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学者姓名：嵇灵
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Abstract ：
To address climate change and ensure energy security, biomass energy has become a popular renewable energy alternative to traditional fossil fuels. This study focuses on the strategic planning and tactical management problem of a regional biomass supply chain system with multiple feedstock and final products. A novel SVCbased data-driven robust optimization model is developed to provide the tradeoff solutions under uncertainties. Compared with the traditional robust optimization model, it can better depict the uncertain sets, reduce data redundancy, and provide less conservative strategies for decision makers according to their risk preferences. The proposed model is validated through a case study, Meizhou city in China. The results suggested the optimal investment scale and site for biorefineries and biomass power plants at the strategic planning level, as well as the feedstock supply network, inventory management, and production arrangement at the tactic management level. The optimal robust solutions can be derived by varying the envelope level of the uncertain sets. Moreover, sensitivity analysis is performed to investigate the influences of the variations of key parameters. It is found that the produced bioethanol and electricity lack cost advantages in the current situation, even with a 30 % reduction in main cost parameters. Insufficient biomass yield may require extra capital investment to satisfy bioenergy demand but with a higher supply cost. Thus, a high and long-term subsidy is necessary to facilitate the sustainable development of biomass and the low-carbon transition of the energy sector.
Keyword ：
Support vector clustering Support vector clustering Data-driven robust optimization Data-driven robust optimization Uncertain Uncertain Biomass supply chain system Biomass supply chain system
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| GB/T 7714 | Huang, Xianling , Ji, Ling , Xie, Yulei et al. Robust optimization of regional biomass supply chain system design and operation with data-driven uncertainties [J]. | FOOD AND BIOPRODUCTS PROCESSING , 2024 , 149 : 176-189 . |
| MLA | Huang, Xianling et al. "Robust optimization of regional biomass supply chain system design and operation with data-driven uncertainties" . | FOOD AND BIOPRODUCTS PROCESSING 149 (2024) : 176-189 . |
| APA | Huang, Xianling , Ji, Ling , Xie, Yulei , Luo, Zhiwei . Robust optimization of regional biomass supply chain system design and operation with data-driven uncertainties . | FOOD AND BIOPRODUCTS PROCESSING , 2024 , 149 , 176-189 . |
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Abstract ：
The rapid social and economic development has led to problems such as over-exploitation of water resources, strong demand for physical water resources, and disequilibrium of water resources load. Based on the current situation of the water resources system in Beijing-Tianjin-Hebei region, this study proposed an input-output analysis-assessment-prediction-optimization framework. A water resources dissipation environment extended multi-regional input-output model was established, and the spatial equilibrium of water resources load was evaluated comprehensively. Furthermore, a multi-dimensional spatial equilibrium optimal allocation for water resources was built to identify key nodes and sectors. The primary findings were as follows: (1) Shijiazhuang and Tangshan were the main cities with net virtual water outflow, while Beijing and Baoding were the primary recipients of net virtual water inflow; (2) The overall score for the spatial equilibrium assessment of water resource load was low, with dimension scores predominantly ranging between 0.2 and 0.6; (3) The key transfer nodes were predominantly concentrated on the "outflow from Shijiazhuang" and the "inflow to Cangzhou and Langfang" nodes. This research conducted an in-depth exploration of the direction of water resource transfers, the actual stress conditions, and the spatial equilibrium of water resources within the Beijing-Tianjin-Hebei region. Finally, the future adjustment strategy for water-intensive industries at the urban agglomeration scale was obtained.
