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Journal articles on the topic 'Energy input output analysis'

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Published: 10 December 2022

Last updated: 28 January 2023

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1

Fadavi, R., A. Keyhani, and S. S. Mohtasebi. "An analysis of energy use, input costs and relation between energy inputs and yield of apple orchard." Research in Agricultural Engineering 57, No. 3 (September 22, 2011): 88–96. http://dx.doi.org/10.17221/0/2010-rae.

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This study examines the energy balance between the input and the output per hectare for an apple orchard in the West Azarbaijan province in Iran (2008–2009). Data were collected by using random sampling method for 80 “face to face” questioners. Results showed that the highest share of energy consumption belongs to packaging (57%) and irrigation (16%). The highest share of expenses was found to be 34% and 30% for labor and packaging, respectively. The total energy input for apple production, energy productivity, net energy and output-input energy value were estimated as 101,505 MJ/ha, 0.23 kg/MJ, –56,320 MJ/ha and 0.44, respectively. Results indicated that 71% and 96.7% of total energy input were in indirect and non-renewable form, respectively. The benefit-cost ratio was estimated as 1.77. The regression results revealed that all exogenous variables (for machinery, fertilizers, farmyard manure and packaging energies) were found statistically significant. The packaging had the highest impact (3.23). According to the benefit-cost ratio, large farms were more successful in economic performance.

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2

Liu, Hai Qing, and En Ping Liu. "Energy Balance Analysis in Hainan Province's Agriculture Sector." Applied Mechanics and Materials 195-196 (August 2012): 1249–53. http://dx.doi.org/10.4028/www.scientific.net/amm.195-196.1249.

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This paper collected energy input-output data of Hainan Province agriculture sector in 21 years (1988-2008).All the direct and indirect inputs of energy for the production of main crops in Hainan were evaluated.The inputs and outputs were calculated by multiplying the amounts of inputs and outputs by their energy equivalents.The results showed that total energy input increased from 16.06 in 1988 to 38.39GJha-1 in 2008, total output energy increased from 83.92 in 1988 to 149.06GJha-1 in 2008. The net energy gain was a positive value,but a majority of the input energy emanates from non-renewable sources of energy.The energy ratio was estimated to be 5.04 and showed a declining trend during the period.This indicates that increased use of inputs ha-1 in production was accompanied by a much less increase in the output levels.Improvements in fertilizer application can significantly affect the energy efficiency of Hainan agriculture sector.

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3

Ozkan, Burhan, Handan Akcaoz, and Cemal Fert. "Energy input–output analysis in Turkish agriculture." Renewable Energy 29, no. 1 (January 2004): 39–51. http://dx.doi.org/10.1016/s0960-1481(03)00135-6.

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4

Han, Kun-Taik, Hye-Min Kim, and Seung-Hoon Yoo. "The Economic Effects of Integrated-Energy Business : An Input-Output Analysis." Journal of Energy Engineering 21, no. 1 (March 31, 2012): 47–54. http://dx.doi.org/10.5855/energy.2012.21.1.047.

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5

Bekhet, Hussain Ali, and Azlina Abdullah. "Energy Use in Agriculture Sector: Input-Output Analysis." International Business Research 3, no. 3 (June 11, 2010): 111. http://dx.doi.org/10.5539/ibr.v3n3p111.

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Many sectors rely on energy as input to produce output. Even though the use of energy in agriculture sector is not as high as in other sectors, it is important to study the connectedness between the two sectors as there is no study done so far to show the linkages between them in Malaysia. Input-output analysis has been used to study the connectedness degree between the two sectors using input-output data for 1991-2000. The direct and total backward linkages analyses have shown that there is a significant increase in the use of energy in agriculture sector for the 1991-2000 period but the connectedness is still weak. Among the three energy-related sectors namely; crude oil, natural gas & coal, petrol & coal industries and electricity & gas, it was found that the agriculture sector depends more on inputs from petrol & coal industries as compared to the other two sectors. Based on these results, some policy implications have been proposed to help the decision-makers in economic planning especially on implementing policies related to energy and agriculture sectors.

