 Subjects -> CONSERVATION (Total: 128 journals)
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- Prediction method of energy consumption in industrial production based on
improved grey model-
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Authors: Vikas Kumar, Pooja Nanda
Pages: 101 - 112
Abstract: In order to reduce the prediction error of energy consumption, a method of energy consumption in industrial production based on improved grey model is proposed. After collecting the energy consumption data, the cluster analysis and interpolation method are used to realise the abnormal value processing and vacancy data processing of the energy consumption data. On this basis, the grey model is constructed, in which the state parameters of energy consumption are introduced, and the influence of production factor fluctuation on energy consumption is considered to realise the accurate prediction. The test results show that the relative error of the design method is less than 0.12% for the total electric energy consumption prediction results, less than 0.80% for the total steam energy consumption prediction results, and less than 0.85% for the total coal energy consumption prediction results.
Keywords: improved grey model; energy consumption; cluster analysis; interpolation method; energy consumption status parameters; fluctuation of production factors
Citation: International Journal of Global Energy Issues, Vol. 45, No. 2 (2023) pp. 101 - 112
PubDate: 2023-03-10T23:20:50-05:00
DOI: 10.1504/IJGEI.2023.129503
Issue No: Vol. 45, No. 2 (2023)
- Carbon emission measurement method of heavy industry based on LMDI
decomposition method-
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Authors: Vikas Kumar, Pooja Nanda
Pages: 113 - 124
Abstract: Aiming at the problems of poor accuracy and low efficiency of traditional measurement methods, this paper designed a measurement method of carbon emissions of heavy industry enterprises based on LMDI decomposition method. Firstly, the carbon emission factors are collected based on the emission coefficient method, and the carbon content in the production process of heavy industry enterprises is detected. Then, using LMDI decomposition method, the operation process of heavy industry enterprises is divided into production, transportation and storage links, and the carbon emissions generated by the above three links are combined with the carbon emission coefficient of the energy chain in the coal combustion process to complete the calculation of carbon emissions. Experimental results show that the measurement accuracy of this method can reach up to 96.8%, and the maximum monitoring amount of carbon emissions per unit time is 24.3 kg, indicating that it improves the measurement accuracy and efficiency.
Keywords: heavy industry enterprises; coal combustion; carbon emissions; to measure; LMDI decomposition method
Citation: International Journal of Global Energy Issues, Vol. 45, No. 2 (2023) pp. 113 - 124
PubDate: 2023-03-10T23:20:50-05:00
DOI: 10.1504/IJGEI.2023.129506
Issue No: Vol. 45, No. 2 (2023)
- Prediction of energy conservation and emission reduction potential of new
energy vehicle industry based on grey model-
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Authors: Hong Li, Chunyu Zhang
Pages: 125 - 137
Abstract: In order to overcome the problems of low accuracy and long time-consuming of traditional methods, a prediction method of energy conservation and emission reduction potential of new energy vehicle industry based on grey model is proposed. Determine the carbon emission of energy consumption of new energy vehicle industry and calculate the energy efficiency value of new energy vehicle industry. According to the calculation results of energy efficiency value, the grey correlation analysis method is used to determine the correlation degree between the prediction factors of energy conservation and emission reduction potential of automobile industry, and the correlation degree coefficient is introduced into the grey model for energy conservation and emission reduction potential prediction to realise the prediction of energy conservation and emission reduction potential. Experimental results show that the prediction accuracy of this method is up to 99.19%, and the maximum prediction time is 0.7 s and the minimum is 0.4 s.
Keywords: grey model; decoupling concept; grey correlation analysis; correction coefficient; conserve energy; reduce emissions
Citation: International Journal of Global Energy Issues, Vol. 45, No. 2 (2023) pp. 125 - 137
PubDate: 2023-03-10T23:20:50-05:00
DOI: 10.1504/IJGEI.2023.129505
Issue No: Vol. 45, No. 2 (2023)
- Industrial coal utilisation efficiency prediction based on Markov Chain
Model-
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Authors: Hui-Fang Zhang, Yun-Xia Yang
Pages: 138 - 152
Abstract: In order to solve the problems of high error interval band width, low-prediction accuracy and long prediction time in traditional methods, an industrial coal utilisation efficiency prediction method based on Markov Chain Model is proposed. Based on the combination of probability matrix and Markov Chain, the prediction model of industrial coal utilisation efficiency is constructed. The grey GM[1,1] method was used to optimise, adjust and modify the model, and the relevant data of industrial coal utilisation were input into the model, and the prediction results of industrial coal utilisation efficiency were obtained. Experimental results show that the error interval band width value of this method is 0.07, and the prediction accuracy of industrial coal utilisation efficiency is up to 95%. Only 4 s can predict the coal utilisation efficiency of 30 different regions, indicating that this method has high-prediction accuracy and good application effect.