Keyword ：
Spatial equilibrium optimal allocation Spatial equilibrium optimal allocation Multi-regional input-output model Multi-regional input-output model Beijing-Tianjin-Hebei region Beijing-Tianjin-Hebei region Virtual water Virtual water
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| GB/T 7714 | Luo, Zhiwei , Ji, Ling , Xie, Yulei . Multi-dimensional equilibrium optimal allocation of water resources in Beijing-Tianjin-Hebei region through spatial association network analysis [J]. | JOURNAL OF HYDROLOGY , 2024 , 642 . |
| MLA | Luo, Zhiwei et al. "Multi-dimensional equilibrium optimal allocation of water resources in Beijing-Tianjin-Hebei region through spatial association network analysis" . | JOURNAL OF HYDROLOGY 642 (2024) . |
| APA | Luo, Zhiwei , Ji, Ling , Xie, Yulei . Multi-dimensional equilibrium optimal allocation of water resources in Beijing-Tianjin-Hebei region through spatial association network analysis . | JOURNAL OF HYDROLOGY , 2024 , 642 . |
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Abstract ：
China has great potential for developing renewable energy to achieve its carbon neutrality goals. Orderly development of renewable energy is essential to enhance resource utilization efficiency and ensure safety during the energy system transition process. This study presents a thorough assessment of China's onshore wind power potential by considering the land suitability, the potential and temporal characteristics, and the impacts of climate change. The high-resolution maps combining wind resources with land conditions and climate scenarios are produced to provide insights into system planning, grid integration, and flexibility management. The results show that the capacity potential of onshore wind energy in China is 9.6 TW with an annual generation of 12.6 PWh, and 83 % of total capacity has a cost advantage with the levelized cost lower than the 60 $/MWh threshold. By comprehensively considering geographical, economic, and social criteria, around 8.1 % of the national territorial area is identified as the most suitable area for wind power development, primarily in Inner Mongolia and Xinjiang. The annual electricity generation from these areas can fulfill nearly 69 % of the nation's electricity demand. Future climate change projections indicate a remarkable generalized drop by 18 % in the north and a slight increase by 7 % in the south under the RCP 8.5 scenario. However, significant changes in wind resources are mostly within restricted areas, suggesting that future climate change would like to bring negative but limited impacts on wind power production in China.
Keyword ：
Land suitability Land suitability Climate change Climate change Wind energy Wind energy Spatial and temporal variability Spatial and temporal variability Potential assessment Potential assessment
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| GB/T 7714 | Ji, Ling , Li, Jiahui , Sun, Lijian et al. China's ' s onshore wind energy potential in the context of climate change [J]. | RENEWABLE & SUSTAINABLE ENERGY REVIEWS , 2024 , 203 . |
| MLA | Ji, Ling et al. "China's ' s onshore wind energy potential in the context of climate change" . | RENEWABLE & SUSTAINABLE ENERGY REVIEWS 203 (2024) . |
| APA | Ji, Ling , Li, Jiahui , Sun, Lijian , Wang, Shuai , Guo, Junhong , Xie, Yulei et al. China's ' s onshore wind energy potential in the context of climate change . | RENEWABLE & SUSTAINABLE ENERGY REVIEWS , 2024 , 203 . |
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Abstract ：
Bioethanol has emerged as a promising alternative to fossil fuels, but its commercialization is hindered by high costs and uncertainties surrounding feedstock supply and policies. To address these challenges, a two-stage stochastic robust programming model is developed for regional biorefineries planning and supply chain management with various technological choices and uncertainty fusions. The model maximizes total profits by optimizing site selection, alternative technology combinations, feedstock inventories, and accounting for uncertain and seasonally varying biomass supply. This method helps decision-makers achieve risk-aversion robust optimal solutions, tailored for a case study in Guangdong, China. The results suggest that installing 8 biorefineries using the LHW-SSF-A technique combination would be optimal. The desired feedstock warehouse capacity would be 358.48 ktons, with low utilization closely tied to seasonal crop harvests. Risk-averse decision makers would take conservative production strategies, potentially reducing investment in biorefineries, while market prices and subsidies could encourage fewer conservative investors.