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6

Treloar, Graham J. "Extracting Embodied Energy Paths from Input–Output Tables: Towards an Input–Output-based Hybrid Energy Analysis Method." Economic Systems Research 9, no. 4 (December 1997): 375–91. http://dx.doi.org/10.1080/09535319700000032.

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7

Shepard, Jun U., and Lincoln F. Pratson. "Hybrid input-output analysis of embodied energy security." Applied Energy 279 (December 2020): 115806. http://dx.doi.org/10.1016/j.apenergy.2020.115806.

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8

Itoh, Yoshinori, and Toshihiko Nakata. "Input-Output Analysis for Installing Renewable Energy Systems." Energy & Environment 15, no. 2 (March 2004): 271–81. http://dx.doi.org/10.1260/095830504323153469.

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9

Mentzas, G. N., P. Capros, and J. E. Samouilidis. "REGIONAL INPUT-OUTPUT ANALYSIS OF ENERGY RESOURCE DEVELOPMENT." Papers in Regional Science 64, no. 1 (January 14, 2005): 117–27. http://dx.doi.org/10.1111/j.1435-5597.1988.tb01119.x.

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10

Karkacier, Osman, and Z. Gokalp Goktolga. "Input–output analysis of energy use in agriculture." Energy Conversion and Management 46, no. 9-10 (June 2005): 1513–21. http://dx.doi.org/10.1016/j.enconman.2004.07.011.

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11

Her, Jae-Jeong, and Hea-Jin Lim. "An analysis of Growth Factors on the City-Gas Industry by Input-Output Structural Decomposition Analysis." Journal of Energy Engineering 21, no. 2 (June 30, 2012): 158–67. http://dx.doi.org/10.5855/energy.2012.21.2.158.

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12

Born, Peter. "Input-output analysis: Input of energy, CO2, and work to produce goods." Journal of Policy Modeling 18, no. 2 (April 1996): 217–21. http://dx.doi.org/10.1016/0161-8938(95)00069-0.

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13

Li, Ji Hong, Xiao Min He, and Jing Xiang. "Research on Symbiotic Order of the Eco-Industrial Chain for Recycling Waste Materials Based on Input-Output Method." Advanced Materials Research 675 (March 2013): 21–24. http://dx.doi.org/10.4028/www.scientific.net/amr.675.21.

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The eco-industrial chain as an input and output of the ecosystem includes the economic and ecological inputs and outputs. The production processes between node enterprises stabilize the input-output structure of the eco-industrial chain through the linkage of material flow and energy flow. The analysis framework of input-output has built based on material flow. When the demand for the product changed, a new input-output matrix could be established. And then according to this matrix, relationships of material flow between node enterprises could be adjusted to realize the symbiotic order of the eco-industrial chain.

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14

Kosemani, Babajide S., and A. Isaac Bamgboye. "Energy input-output analysis of rice production in Nigeria." Energy 207 (September 2020): 118258. http://dx.doi.org/10.1016/j.energy.2020.118258.

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15

Yoshida, Yoshikuni, Hisashi Ishitani, and Ryuji Matsuhashi. "Modelling energy system using three-dimensional input-output analysis." International Journal of Global Energy Issues 13, no. 1/2/3 (2000): 86. http://dx.doi.org/10.1504/ijgei.2000.000871.

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16

Külekçi, Murat, and Adem Aksoy. "Input-output energy analysis in pistachio production of Turkey." Environmental Progress & Sustainable Energy 32, no. 1 (September 30, 2011): 128–33. http://dx.doi.org/10.1002/ep.10613.

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17

Li, Ai Jun, and Yin Xue Cao. "Thermodynamic Input-Output Analysis of Energy Utilization in Hubei Province." Advanced Materials Research 516-517 (May 2012): 74–79. http://dx.doi.org/10.4028/www.scientific.net/amr.516-517.74.

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This paper develops a thermodynamic input-output analysis of industrial economy for Hubei Province, which accounts for the ﬂow of cumulative exergy consumption of primary energy. Firstly, the basic situation of energy utilization in 2007 Hubei Province is analyzed. Then two different methods are adopted for thermodynamic input-output analysis in this paper, which are named as industrial cumulative exergy consumption and ecological cumulative exergy consumption. Results show that primary energy extraction sectors and raw material processing sectors have prominent peaks on both industrial cumulative exergy consumption and ecological cumulative exergy consumption for the case of Hubei Province. In terms of primary energy extraction sectors, traditional energy which has high exergy content should be substituted for new energy which has low exergy content. In terms of raw material processing sectors, high energy efficient and clean energy utilization technology should be promoted.

