yu, T. (2019). A new generation of AI: A review and perspective on machine learning technologies applied to smart energy and electric power systems. International Journal of Energy Research, 43(6), 1928–1973. https://doi.org/10.1002/er.4333.
Cheng, L., Qi, N., Zhang, F., et al. (2017). Energy internet: Concept and practice exploration. In 2017 IEEE conference on energy internet and energy system integration (EI2) (pp. 1–5). https://doi.org/10.1109/EI2.2017.8245533.
Demirci, A., Akar, O., & Ozturk, Z. (2022). Technical-environmental-economic evaluation of biomass-based hybrid power system with energy storage for rural electrification. Renewable Energy, 195, 1202–1217. https://doi.org/10.1016/j.renene.2022.06.097
Ding, S., Zeng, J., Hu, Z., et al. (2022). A peer-2-peer management and secure policy of the energy internet in smart microgrids. IEEE Transactions on Industrial Informatics, 18(8), 5689–5697. https://doi.org/10.1109/TII.2021.3133458
Du, J., Cai, C., Xie, Z., et al. (2020). Comprehensive energy efficiency evaluation of municipal power grid based on topsis method. In 2020 5th Asia Conference on Power and Electrical Engineering (ACPEE) (pp. 829–833). https://doi.org/10.1109/ACPEE48638.2020.9136435.
Ferrag, M. A., Derdour, M., Mukherjee, M., et al. (2019) Blockchain technologies for the internet of things: Research issues and challenges. IEEE Internet of Things Journal, 6(2), 2188–2204. https://doi.org/10.1109/JIOT.2018.2882794
Gangopadhyay, S., & Das, S. (2021). Fuzzy theory based quality assessment of multivariate electrical measurements of smart grids. IEEE Access, 9, 97686–97704. https://doi.org/10.1109/ACCESS.2021.3094671
Geng, J., Du, W., Yang, D., et al. (2021). Construction of energy internet technology architecture based on general system structure theory. Energy Reports, 7, 10–17. https://doi.org/10.1016/j.egyr.2021.09.037
He, K., Mi, Z., Zhang, J., et al. (2023). The polarizing trend of regional Co2 emissions in China and its implications. Environmental Science & Technology, 57(11), 4406–4414. https://doi.org/10.1021/acs.est.2c08052
He, Y. X., Jiao, J., Chen, R. J., et al. (2018). The optimization of chinese power grid investment based on transmission and distribution tariff policy: A system dynamics approach. Energy Policy, 113, 112–122. https://doi.org/10.1016/j.enpol.2017.10.062
Hong, L., Zhiwei, L., Qing, C., et al. (2020). Construction of the evaluation index system of the regional integrated energy system compatible with the hierarchical structure of the energy internet. In 2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2) (pp. 342–348). https://doi.org/10.1109/EI250167.2020.9346665.
