Application of Gray Expansion Model in Energy Economic Analysis and Load Forecasting
DOI:
https://doi.org/10.13052/spee1048-5236.4313Keywords:
Energy consumption, gray theory, load capacity, DEA-Malmqusit model, LEAPS modelAbstract
Objective and effective prediction of energy consumption can not only optimize the energy consumption structure, but also provide important information for the government to formulate energy conservation and emission reduction measures. With the development of new energy sources and changes in the global energy consumption structure, historical energy data that are too old may no longer be reliable for forecasting, which leads to a decrease in the amount of information on energy, and the gray theory, which is applicable to “poor information”, has gained attention. Firstly, the optimization of energy economic objectives and transformation path methods at this stage is clarified; then, the DEA-Malmqusit model is used to improve the shortcomings of the traditional model that can only compare different cross-sections at the same time node, and to evaluate and analyze the full-factor multi-indicators of energy enterprises in terms of technological empowerment, environmental dynamics, and economic output efficiency; finally, the LEAPS-based energy system consumption and load capacity prediction model. The results show that the traditional algorithm is not accurate enough and has some deviation when the energy raw data fluctuates a lot. The algorithm proposed in this paper still gives a better prediction, predicting a city’s carbon emission to be 65,240,100 tons in 2024, with a 3.6% increase in energy output year by year.
Downloads
References
Li Nu, Wang Jianliang, Liu Rui, et al. Multi scenario concept of natural gas industry development under the goal of carbon neutrality [J] Natural Gas Industry, 2021, 41(2).
Zeng Shihong, Li Gen, Weng Zhixiong, et al. Research on the path of China’s energy transformation towards carbon peaking and carbon neutralization [J] Environmental Protection, 2021, 49(16): 26–29.
Li Zheng, Zhang Dongjie, Pan Lingying, et al. China’s low-carbon energy transformation path and suggestions under the “dual carbon” goal [J] Journal of Power Engineering, 2021, 41(11): 905–909.
Lin Boqiang, Zhan Yanhong, Sun Chuanwang Research on the bilateral coordinated development of energy supply and demand oriented to carbon neutralization [J] Governance Research, 2022, 38(3): 24.
Liu Peiji, Liu Fei, Wang Xu, et al. The theory and technology system of green manufacturing and its new framework [J] Journal of Mechanical Engineering, 2022, 57(19): 165–179.
Satterthwaite D. The implications of population growth and urbanization for climate change[J]. Environment and urbanization, 2009, 21(2): 545–567.
Gupta A, Gupta K. Short Term Solar Irradiation Prediction Framework Based on EEMD-GA-LSTM Method[J]. Strategic Planning for Energy and the Environment, 2022: 255–280.
Rahman S M, Kirshner J, Groh S, et al. A review of the energy-employment nexus in Bangladesh: Rural-urban electrification and sectoral occupation patterns[J]. Strategic Planning for Energy and the Environment, 2022: 317–344.
Zhang S, Wu S. Evaluation of Digital Rural Development from the Perspective of Rural Revitalization–Take Zhejiang Province as an Example[J]. Strategic Planning for Energy and the Environment, 2021: 121–144.
Li Xin’an, Li Hui Research on carbon emission effect of green technology innovation from the perspective of high-quality development of manufacturing industry [J] Innovative technology, 2021.
Lin S, Cai S, Sun J, et al. Influencing mechanism and achievement of manufacturing transformation and upgrading: Empirical analysis based on PLS-SEM model[J]. Journal of Manufacturing Technology Management, 2018, 30(1): 213–232.
Dong B, Ma X, Zhang Z, et al. Carbon emissions, the industrial structure and economic growth: Evidence from heterogeneous industries in China[J]. Environmental Pollution, 2020, 262: 114322.
Guo Xiaojun Research on the Extended Model and Application of Grey Self Memory Combination Prediction [D] Nanjing University of Aeronautics and Astronautics, 2015.
Zhang Xiao, Zhang Xidong Application of CGE model in resource and environmental economics [J] Urban and Environmental Studies, 2015 (2): 91–112.
Zhu Peiyu, Ling Wen Impact of different carbon emission peak scenarios on industrial structure – analysis based on dynamic CGE model [J] Financial Theory and Practice, 2020, 41(5): 110–118.