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18

Gowdy, J. M., and J. L. Miller. "Technological and Demand Change in Energy Use: An Input—Output Analysis." Environment and Planning A: Economy and Space 19, no. 10 (October 1987): 1387–98. http://dx.doi.org/10.1068/a191387.

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In this study input–output tables for the US economy are used to examine the changing pattern of energy use from 1963 to 1977. A method is developed for isolating some of the reasons behind the observed changes. We examine the impact of four types of technological change and two types of demand change on energy use. Two types of technological change that are of particular importance in the time period considered are changes in energy mix and changes due to substitution among nonenergy inputs.

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19

Önder, Hatice Gül. "Renewable energy consumption policy in Turkey: An energy extended input-output analysis." Renewable Energy 175 (September 2021): 783–96. http://dx.doi.org/10.1016/j.renene.2021.05.025.

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20

Lam, Ka Leung, Steven J. Kenway, Joe L. Lane, K. M. Nazmul Islam, and Romain Bes de Berc. "Energy intensity and embodied energy flow in Australia: An input-output analysis." Journal of Cleaner Production 226 (July 2019): 357–68. http://dx.doi.org/10.1016/j.jclepro.2019.03.322.

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21

Alghalith, Moawia, Xu Guo, Cuizhen Niu, and Wing-Keung Wong. "Input Demand Under Joint Energy and Output Prices Uncertainties." Asia-Pacific Journal of Operational Research 34, no. 04 (August 2017): 1750018. http://dx.doi.org/10.1142/s021759591750018x.

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In this paper, we analyze the impacts of joint energy and output prices uncertainties on the input demands in a mean–variance framework. We find that an increase in expected output price will surely cause the risk-averse firm to increase the input demand, while an increase in expected energy price will surely cause the risk-averse firm to decrease the demand for energy, but increase the demand for the non-risky inputs. Furthermore, we investigate the two cases with only uncertain energy price and only uncertain output price. In the case with only uncertain energy price, we find that the uncertain energy price has no impact on the demands for the non-risky inputs. We also show that the concepts of elasticity and decreasing absolute risk aversion (DARA) play an important role in the comparative statics analysis.

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22

Wang, Saige, Tao Cao, and Bin Chen. "Urban energy–water nexus based on modified input–output analysis." Applied Energy 196 (June 2017): 208–17. http://dx.doi.org/10.1016/j.apenergy.2017.02.011.

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23

Wu, Rong-Hwa, and Chia-Yon Chen. "On the application of input-output analysis to energy issues." Energy Economics 12, no. 1 (January 1990): 71–76. http://dx.doi.org/10.1016/0140-9883(90)90010-d.

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24

Li, Zheng, Lingying Pan, Feng Fu, Pei Liu, Linwei Ma, and Angelo Amorelli. "China's regional disparities in energy consumption: An input–output analysis." Energy 78 (December 2014): 426–38. http://dx.doi.org/10.1016/j.energy.2014.10.030.

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25

Hatirli, Selim Adem, Burhan Ozkan, and Cemal Fert. "An econometric analysis of energy input–output in Turkish agriculture." Renewable and Sustainable Energy Reviews 9, no. 6 (December 2005): 608–23. http://dx.doi.org/10.1016/j.rser.2004.07.001.

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26

Esengun, Kemal, Orhan Gündüz, and Gülistan Erdal. "Input–output energy analysis in dry apricot production of Turkey." Energy Conversion and Management 48, no. 2 (February 2007): 592–98. http://dx.doi.org/10.1016/j.enconman.2006.06.006.

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27

HAYASHI, Hideaki, Tatsuo OKA, and Yuichiro KODAMA. "ENERGY/CARBON INTENSITIES BASED ON 1990 INPUT/OUTPUT TABLE : Application of input/output analysis to buildings (Part 5)." Journal of Architecture and Planning (Transactions of AIJ) 63, no. 511 (1998): 75–81. http://dx.doi.org/10.3130/aija.63.75_4.