Hong, Z., Feng, Y., Li, Z., et al. (2019). An integrated approach for multi-objective optimisation and Mcdm of energy internet under uncertainty. Future Generation Computer Systems, 97, 90–104. https://doi.org/10.1016/j.future.2019.02.046
Hou, H., Zhu, G., Chen, W., et al. (2015). Energy internet risk assessment framework. IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), 2015, 1–5. https://doi.org/10.1109/APPEEC.2015.7380955
Iqbal, J., Khand, M., Talha, M., et al. (2018). A generic internet of things architecture for controlling electrical energy consumption in smart homes. Sustainable Cities and Society, 43, 443–450. https://doi.org/10.1016/j.scs.2018.09.020
Ishida, H. (2015). The effect of ICT development on economic growth and energy consumption in Japan. Telematics and Informatics, 32(1), 79–88. https://doi.org/10.1016/j.tele.2014.04.003
Jamali, A., & Alam, M. A. (2019). Approximate relations between manhattan and euclidean distance regarding latin hypercube experimental design. Journal of Physics Conference Series, 1366(1), 012030. https://doi.org/10.1088/1742-6596/1366/1/012030
Jiang, H., Gao, Y., Jun, L., et al. (2019). The comprehensive benefit analysis of regional energy interconnection based on system dynamics method. Journal of Global Energy Interconnection, 2(1), 16–26. https://doi.org/10.19705/j.cnki.issn2096-5125.2019.01.003
Kabir, K. H., Aurko, S. Y., & Rahman, M. S. (2021). Smart power management in OIC countries: A critical overview using swot-ahp and hybrid mcdm analysis. Energies, 14(20), 1. https://doi.org/10.3390/en14206480
Kamruzzaman, M., Bhusal, N., & Benidris, M. (2022). A convolutional neural network-based approach to composite power system reliability evaluation. International Journal of Electrical Power & Energy Systems, 135, 107468. https://doi.org/10.1016/j.ijepes.2021.107468
Li, C., Miao, X., Zhang, C., et al. (2019). Research on benefit evaluation method of integrated energy system project based on combination weight. IOP Conference Series Earth and Environmental Science, 227(4), 042061. https://doi.org/10.1088/1755-1315/227/4/042061
Li, D. (1995). Membership clouds and membership cloud generators. Computer Research and Development, 32(6), 15–20.
Li, D., Cheung, D., Shi, X. M., et al. (1998). Uncertainty reasoning based on cloud models in controllers. Computers & Mathematics with Applications, 35(3), 99–123. https://doi.org/10.1016/S0898-1221(97)00282-4
Li, F., Li, N., Ma, X., et al. (2022a). Selection of energy internet economic value indicators based on interpretative structural modeling. International Conference on Artificial Intelligence in Everything (AIE), 2022, 37–41. https://doi.org/10.1109/AIE57029.2022.00015
Li, G., Xiang, F., & Shuang, W. (2020). Energy internet evaluation based on fuzzy comprehensive evaluation method. IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS), 2020, 611–616. https://doi.org/10.1109/ICAIIS49377.2020.9194914
Li, S., Liu, L., Wang, X., et al. (2021). Design on Business Strategy under Value Creation System of Energy Internet. In 2021 6th International Conference on Power and Renewable Energy (ICPRE) (1422–1427). https://doi.org/10.1109/ICPRE52634.2021.9635364.
Li, Y. & Chen, G. (2018). Great revolution: The business perspective of energy internet in China. https://doi.org/10.34890/343.
Li, Z., Luo, Z., Wang, Y., et al. (2022b). Suitability evaluation system for the shallow geothermal energy implementation in region by entropy weight method and topsis method. Renewable Energy, 184, 564–576. https://doi.org/10.1016/j.renene.2021.11.112
Liao, H., & Xu, Z. (2015). Consistency of the fused intuitionistic fuzzy preference relation in group intuitionistic fuzzy analytic hierarchy process. Applied Soft Computing, 35, 812–826. https://doi.org/10.1016/j.asoc.2015.04.015
Liao, Z., Ru, S., & Cheng, Y. (2023). A simulation study on the impact of the digital economy on Co2 emission based on the system dynamics model. Sustainability, 15(4), 1. https://doi.org/10.3390/su15043368
Lin, C., Ning, Q., Liting, T., et al. (2018). Exploration on the Value Innovation of Energy Internet Demonstration Park. In 2018 2nd IEEE conference on energy internet and energy system integration (EI2) (pp. 1–6). https://doi.org/10.1109/EI2.2018.8582558.
Liu, L., & Chen, S. (2018). The Application of Artificial Intelligence Technology in Energy Internet. In 2018 2nd IEEE conference on energy internet and energy system integration (EI2) (pp. 1–5). https://doi.org/10.1109/EI2.2018.8582096.
