Analysis of Dynamic Biogas Consumption in Chinese Rural Areas at Village, Township, and County Levels
Understanding the characteristics of biogas demand in rural areas is essential for on-demand biogas production and fossil fuel offsetting. However, the spatiotemporal features of rural household energy consumption are unclear. This paper developed a rural biogas demand forecasting model (RBDM) based...
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MDPI AG
2025-01-01
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| Series: | Agriculture |
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| Online Access: | https://www.mdpi.com/2077-0472/15/2/149 |
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| author | Gongyi Li Tao Luo Jianghua Xiong Yanna Gao Xi Meng Yaoguo Zuo Yi Liu Jing Ma Qiuwen Chen Yuxin Liu Yichong Xin Yangjie Ye |
| author_facet | Gongyi Li Tao Luo Jianghua Xiong Yanna Gao Xi Meng Yaoguo Zuo Yi Liu Jing Ma Qiuwen Chen Yuxin Liu Yichong Xin Yangjie Ye |
| author_sort | Gongyi Li |
| collection | DOAJ |
| description | Understanding the characteristics of biogas demand in rural areas is essential for on-demand biogas production and fossil fuel offsetting. However, the spatiotemporal features of rural household energy consumption are unclear. This paper developed a rural biogas demand forecasting model (RBDM) based on the hourly loads of different energy types in rural China. The model requires only a small amount of publicly available input data. The model was verified using household energy survey data collected from five Chinese provinces and one year’s data from a village-scale biogas plant. The results showed that the predicted and measured biogas consumption and dynamic load were consistent. The relative error of village biogas consumption was 11.45%, and the dynamic load showed seasonal fluctuations. Seasonal correction factors were incorporated to improve the model’s accuracy and practicality. The accuracy of the RBDM was 19.27% higher than that of a static energy prediction model. Future research should verify the model using additional cases to guide the design of accurate biogas production and distribution systems. |
| format | Article |
| id | doaj-art-1406b4d322604d9f9ae443c340bfa3f0 |
| institution | Kabale University |
| issn | 2077-0472 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agriculture |
| spelling | doaj-art-1406b4d322604d9f9ae443c340bfa3f02025-01-24T13:15:54ZengMDPI AGAgriculture2077-04722025-01-0115214910.3390/agriculture15020149Analysis of Dynamic Biogas Consumption in Chinese Rural Areas at Village, Township, and County LevelsGongyi Li0Tao Luo1Jianghua Xiong2Yanna Gao3Xi Meng4Yaoguo Zuo5Yi Liu6Jing Ma7Qiuwen Chen8Yuxin Liu9Yichong Xin10Yangjie Ye11College of Architecture and Urban Planning, Qingdao University of Technology, Qingdao 266033, ChinaBiogas Institute of Ministry of Agriculture (BIOMA), Chengdu 610041, ChinaRural Energy and Environment Agency of Jiangxi Province, Nanchang 335000, ChinaCollege of Architecture and Urban Planning, Qingdao University of Technology, Qingdao 266033, ChinaCollege of Architecture and Urban Planning, Qingdao University of Technology, Qingdao 266033, ChinaCollege of Architecture and Urban Planning, Qingdao University of Technology, Qingdao 266033, ChinaBiogas Institute of Ministry of Agriculture (BIOMA), Chengdu 610041, ChinaRural Energy and Environment Agency of Jiangxi Province, Nanchang 335000, ChinaBiogas Institute of Ministry of Agriculture (BIOMA), Chengdu 610041, ChinaRural Energy and Environment Agency of Jiangxi Province, Nanchang 335000, ChinaRural Energy and Environment Agency of Jiangxi Province, Nanchang 335000, ChinaBiogas Institute of Ministry of Agriculture (BIOMA), Chengdu 610041, ChinaUnderstanding the characteristics of biogas demand in rural areas is essential for on-demand biogas production and fossil fuel offsetting. However, the spatiotemporal features of rural household energy consumption are unclear. This paper developed a rural biogas demand forecasting model (RBDM) based on the hourly loads of different energy types in rural China. The model requires only a small amount of publicly available input data. The model was verified using household energy survey data collected from five Chinese provinces and one year’s data from a village-scale biogas plant. The results showed that the predicted and measured biogas consumption and dynamic load were consistent. The relative error of village biogas consumption was 11.45%, and the dynamic load showed seasonal fluctuations. Seasonal correction factors were incorporated to improve the model’s accuracy and practicality. The accuracy of the RBDM was 19.27% higher than that of a static energy prediction model. Future research should verify the model using additional cases to guide the design of accurate biogas production and distribution systems.https://www.mdpi.com/2077-0472/15/2/149forecasting modelrural energy surveycase studyconsumption amountconsumption rate |
| spellingShingle | Gongyi Li Tao Luo Jianghua Xiong Yanna Gao Xi Meng Yaoguo Zuo Yi Liu Jing Ma Qiuwen Chen Yuxin Liu Yichong Xin Yangjie Ye Analysis of Dynamic Biogas Consumption in Chinese Rural Areas at Village, Township, and County Levels Agriculture forecasting model rural energy survey case study consumption amount consumption rate |
| title | Analysis of Dynamic Biogas Consumption in Chinese Rural Areas at Village, Township, and County Levels |
| title_full | Analysis of Dynamic Biogas Consumption in Chinese Rural Areas at Village, Township, and County Levels |
| title_fullStr | Analysis of Dynamic Biogas Consumption in Chinese Rural Areas at Village, Township, and County Levels |
| title_full_unstemmed | Analysis of Dynamic Biogas Consumption in Chinese Rural Areas at Village, Township, and County Levels |
| title_short | Analysis of Dynamic Biogas Consumption in Chinese Rural Areas at Village, Township, and County Levels |
| title_sort | analysis of dynamic biogas consumption in chinese rural areas at village township and county levels |
| topic | forecasting model rural energy survey case study consumption amount consumption rate |
| url | https://www.mdpi.com/2077-0472/15/2/149 |
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