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28

YOKOYAMA, Kenji, Osamu SHIBATA, Noriyoshi YOKOO, and Tatsuo OKA. "ENERGY/CARBON INTENSITIES BASED ON 1995 INPUT/OUTPUT TABLE : Application of input/output analysis to buildings (Part 8)." Journal of Architecture and Planning (Transactions of AIJ) 65, no. 531 (2000): 75–80. http://dx.doi.org/10.3130/aija.65.75_2.

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29

Chen, Shaoqing, and Bin Chen. "Urban energy consumption: Different insights from energy flow analysis, input–output analysis and ecological network analysis." Applied Energy 138 (January 2015): 99–107. http://dx.doi.org/10.1016/j.apenergy.2014.10.055.

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30

Ashraf, Muhammad N., Muhammad H. Mahmood, Muhammad Sultan, Narges Banaeian, Muhammad Usman, Sobhy M. Ibrahim, Muhammad U. B. U. Butt, et al. "Investigation of Input and Output Energy for Wheat Production: A Comprehensive Study for Tehsil Mailsi (Pakistan)." Sustainability 12, no. 17 (August 24, 2020): 6884. http://dx.doi.org/10.3390/su12176884.

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The global increasing food demand can be met by efficient energy utilization in mechanized agricultural productions. In this study, input–output energy flow along with CO2 emissions for different wheat production cases (C-I to C-V) were investigated to identify the one that is most energy-efficient and environment-friendly case. Data and information about input and output sources were collected from farmers through questionnaires and face-to-face interviews. Input and output sources were converted into energy units by energy equivalents while CO2 emissions were calculated by emission equivalents. Data envelopment analysis (DEA) was conducted to compare technical efficiencies of the developed cases for optimization of inputs in inefficient cases. Results revealed that case C-Ⅴ (higher inputs, larger fields, the tendency of higher fertilizer application and tillage operations) has the highest energy inputs and outputs than the rest of the cases. Moreover, it possesses the lowest energy use efficiency and energy productivity. The highest CO2 emissions (1548 kg-CO2/ha) referred to C-Ⅴ while lowest emissions per ton of grain yield were determined in C-Ⅳ (higher electricity water pumping, moderate energy input). The grain yield increases directly with input energy in most of the cases, but it does not guarantee the highest values for energy indices. C-Ⅲ (moderate irrigations, educated farmers, various fertilizer applications) was found as an optimum case because of higher energy indices like energy use efficiency of 4.4 and energy productivity of 153.94 kg/GJ. Optimum input and better management practices may enhance energy proficiency and limit the traditionally uncontrolled CO2 emissions from wheat production. Therefore, the agricultural practices performed in C-Ⅲ are recommended for efficient cultivation of wheat in the studied area.

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31

Liu, Hongtao, Youmin Xi, Ju’e Guo, and Xia Li. "Energy embodied in the international trade of China: An energy input–output analysis." Energy Policy 38, no. 8 (August 2010): 3957–64. http://dx.doi.org/10.1016/j.enpol.2010.03.019.

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32

Bayasgalankhuu, Lyankhua, Sara Ilahi, Wenshan Wei, and Yongchang Wu. "Energy Analysis on Wheat Yield of Mongolian Agriculture." Processes 10, no. 2 (January 18, 2022): 190. http://dx.doi.org/10.3390/pr10020190.