Liu, L., Wang, C., Cui, W., et al. (2021a). Evaluation of the development maturity of emerging industry of energy internet based on entropy weight matter-element model. In 2021a 11th International conference on power and energy systems (ICPES) (pp. 850–855). https://doi.org/10.1109/ICPES53652.2021.9683903.
Liu, P., & Liu, X. (2017). Multi-attribute group decision-making method based on cloud distance operators with linguistic information. International Journal of Fuzzy Systems, 19(4), 1011–1024. https://doi.org/10.1007/s40815-016-0279-5
Liu, T., Xu, B., Zheng, X., et al. (2021b). The impact mechanism and scenario simulation of energy internet on transition. Discrete Dynamics in Nature and Society, 2021, 5549991. https://doi.org/10.1155/2021/5549991
Liu, Z., Wang, X., Wang, W., et al. (2022a). An integrated topsis-oreste-based decision-making framework for new energy investment assessment with cloud model. Computational & Applied Mathematics, 41(1), 1. https://doi.org/10.1007/s40314-021-01751-9
Liu, Z. W., Xie, Q. Y., Dai, L., et al. (2022b). Research on comprehensive evaluation method of distribution network based on Ahp-entropy weighting method. Frontiers in Energy Research, 10, 1. https://doi.org/10.3389/fenrg.2022.975462
Mancasi, M., & Vatu, R. (2015). Smart grids reliability indices assessment using sequential Monte Carlo Method. In 2015 IEEE 15th international conference on environment and electrical engineering (EEEIC) (2066–2071). https://doi.org/10.1109/EEEIC.2015.7165495
National Development and Reform Commission, National Energy Administration, Ministry of Industry and Information Technology. Guidelines for Promoting Internet + Smart Energy Development. 2016. http://www.nea.gov.cn/2016-02/29/c_135141026.htm
Qin, G., Zhang, M., Yan, Q., et al. (2021). Comprehensive evaluation of regional energy internet using a fuzzy analytic hierarchy process based on cloud model: A case in China. Energy, 228, 120569. https://doi.org/10.1016/j.energy.2021.120569
Ramirez Lopez, L. J., Puerta Aponte, G., & Rodriguez Garcia, A. (2019). Internet of things applied in healthcare based on open hardware with low-energy consumption. Healthcare Informatics Research, 25(3), 230–235. https://doi.org/10.4258/hir.2019.25.3.230
Ren, S., Hao, Y., Xu, L., et al. (2021). Digitalization and energy: How does internet development affect China’s energy consumption? Energy Economics, 98, 105220. https://doi.org/10.1016/j.eneco.2021.105220
Şahin, M. (2021). A comprehensive analysis of weighting and multicriteria methods in the context of sustainable energy. International Journal of Environmental Science and Technology, 18(6), 1591–1616. https://doi.org/10.1007/s13762-020-02922-7
Samara, E., Andronikidis, A., Komninos, N., et al. (2022). The role of digital technologies for regional development: A system dynamics analysis. Journal of the Knowledge Economy. https://doi.org/10.1007/s13132-022-00951-w
Sani, A. S., Yuan, D. Jin, J., et al. (2019). Cyber security framework for internet of things-based energy internet. Future Generation Computer Systems, 93, 849–859. https://doi.org/10.1016/j.future.2018.01.029
Shangguan, P. (2021). Research on comprehensive evaluation indicator system of regional energy internet. In 4th International Symposium on Power Electronics and Control Engineering (ISPECE 2021), (Vol. 12080, pp. 777–786). https://doi.org/10.1117/12.2620237
Si, W. G., Lin, W. F., Xu, D. L., et al. (2022). Evaluation method of a new power system construction based on improved Lstm neural network. Journal of Computational Methods in Sciences and Engineering, 22(5), 1819–1832. https://doi.org/10.3233/JCM-226445
Su, X., Yang, X., Ran, Q., et al. (2022). Assessing the impact of energy internet and energy misallocation on carbon emissions: New insights from china. Environmental Science and Pollution Research, 29(16), 23436–23460. https://doi.org/10.1007/s11356-021-17217-8
Sun, X., Chen, M., Zhu, Y., et al. (2018). Research on the application of blockchain technology in energy internet. In 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2), 1–6. https://doi.org/10.1109/EI2.2018.8582599.