Keyword ：
Two-stage stochastic programming Two-stage stochastic programming Robust programming Robust programming Biomass Biomass Supply chain management Supply chain management Bioethanol production Bioethanol production
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| GB/T 7714 | Huang, Xianling , Ji, Ling , Yin, Jianguang et al. Optimal design and robust operational management of regional bioethanol supply chain with various technological choices and uncertainty fusions [J]. | COMPUTERS & CHEMICAL ENGINEERING , 2023 , 182 . |
| MLA | Huang, Xianling et al. "Optimal design and robust operational management of regional bioethanol supply chain with various technological choices and uncertainty fusions" . | COMPUTERS & CHEMICAL ENGINEERING 182 (2023) . |
| APA | Huang, Xianling , Ji, Ling , Yin, Jianguang , Huang, Guohe . Optimal design and robust operational management of regional bioethanol supply chain with various technological choices and uncertainty fusions . | COMPUTERS & CHEMICAL ENGINEERING , 2023 , 182 . |
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Abstract ：
This study presents a novel decision-support framework for the bioethanol supply chain network planning and management under uncertainties. Under the holistic framework, the most suitable sites for biorefineries are first screened out by adopting a GIS-based multi-criteria decision-making approach. Then, a mixed-integer linear programming model combined with quantile-based scenario analysis is developed to determine the strategic planning (i.e. locations and size of biorefineries) and tactical management (i.e. biomass purchasing, feedstock transportation, bioethanol production, and product delivery) under uncertainties. The model can effectively search for reliable solutions under uncertainties and achieve tradeoff solutions with the consideration of decision makers' risk tolerance. The proposed framework is demonstrated through a case study in China. It is suggested to build seven biorefineries with a capacity of 100 million liters in Zhumadian city. Utilizing 41% of local agricultural residues could satisfy the bioethanol requirement in the transportation sector under the E20 policy. However, the estimated production cost of bioethanol in Zhumadian is very high, about 1.11 $/L, which makes it lose cost advantage in the fuel market. Thus, currently, effective subsidies, mandatory energy substitution policies, along other environmental regulatory measures are desired to promote the bioethanol industry development.
Keyword ：
Bioethanol supply chain Bioethanol supply chain Uncertainties Uncertainties GIS GIS Quantile-based scenario analysis Quantile-based scenario analysis MCDM MCDM
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| GB/T 7714 | Wang, Mengmeng , Ji, Ling , Xie, Yulei et al. Regional bioethanol supply chain optimization with the integration of GIS-MCDM method and quantile-based scenario analysis [J]. | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2023 , 351 . |
| MLA | Wang, Mengmeng et al. "Regional bioethanol supply chain optimization with the integration of GIS-MCDM method and quantile-based scenario analysis" . | JOURNAL OF ENVIRONMENTAL MANAGEMENT 351 (2023) . |
| APA | Wang, Mengmeng , Ji, Ling , Xie, Yulei , Huang, Guohe . Regional bioethanol supply chain optimization with the integration of GIS-MCDM method and quantile-based scenario analysis . | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2023 , 351 . |
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Abstract ：
Comprehensively understanding the factors influencing crime is a prerequisite for preventing and combating crime. Although some studies have investigated the relationship between environmental factors and property crime, the interaction between factors was not fully considered in these studies, and the explanation of complex factors may be insufficient. This paper explored the influence of environmental factors on property crime using factor regression and factor interaction based on data from the central city of Lanzhou, China. Our findings showed that: (1) The distribution of crime cases showed the pattern of a local multi-center. Shop density, hotel density, entertainment density and house price were the four dominant environmental drivers of property crime; (2) The relationship between the light intensity and property crime had different correlation explanations in temporal projection and spatial projection. There was a normal distribution curve between the number of property crimes and the Price-to-Earnings Ratio (PE Ratio) of the community house price; and (3) The results of the factor interaction indicated that the effect of all factors on crime showed a two-factor enhancement. As an important catalyst, shop density had the strongest interaction with other factors. Shop density gradient influenced the degree of interpretation of spatial heterogeneity of property crime.
Keyword ：
Bayesian linear regression (BLR) Bayesian linear regression (BLR) geo-detector geo-detector Lanzhou Lanzhou factor interaction factor interaction property crime property crime environmental factors environmental factors
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| GB/T 7714 | Sun, Lijian , Zhang, Guozhuang , Zhao, Dan et al. Explore the Correlation between Environmental Factors and the Spatial Distribution of Property Crime [J]. | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION , 2022 , 11 (8) . |
| MLA | Sun, Lijian et al. "Explore the Correlation between Environmental Factors and the Spatial Distribution of Property Crime" . | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 11 . 8 (2022) . |
| APA | Sun, Lijian , Zhang, Guozhuang , Zhao, Dan , Ji, Ling , Gu, Haiyan , Sun, Li et al. Explore the Correlation between Environmental Factors and the Spatial Distribution of Property Crime . | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION , 2022 , 11 (8) . |
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Abstract ：
This paper presents an integrated research framework for the techno-economic feasibility and optimal design of a hybrid energy system for a remote area. A mixed-integer linear programming model is developed for finding optimal solutions to satisfy electricity demand and ensure sustainability. The cost-efficiency and environmental benefits of the hybrid system under the stand-alone and grid-connected operation modes are evaluated and compared. Suifenhe, a remote border area in Northeast China was taken as the case study to verify this model. The results suggest that a grid-connected hybrid system consisting of solar power (28.17 MW), biomass generator (8.71 MW), and battery storage (79.51 MW) is the best economically feasible option to satisfy local electricity demand with the levelized cost of electricity of 0.1498 $/kWh. To achieve 100% electricity self-sufficiency, diesel generators would become the main component satisfying 70% of total demand due to the cost advantage and flexibility. Besides, a 100% renewable energy system is currently not economically feasible due to extremely high costs and considerable electricity supply surplus. Future decreasing PV capital cost and implementing carbon price would facilitate the development of renewable energy and the decarbonization of the power system.