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Agricultural policies should be aimed at enhancing production per unit area and help to reduce the cultivated area. To that end, it is critical to conserve soil fertility, promote ecological agriculture, employ climate change adaptation technology, significantly enhance irrigated agriculture, and decrease agricultural production risks. Sustainable agricultural production requires optimized land usage, increased energy efficiency, reduced use of fossil fuels, and minimized environmental consequences. Energy has been used in agriculture in a dramatically increased manner, and the agri-food chain now accounts for 30% of the total global energy use. Energy analysis quantifies the amount of energy used in agricultural production, so it may be used to optimize energy consumption and boost energy efficiency, further propelling the sustainable development of agriculture. Recently, the Mongolian government has expressed concerns about how to realize food sustainability and self-sufficiency in wheat production and agriculture, while also maintaining environmental sustainability. However, there is a substantial study gap between agriculture and energy analysis in Mongolia. This study investigated energy consumption and the effects of energy inputs and energy types on the agricultural production of Mongolia from 2005 to 2018. The output was calculated based on the annual wheat equivalent for the 14 major provinces as a whole. The output level is given as a function of human labor, machinery, electricity, diesel fuel, fertilizers, pesticides, irrigation water, and seed energy, and the yield and different energy inputs are determined using the ordinary least squares of the Cobb–Douglas function. Total energy input grew from 2359.50 MJ ha−1 in 2005 to 3047.61 MJ ha−1 in 2018, while total output energy increased from 2312.08 MJ ha−1 to 4562.56 MJ ha−1. During this period, the energy use efficiency (input–output ratio), energy productivity, and net energy of wheat production were studied. The fertilizer inputs were statistically significant. The contribution of nitrogen, diesel, and irrigation water towards the production level was 3.52, 3.09, and 2.33, respectively. As a result, the data indicated that non-renewable, direct, and indirect energy sources all had a positive impact on the output level. Furthermore, non-renewable energy in Mongolian agriculture has been used in a significantly increased manner.

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33

Pearson, P. J. G. "Proactive Energy-Environment Policy Strategies: A Role for Input — Output Analysis?" Environment and Planning A: Economy and Space 21, no. 10 (October 1989): 1329–48. http://dx.doi.org/10.1068/a211329.

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This paper contains a consideration of the recent arguments in favour of adopting ‘anticipate and prevent’ or ‘proactive’ energy — environment policy strategies, in place of the ‘reactive’ strategies that are a feature of many current approaches to policymaking in this area. The roles that energy — environment modelling might play in investigating alternative scenarios and proactive policy strategies are then examined. The focus is on the advantages and disadvantages of using Input — Output analysis and related mathematical programming techniques to provide information for the policymaking process. Of course, Input — Output analysis is neither the only nor the ideal approach to energy — environment modelbuilding. However, despite acknowledged conceptual and practical limitations of applying Input — Output analysis in this area, it is suggested there is a case for considering its further application, particularly in the context of the United Kingdom, not least because it enables a general equilibrium approach to be implemented.

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34

KANAGAWA, Taku, Tohru FUTAWATARI, and Hdefumi IMURA. "Urban energy and environmental analysis based on an input-output model." ENVIRONMENTAL SYSTEMS RESEARCH 19 (1991): 70–75. http://dx.doi.org/10.2208/proer1988.19.70.

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35

Sidhpuria, M. S., P. S. Sangwan, B. S. Jhorar, S. B. Mittal, S. K. Sharma, and Ashwani Kumar. "Resource Conservation Practices in Rainfed Pearl Millet-Energy Input-Output Analysis." Indian Journal of Dryland Agricultural Research and Development 29, no. 2 (2014): 83. http://dx.doi.org/10.5958/2231-6701.2014.01220.2.

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36

., D. Akbolat, K. Ekinci ., and V. Demircan . "Energy Input-Output and Economic Analysis of Rose Production in Turkey." Journal of Agronomy 5, no. 4 (September 15, 2006): 570–76. http://dx.doi.org/10.3923/ja.2006.570.576.

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37

Jongdeepaisal, Cholapat, and Seigo Nasu. "Hybrid input-output analysis to evaluate economic impacts of biomass energy." International Journal of Green Energy 17, no. 14 (September 3, 2020): 937–45. http://dx.doi.org/10.1080/15435075.2020.1814301.

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38

Reed, W., Shu Geng, and F. J. Hills. "Energy Input and Output Analysis of four Field Crops in California." Journal of Agronomy and Crop Science 157, no. 2 (August 1986): 99–104. http://dx.doi.org/10.1111/j.1439-037x.1986.tb00054.x.

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39

Shariful Islam, Abu Reza Md, and Julian B. Morison. "Sectoral Changes in Energy Use in Australia an Input-Output Analysis." Economic Analysis and Policy 22, no. 2 (September 1992): 161–75. http://dx.doi.org/10.1016/s0313-5926(92)50004-2.