Tang, Q., Xu, W., Shen, L., et al. (2016). Urban energy internet: Concept and key technology (pp. 318–323). https://doi.org/10.1109/ICSAI.2016.7810975.
Tang, Y., Qing, X., Pengfei, Z., et al. (2022). Value creation, business model innovation and development plan of the energy internet. Journal of Global Energy Interconnection, 5(2), 105–115. https://doi.org/10.19705/j.cnki.issn2096-5125.2022.02.001
The National Development and Reform Commission, The National Energy Administration officially. The 13th Five-Year Plan for Electric Power Development. 2016. http://www.chinapower.com.cn/focus/20161108/64097.html
The National Development and Reform Commission, The National Energy Administration officially. 14th Five-Year Plan for Modern Energy System. 2022. http://www.gov.cn/zhengce/zhengceku/2022-03/23/content_5680759.htm
The National People’s Congress. The 14th Five-Year Plan. 2021. http://www.gov.cn/xinwen/2021-03/13/content_5592681.htm
Vaidya, O. S., & Kumar, S. (2006). Analytic hierarchy process: An overview of applications. European Journal of Operational Research, 169(1), 1–29. https://doi.org/10.1016/j.ejor.2004.04.028
Wang, B., & Zai, W. (2018). Factors affecting the benefit of the investment subjects of the global energy internet. IOP Conference Series: Materials Science and Engineering, 392(4), 042026. https://doi.org/10.1088/1757-899X/392/4/042026/meta
Wang, B., Zai, W., & IOP. (2018). Analysis of key factors affecting investors under the global energy internet. In 2018 International conference of green buildings and environmental management (GBEM) (p. 186). https://doi.org/10.1088/1755-1315/186/4/012004/meta.
Wang, D., Li, Y., Zhang, Q., et al. (2022a). Research on standards for information supportive system in district energy internet construction. Journal of Physics: Conference Series, 2195, 012020. https://doi.org/10.1088/1742-6596/2195/1/012020/meta
Wang, S., Zhou, X., Meng, X., et al. (2021a). Electricity Value-Added Service Business Model under Energy Internet. In 2021a 3rd Asia energy and electrical engineering symposium (AEEES) (pp. 1016–1023). https://doi.org/10.1109/AEEES51875.2021.9403011.
Wang, X. J., Jiang, R. M., Zhang, P., et al. (2018). An economic benefit evaluation model and its application for optimizing transmission capacity of multinational interconnections. CSEE Journal of Power and Energy Systems, 4(4), 444–451. https://doi.org/10.17775/CSEEJPES.2017.00200
Wang, Y., W. Xu, C. Liu, et al. (2022b). Evaluation Methods for the Development of New Power Systems Based on Cloud Model. In 2022b 12th International conference on power and energy systems (ICPES) (pp. 298–303). https://doi.org/10.1109/ICPES56491.2022.10072835.
Wang, Y., Zhang, J., Pan, C., et al. (2021b). Multi-dimensional performance evaluation index review of integrated and intelligent energy (in Chinese). Journal of Global Energy Interconnection, 4(3), 207–225. https://doi.org/10.19705/j.cnki.issn2096-5125.2021.03.002
Wu, J., & Tran, N. K. (2018). Application of blockchain technology in sustainable energy systems: An overview. Sustainability, 10(9), 3067. https://doi.org/10.3390/su10093067.