Keywords: Markov chain model; industrial coal; utilisation efficiency; prediction model design
Citation: International Journal of Global Energy Issues, Vol. 45, No. 2 (2023) pp. 138 - 152
PubDate: 2023-03-10T23:20:50-05:00
DOI: 10.1504/IJGEI.2023.129507
Issue No: Vol. 45, No. 2 (2023)
- Risk evaluation method of renewable energy investment based on fuzzy
analytic hierarchy process-
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Authors: Weina Li, Zhinan Cui, Xiaochun Tang
Pages: 153 - 165
Abstract: Aiming at the problems of large error, long evaluation time and incomplete evaluation results of traditional methods, a risk evaluation method of renewable energy investment based on fuzzy analytic hierarchy process is proposed. Firstly, based on the theory of system dynamics, this paper analyses the risk factors of renewable energy investment. Secondly, the set of risk evaluation index factors and evaluation criteria are established. Thirdly, the evaluation index system is constructed, and the weight matrix is established by using the entropy weight method to calculate the specific weight of the evaluation index. Finally, the risk evaluation model of renewable energy investment based on fuzzy analytic hierarchy process is established to realise the fuzzy comprehensive evaluation of renewable energy investment risk. The experimental results show that the calculation error of this method is small and the evaluation time is short, it can realise the comprehensive evaluation of risk.
Keywords: fuzzy analytic hierarchy process; renewable energy; risk assessment; system dynamics; entropy weight method
Citation: International Journal of Global Energy Issues, Vol. 45, No. 2 (2023) pp. 153 - 165
PubDate: 2023-03-10T23:20:50-05:00
DOI: 10.1504/IJGEI.2023.129508
Issue No: Vol. 45, No. 2 (2023)
- Hedging behaviour in China's crude oil futures market
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Authors: Weina Li, Zhinan Cui, Xiaochun Tang
Pages: 166 - 181
Abstract: Hedging behaviour of hedgers in China's crude oil futures market has naturally become a hot topic in academia and industry. This paper examines the behaviour of hedgers in China's crude oil futures market from the perspective of risk premium. The topic selection of this paper is helpful to reflect the real behaviour pattern of China's crude oil futures hedging, and also provides a more reasonable trading strategy for real traders and a practical basis for exchanges to regulate the market. The results facilitate reasonable trading strategies for hedgers and practical basis for the regulator in China's crude oil futures market.
Keywords: China's crude oil futures market; risk premium; selective hedging; classic hedging
Citation: International Journal of Global Energy Issues, Vol. 45, No. 2 (2023) pp. 166 - 181
PubDate: 2023-03-10T23:20:50-05:00
DOI: 10.1504/IJGEI.2023.129498
Issue No: Vol. 45, No. 2 (2023)
- Optimisation of natural gas supply chain considering pipeline
transportation cost reformation in China-
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Authors: Jun Zhou, Daixin Zhang, Guangchuan Liang, Guancheng Wu, Nengjia He
Pages: 182 - 206
Abstract: Natural gas plays an important role in the transition to renewable energy. The China national pipeline network company was established in 2019 and the Natural Gas Supply Chain (NGSC) is now in the transition stage. In addition, the reform of the Pipeline Transportation Cost Mode (PTCM) would have a greater impact on the natural gas market and benefit the marketers. This paper proposed an NGSC linear programming model to maximise the marketers' profit under two PTCM during the supply period. The CPLEX solver is used to find out the optimal gas distribution. Then, a long-distance pipeline in China is selected to verify the accuracy of this model. The price of different gas types, the gas volume of different market users, as well as the marketer's gas distribution are studied. And finally comes the sensitivity analysis of peak shaving gas price and extra gas price and greenhouse gas emission costs. The results show that the reform of the PTCM has a great impact on the profit of the marketers and the lucrative boundary is achieved. By fully understanding the profit map, thereby guiding the management of the marketer.
Keywords: natural gas supply chain; natural gas marketer; pipeline transportation cost; optimisation
Citation: International Journal of Global Energy Issues, Vol. 45, No. 2 (2023) pp. 182 - 206
PubDate: 2023-03-10T23:20:50-05:00
DOI: 10.1504/IJGEI.2023.129493
Issue No: Vol. 45, No. 2 (2023)
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