Keyword ：
Sensitivity analysis Sensitivity analysis Photovoltaic Photovoltaic Levelized cost of energy Levelized cost of energy Remote area Remote area Biomass generator Biomass generator
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| GB/T 7714 | Ji, Ling , Liu, Zhengping , Wu, Yuxuan et al. Techno-economic feasibility analysis of optimally sized a biomass/PV/DG hybrid system under different operation modes in the remote area [J]. | SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS , 2022 , 52 . |
| MLA | Ji, Ling et al. "Techno-economic feasibility analysis of optimally sized a biomass/PV/DG hybrid system under different operation modes in the remote area" . | SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS 52 (2022) . |
| APA | Ji, Ling , Liu, Zhengping , Wu, Yuxuan , Huang, Guohe . Techno-economic feasibility analysis of optimally sized a biomass/PV/DG hybrid system under different operation modes in the remote area . | SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS , 2022 , 52 . |
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Abstract ：
Waste-to-energy technologies compatible with recycling are promising solutions for sustainable municipal waste management from both economic and environmental perspectives. This study focuses on the economic -environment-energy (3E) objective-driven integrated waste management optimization problems under deep complexities. A novel multi-objective programming model is developed to assist the optimal decision-making with the consideration of system profit, greenhouse gas emission, and energy recovery simultaneously. Be-sides, it advances existing optimization methods by incorporating interval-valued fuzzy numbers to tackle the ambiguity and the essential fuzziness in experts' judgment. It was verified by a case study from an urban district of Beijing, China. The optimum waste treatment facility planning and waste stream allocation strategies with multi-objective tradeoffs were obtained to support decision-making considering different preferences of impor-tance ranking. In general, incineration and anaerobic digestion would be the main technologies for waste disposal in the study area. Recycling would be greatly encouraged when pursuing more economic profits and greenhouse gas emission reduction. With withdrawing the subsidy in the future, the investment in anaerobic digestion would become less attractive. Meanwhile, the landfill with gas recovery would even become economically infeasible if there is no further reduction in cost. In addition, waste source separation is also a crucial factor for successful integrated waste management. It is suggested that a proper government subsidy and public participation in waste source separation would guarantee the sustainable development of the integrated waste management system.
Keyword ：
Waste management Waste management Multi-objective programming Multi-objective programming Waste-to-energy Waste-to-energy Interval-valued fuzzy parameters Interval-valued fuzzy parameters
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| GB/T 7714 | Liang, Xiaolin , Ji, Ling , Xie, Yulei et al. Economic-Environment-Energy (3E) objective-driven integrated municipal waste management under deep complexities - A novel multi-objective approach [J]. | SUSTAINABLE CITIES AND SOCIETY , 2022 , 87 . |
| MLA | Liang, Xiaolin et al. "Economic-Environment-Energy (3E) objective-driven integrated municipal waste management under deep complexities - A novel multi-objective approach" . | SUSTAINABLE CITIES AND SOCIETY 87 (2022) . |
| APA | Liang, Xiaolin , Ji, Ling , Xie, Yulei , Huang, Guohe . Economic-Environment-Energy (3E) objective-driven integrated municipal waste management under deep complexities - A novel multi-objective approach . | SUSTAINABLE CITIES AND SOCIETY , 2022 , 87 . |
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Abstract ：
As the total water resources consumption control and carbon mitigation continuous improvement, the weak water-carbon incorporate management is increasingly exposed. In this study, a water-carbon nexus assessment framework is proposed to analyze the nexus relationship between water consumption and carbon emission, and distinguishes the coupled water-carbon transmission intensity and the transfer paths under regional and industrial scales. According to the practical input-output table, water consumption, and carbon emission information, the framework is applied to Beijing-Tianjin-Hebei urban agglomeration (BTHUA), a population, resource, and trade intensive area of China. Inter-regional/intra-regional water consumption and carbon emission transfer fluxes between sectors, the pairwise ecological relationship, and the water-carbon nexus were analyzed. Results indicated that the water-carbon transfer indexes from Hebei to Beijing and Tianjin were 161.85 kg/m(3) and 113.88 kg/m(3) in the study period, along with the most water consumption and carbon emission, and the worst water-carbon nexus. From the industrial perspective, electricity and gas supplying industry provided 7.8% and 29.1% of the total carbon transfer in Tianjin and Hebei, as the most key node sectors on the water-carbon nexus in the BTHUA. The research provides valuably supporting the adjustment of the existing urban agglomeration water-carbon nexus management schemes.