Wu, F. F., Varaiya, P. P., & Hui, R. S. Y. (2015). Smart grids with intelligent periphery: An architecture for the energy internet. Engineering, 1(4), 436–446. https://doi.org/10.1502/J-ENG-2015111
Wu, G. D., Duan, K. F., Zuo, J., et al. (2017). Integrated sustainability assessment of public rental housing community based on a hybrid method of Ahp-entropy weight and cloud model. Sustainability, 9(4), 603. https://doi.org/10.3390/su9040603
Wu, H., Kong, W., & Wu, X. (2022). Comprehensive benefit evaluation of rural energy internet in different application scenarios.
Wu, Y., Wu, Y., Guerrero, J. M., et al. (2021). A comprehensive overview of framework for developing sustainable energy internet: From things-based energy network to services-based management system. Renewable & Sustainable Energy Reviews. https://doi.org/10.1016/j.rser.2021.111409
Xie, A., Li, P., Tong, Z., et al. (2021). Comprehensive Benefit Evaluation Method of Energy Internet Platform Based on Cloud Model. In 2021 2nd International conference on big data and artificial intelligence and software engineering (ICBASE(ICBASE 2021) (pp. 736–742). https://doi.org/10.1109/ICBASE53849.2021.00144.
Xie, A., Li, P., Zheng, Y., et al. (2022). Investment Value Evaluation of Energy Internet Business Based on Topsis Method. In 2022 7th Asia conference on power and electrical engineering (ACPEE) (pp. 364–368). https://ieeexplore.ieee.org/abstract/document/9783970/.
Xing, L., Xue, M., & Hu, M. (2019). Dynamic simulation and assessment of the coupling coordination degree of the economy–resource–environment system: Case of Wuhan City in China. Journal of Environmental Management, 230, 474–487. https://doi.org/10.1016/j.jenvman.2018.09.065
Xu, X. Q., Xie, J. L., Wang, H. H., et al. (2022). Online education satisfaction assessment based on cloud model and fuzzy topsis. Applied Intelligence, 52(12), 13659–13674. https://doi.org/10.1007/s10489-022-03289-7
Yang, F., Bai, C., & Zhang, Y. (2015). Research on the value and implementation framework of energy internet. Proceedings of the Chinese Society of Electrical Engineering, 35(14), 3495–3502. https://doi.org/10.13334/j.0258-8013.pcsee.2015.14.003.html
Yang, K., Ding, Y., Zhu, N., et al. (2018). Multi-criteria integrated evaluation of distributed energy system for community energy planning based on improved grey incidence approach: A case study in Tianjin. Applied Energy, 229, 352–363. https://doi.org/10.1016/j.apenergy.2018.08.016
Yang, S.-X., Zhu, C.-X., Qiao, L., et al. (2020). Dynamic assessment of energy internet’s emission reduction effect—A Case Study of Yanqing, Beijing. Journal of Cleaner Production, 272, 1263. https://doi.org/10.1016/j.jclepro.2020.122663
Yang, S., Zhang, D., & Li, D. (2019). A calculation model for Co2 emission reduction of energy internet: A case study of Yanqing. Sustainability, 11(9), 2502. https://doi.org/10.3390/su11092502
Yang, L. X., Sun, Q. Y., Zhang, N., et al. (2022). Indirect multi-energy transactions of energy internet with deep reinforcement learning approach. IEEE Transactions on Power Systems, 37(5), 4067–4077. https://doi.org/10.1109/TPWRS.2022.3142969.
Ying, Z., Hui, P., Ye, L., et al. (2021). Scenario analysis for carbon emission in energy internet. In 2021 11th International Conference on Power and Energy Systems (ICPES) (pp. 678–684). https://ieeexplore.ieee.org/abstract/document/9683829.
Yuan, K., Song, Y., Sun, C. B. et al. (2021). The planning evaluation method of the regional energy internet based on the Ahp. In 2021 IEEE IAS industrial and commercial power system ASIA (IEEE I&CPS ASIA 2021) (pp. 970–975). https://doi.org/10.1109/ICPSAsia52756.2021.9621547.