Li Xin’an Research on the driving role of regional innovation capability in improving the quality of economic development [J] Regional Economic Review, 2020, 2.
Zhang H. The impact on China’s economy of its accession to the WTO: A computable general equilibrium (CGE) analysis[M]. Northern Illinois University, 2002.
Li Qingxiang Analysis of China’s water transport carbon emission status and carbon reduction path [J] Transportation energy conservation and environmental protection, 2021.
Xie Hansheng, Huang Yin, Ma Long Analysis and Research on China’s Railway Energy Efficiency and Energy Conservation and Emission Reduction [J] Railway Labor Safety, Health and Environmental Protection, 2010, 37(3): 118–122.
Wu Xiaoping, Li Yusi, Liu Jiangwei Comparative analysis of railway energy consumption between China’s railways and major countries in the world [J] Science and Technology Bulletin, 2016, 34(2): 313–317.
Cui Jie, Liu Sifeng The Illness Problem of Grey Verhulst Extended Model [J] Control and Decision Making, 2014, 29(3): 567–571.
Wang Tiecheng Research on the influence of railway transport energy consumption factors based on econometric regression method [J] Railway Economic Research, 2021.
Gao Ruifeng Analysis on the relationship between energy economy and regional economic growth [J] SMEs in China, 2021.
Liu Wenjun, Li Jiao, Liu Xiuchun Empirical analysis on energy efficiency of China’s tourism industry under carbon emission constraints – based on SBM model and Tobit regression model [J] Journal of Central South Forestry University: Social Science Edition, 2017, 11(1): 40–46.
Chen Guangjiu New Trends of International Energy Economy and Strategic Choices for China’s Energy Economic Development [J] Journal of Changchun University, 2014, 24(5): 596–599.
Chen Q, Kang C, Xia Q, et al. Optimal Flexible Operation of a CO2
Capture Power Plant in a Combined Energy and Carbon Emission Market[J]. IEEE Transactions on Power Systems, 2012, 27(3): 1602–1609.
Liu J, Ye J, Yang C. Power Battery Recycling Mode and Decision-making Model for New Energy Vehicles Under the Background of Dual Carbon[J]. Strategic Planning for Energy and the Environment, 2022: 457–476.
Hu W, Wang G. Research on sustainable landscape design and public environmental perception of modern communities based on deep learning nonlinear data[J]. Strategic Planning for Energy and the Environment, 2022.
Lv Jiawei, Zhang Shenxi, Cheng Haozhong, et al. Overview of regional integrated energy system planning considering interconnection and interaction [J] Chinese Journal of Electrical Engineering, 2021.
Zhang Yunzhou, Zhang Ning, Dai Hongcai, et al. Analysis model construction and transformation path comparison of low carbon development of China’s power system [J] China Power, 2021, 54(3): 1–11.
Liu Yongqi, Chen Longxiang, Han Xiaoqi Analysis on key issues of new energy substitution in China under the energy transition [J] Chinese Journal of Electrical Engineering, 2022, 42(2): 515–524.
Voumik L C, Hossain M S, Islam M A, et al. Power generation sources and carbon dioxide emissions in brics countries: static and dynamic panel regression[J]. Strategic Planning for Energy and the Environment, 2022: 401–424.
Tian Feng, Jia Yanbing, Ren Haiquan, et al. Low carbon economic dispatch of integrated energy system “source r load” considering carbon capture system [J] Power grid technology, 2020, 44(9): 3346–3355.
Fan J L, Shen S, Xu M, et al. Cost-benefit comparison of carbon capture, utilization, and storage retrofitted to different thermal power plants in China based on real options approach[J]. Advances in Climate Change Research, 2020, 11(4): 415–428.
Lu Zhigang, Yang Yu, Geng Lijun, et al. Low carbon economic dispatch of electric heating integrated energy system based on Benders decomposition method [J] Chinese Journal of Electrical Engineering, 2018, 38(7): 1922–1934.
Wang R, Wang J, Teng Y. A Hybrid Evaluation Method of Ecological Environment Quality Based on Entropy and Matter-Element Extension Model[J]. Strategic Planning for Energy and the Environment, 2021: 387–406.
Yan Z, Cui C, Liao C. The Impact of Green Finance on Clean Power Generation: Evidence Based on China[J]. Strategic Planning for Energy and the Environment, 2021: 421–436.
https://aeeeuropeenergy.com/