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40

Gowdy, J. "Energy use in the U.S. service sector: An input-output analysis." Energy 12, no. 7 (July 1987): 555–62. http://dx.doi.org/10.1016/0360-5442(87)90096-x.

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41

Pan, Lingying, Pei Liu, Zheng Li, and Yonglian Wang. "A dynamic input–output method for energy system modeling and analysis." Chemical Engineering Research and Design 131 (March 2018): 183–92. http://dx.doi.org/10.1016/j.cherd.2017.11.032.

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42

Hannon, Bruce. "The role of input-output analysis of energy and ecologic systems." Annals of the New York Academy of Sciences 1185, no. 1 (January 2010): 30–38. http://dx.doi.org/10.1111/j.1749-6632.2009.05165.x.

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43

Pokushko, Mariia, Alena Stupina, Inmaculada Medina-Bulo, and Egor Dresvianskii. "Data Envelopment Analysis in Performance Assessment of Fuel and Energy Complex Enterprises." Bulletin of Kemerovo State University. Series: Political, Sociological and Economic sciences 2020, no. 2 (May 29, 2020): 251–62. http://dx.doi.org/10.21603/2500-3372-2020-5-2-251-262.

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The authors applied the Data Envelopment Analysis (DEA) to assess the performance of the heat supply system in the city of Krasnoyarsk. The article provides a detailed description of the DEA method, its positive sides and shortcomings. The research included a comparative analysis of performance assessment methods in terms of advantages and disadvantages. The DEA method proved the most convenient tool for measuring the production efficiency of an object. The authors modified the architecture of the universal decision support system into a DEA-based one. The DEA method also proved highly efficient in assessing the performance of the heat supply system in the city of Krasnoyarsk. The analysis made it possible to develop recommendations to improve the efficiency of the local heat supply system using the case of thirteen unites, e.g. boilers, heat and power plants, etc. The input indicator was represented by the available heat capacity. Heat output to the grid and emission mass were used as output indicators. Based on the available initial data, the authors constructed an output-oriented model for analyzing the functioning environment with one input and two outputs. They identified inefficient units of the Krasnoyarsk heat supply system and proposed optimization of input and output values for each unit to improve the functioning of the heat supply system as a whole. The developed for the upgrading of boilers and heat and power plants had an efficiency index in the range up to 1.

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44

Huang, X. Y., J. Q. Zhou, Z. Wang, L. C. Deng, and S. Hong. "Structural Decomposition Analysis of China’s Industrial Energy Consumption Based on Input-Output Analysis." IOP Conference Series: Earth and Environmental Science 63 (May 2017): 012041. http://dx.doi.org/10.1088/1755-1315/63/1/012041.

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45

Deng, Wei. "The Analysis of Energy and Environmental Efficiency Based on Input-Output Model." Applied Mechanics and Materials 34-35 (October 2010): 1253–57. http://dx.doi.org/10.4028/www.scientific.net/amm.34-35.1253.

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Input-output method can conveniently analyze energy consumption and environmental load for iron and steel enterprises. It can visually express production manufacturing statement and the consumption of energy and non-energy. Mathematical models are helpful for quantitative analysis and data handling. In addition, it’s useful to analyze main affected factors. Unit process energy consumption and steel ratio directly affect energy efficiency, which can be analyzed by e-p method.

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46

Neagoe, Mircea, Radu Saulescu, Codruta Jaliu, and Petru A. Simionescu. "A Generalized Approach to the Steady-State Efficiency Analysis of Torque-Adding Transmissions Used in Renewable Energy Systems." Energies 13, no. 17 (September 3, 2020): 4568. http://dx.doi.org/10.3390/en13174568.