Zhang, D., Yang, S., & Li, D. (2019). A calculation model for Co2 emission reduction of energy internet: A case study of Yanqing. Sustainability, 11(9), 1. https://doi.org/10.3390/su11092502
Zhang, J., Hou, Y., Liu, S., et al. (2023). Can the energy internet promote China’s energy system to achieve carbon emission peak goal? Journal of Cleaner Production, 417, 1314. https://doi.org/10.1016/j.jclepro.2023.138014
Zhang, X., Xu, K., & He, M. (2022a). Development status and some considerations on energy internet construction in Beijing-Tianjin-Hebei Region. Heliyon, 8(1), 1. https://doi.org/10.1016/j.heliyon.2022.e08722
Zhang, X. Y., H. L. Wang, B. W. Wang, et al. (2021). Research on the Framework of the New Urban Energy Internet Demonstration Project. In 6th International conference on advances in energy resources and environment engineering (p. 647). https://doi.org/10.1088/1755-1315/647/1/012142/meta.
Zhang, Y., Deng, H., Yang, J., et al. (2022b). Impacts of renewable portfolio standard on carbon emission peaking and tradable green certificate market: A system dynamics analysis method. Frontiers in Energy Research, 10, 1. https://doi.org/10.3389/fenrg.2022.963177
Zhao, D., Li, C., Wang, Q., et al. (2020a). Comprehensive evaluation of national electric power development based on cloud model and entropy method and topsis: A case study in 11 countries. Journal of Cleaner Production, 277, 123190. https://doi.org/10.1016/j.jclepro.2020.123190
Zhao, J., & Wang, L. (2021). Research on the new power system during the 14th five-year plan. China Energy, 43(5), 17–21.
Zhao, Z., Li, H., Wang, X., et al. (2020b). Research on Evaluation Index System of Urban Energy Internet Development. IOP Conference Series Earth and Environmental Science, 446(2), 022052. https://doi.org/10.1088/1755-1315/446/2/022052/meta
Zhou, K. L., Yang, S. L., & Shao, Z. (2016). Energy internet: The business perspective. Applied Energy, 178, 212–222. https://doi.org/10.1016/j.apenergy.2016.06.052
Zhou, Z. Y., Xiong, F., Huang, B. Y. et al. (2017). Game-theoretical energy management for energy internet with big data-based renewable power forecasting. IEEE Access, 5, 5731–5746. https://doi.org/10.1109/ACCESS.2017.2658952.
Zuo, Z., Guo, H., Cheng, J., et al. (2021). How to achieve new progress in ecological civilization construction?—Based on cloud model and coupling coordination degree model. Ecological Indicators, 127, 107789. https://doi.org/10.1016/j.ecolind.2021.107789
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We gratefully acknowledge the following sources of financial support for this study: Major project of the National Social Science Foundation of China (Grant NO. 21&ZD108), Youth Program of National Natural Science Foundation of China (Grant NO. 72204230), National Social Science Foundation of China (Grant NO. 20BJL034), Sciences and Technology Foundation of the State Grid Corporation of China (NO. 52094021000 K).
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All authors contributed to the study conception and design. JZ was involved in conceptualization; methodology; validation; review and editing. WZ helped in methodology; software; original draft; formal analysis; data curation; review and editing. JL contributed to resources; review and editing; supervision; funding acquisition; project administration. TN was involved in conceptualization; methodology; original draft; review and editing. SL helped in software; review and editing. GL contributed to funding acquisition; project administration. ZL was involved in resources; funding acquisition. XW helped in resources; funding acquisition. All authors read and approved the final manuscript.
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Zhang, J., Zhang, W., Li, J. et al. A novelty evaluation of the impact of digitalization on energy internet value creation. Environ Dev Sustain (2023). https://doi.org/10.1007/s10668-023-03888-5
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DOI: https://doi.org/10.1007/s10668-023-03888-5