Keyword ：
Environment -extended multi-region input-output model Environment -extended multi-region input-output model Water-carbon nexus Water-carbon nexus Urban agglomerations Urban agglomerations Assessment framework Assessment framework
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| GB/T 7714 | Luo, Zhiwei , Ji, Ling , Xie, Yulei et al. Water-carbon nexus relationship and interaction mechanism analysis within Beijing-Tianjin-Hebei urban agglomeration [J]. | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2022 , 321 . |
| MLA | Luo, Zhiwei et al. "Water-carbon nexus relationship and interaction mechanism analysis within Beijing-Tianjin-Hebei urban agglomeration" . | JOURNAL OF ENVIRONMENTAL MANAGEMENT 321 (2022) . |
| APA | Luo, Zhiwei , Ji, Ling , Xie, Yulei , Zhai, Liang , Cai, Yanpeng . Water-carbon nexus relationship and interaction mechanism analysis within Beijing-Tianjin-Hebei urban agglomeration . | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2022 , 321 . |
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Abstract ：
Energy and water are rapidly consumed as the most basic strategic resources of various nations. It is of vital importance to systematically explore the environmental and economic impacts of energy-water co-management policies. This study is to develop a multiperspective-driven factorial metabolic network analysis framework (MPDF) to (a) investigate the direct/indirect/total resource consumption response mechanisms induced by changes in production and consumption; (b) explore the factor interactions of different policies in diverse energy and water metabolic networks by initiating factorial analysis; (c) quantify the economic effects of co management policies by proposing multiple vulnerability indicators. A typical energy-dependent region, Shanxi Province, China was selected as a case study. The results indicated that the production-and consumption oriented policies have various guidelines for reducing direct and indirect energy-water consumption. Significant interactions in simulation results suggest synergistic effects across sectors. Considering that Shanxi's energy water nexus economic vulnerability is as high as 2.22%, it is recommended to prioritize the allocation of resources to sectors with significant factor effects to avoid economic losses. Implementing corresponding resource conservation policies for light industry, machinery manufacturing, construction can reduce water consumption by 18.8%. The findings are expected to provide a solid scientific basis for formulating co-management strategies to alleviate resource scarcities.
Keyword ：
Energy -water nexus scarcity Energy -water nexus scarcity Policy simulation Policy simulation Environmentally extended input -output Environmentally extended input -output network framework network framework analysis analysis Multiperspective-driven factorial metabolic Multiperspective-driven factorial metabolic Factorial design Factorial design
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| GB/T 7714 | Zhang, Jinbo , Xie, Yulei , Liu, Lirong et al. Multiperspective-driven factorial metabolic network analysis framework for energy-water nexus vulnerability assessment and management-policy simulation [J]. | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2022 , 315 . |
| MLA | Zhang, Jinbo et al. "Multiperspective-driven factorial metabolic network analysis framework for energy-water nexus vulnerability assessment and management-policy simulation" . | JOURNAL OF ENVIRONMENTAL MANAGEMENT 315 (2022) . |
| APA | Zhang, Jinbo , Xie, Yulei , Liu, Lirong , Ji, Ling , Zhang, Yang , Guo, Huaicheng . Multiperspective-driven factorial metabolic network analysis framework for energy-water nexus vulnerability assessment and management-policy simulation . | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2022 , 315 . |
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