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The paper presents a general approach to the steady-state efficiency analysis of one degree of freedom (1-DOF) speed increasers with one or two inputs, and one or two outputs, applicable to wind, hydro and marine-current power generating systems. The mechanical power flow, and the efficiency of this type of complex speed increasers, are important issues in the design and development of new power-generating systems. It is revealed that speed increases, with in-parallel transmission of the mechanical power from the wind or water rotors to the electric generator, have better efficiency than serial transmissions, but their efficiency calculus is still a challenging problem, solved in the paper by applying the decomposition method of complex speed increasers into simpler component planetary gear sets. Therefore, kinematic, steady-state torque and efficiency equations are derived for a generic 1-DOF speed increasers with two inputs and two outputs, obtained by connecting in parallel two gear mechanisms. These equations allow any speed increaser to be analysed with two inputs and one output, with one input and two outputs, and with one input and one output. We discuss a novel design of a patent-pending planetary-gear speed increaser, equipped with a two-way clutch, which can operate (in combination with the pitch adjustment of the rotors blades) in four distinct configurations. It was found that the mechanical efficiency of this speed increaser in the steady-state regime is influenced by the interior kinematic ratios, the input-torque ratio and by the meshing efficiency of its individual gear pairs. The efficiency of counter-rotating dual-rotor systems was found to be the highest, followed by systems with counter-rotating electric generator, and both have higher efficiency than conventional systems with one rotor and one electric generator with fixed-stator.

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47

Liu, Hongtao, and Juanjuan Lei. "The impacts of urbanization on Chinese households' energy consumption: An energy input-output analysis." Journal of Renewable and Sustainable Energy 10, no. 1 (January 2018): 015903. http://dx.doi.org/10.1063/1.5020077.

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48

Adelaja, Adesoji, and Anwarul Hoque. "A Multi-Product Analysis of Energy Demand in Agricultural Subsectors." Journal of Agricultural and Applied Economics 18, no. 2 (December 1986): 51–64. http://dx.doi.org/10.1017/s0081305200006105.

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AbstractA multi-product cost function model was used to analyze energy demand in various agricultural subsectors. This approach has advantages over previously used approaches since it reduces aggregation bias, considers technological jointness, and provides various disaggregative measures related to energy input demand. When fitted to West Virginia county level data, labor and miscellaneous inputs in crop and livestock production were found to be substitutes for energy, while capital, machinery, and fertilizer were complementary to energy. Energy demand was inelastic and increases in machinery prices had the largest reduction effect on energy demand. Technological change was found to be capital, machinery, and fertilizer using, but it was labor and energy saving. Analyses indicated that the elasticity of demand for energy inputs with respect to livestock output was significantly larger than the elasticity with respect to crop output.

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Yousif, Lotfie A., Mohamed Y. Mohamed, and Mohammed Ahmed AbdElmowla Ahmed. "Energy use analysis for sunflower (Helianthus annuus L.) production in the mechanized rain fed schemes eastern Sudan." Diyala Agricultural Sciences Journal 14, no. 2 (December 30, 2022): 43–51. http://dx.doi.org/10.52951/dasj.22140205.

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The objectives of this study were to analyze energy input-output and to identify the energy use patterns for sunflower production in the mechanized rain fed agricultural schemes eastern Sudan. The results revealed that the total energy input used to produce sunflower was 1671.33 MJ ha-1 and the total energy output was 11882.83 MJ ha-1. Sunflower production was efficient in energy consumption. The result showed that the energy ratio of output to input was greater than seven. The results indicated that the average net energy, the energy productivity and the specific energy was 10211.5 MJ ha-1, 0.28 kg. MJ-1 and 3.52 MJ kg -1, respectively. Fuel energy input was the highest among the energy input items while hand labor energy input was lower. These results indicate the dependence of sunflower production in rain fed agricultural schemes eastern Sudan on machinery. This necessitated the availability and readiness of the relevant and appropriate machineries as well as sufficient amount of fuel. The results also revealed that the energy profitability was 6.11 and human energy profitability was 1165.83 MJ h-1.The direct energy input was greater than the indirect energy input. Similarly, non-renewable energy was much greater than renewable energy. The established information is useful to manage and to sustain the productivity of sunflower crop in the mechanized rain fed schemes eastern Sudan

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NAKANO, Satoshi, and Ayu WASHIZU. "An Input-output Analysis of Two Green Microalgae Oil Production Systems." Journal of the Japan Institute of Energy 95, no. 1 (2016): 123–38. http://dx.doi.org/10.3775/jie.95.123.

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