Pub Date : 2023-07-11DOI: 10.13052/spee1048-5236.4241
Du Zhong, Yao Haiyan
With the advancement of the industrial Internet of Things era, and the use of renewable energy technologies, smart grid has become the main form of power grid, and data has become a key link. The problem of data islands is common, and the data value, especially the commercial value, has yet to be tapped. This phenomenon is particularly prominent in power grid enterprises. Therefore, a data management model and method for power grid enterprises are proposed. The model aims at data asset management of power grid enterprises, reveals the process of extracting, modeling, analyzing and value mining of power grid data based on big data BI technology, and puts forward a practical and easy-to-land data asset management method, which really solves the problems of how to collect, store, manage and use data. Finally, taking the linkage between power marketing data and power grid planning in a certain area of Hangzhou, Zhejiang Province as a specific scenario, the BI analysis conclusion of relevant marketing data is displayed, which realizes the echo of conventional application and advanced application, reduces investment practically, improves economic benefits, and demonstrates the feasibility and scientificity of the method.
{"title":"Research on Power Grid Data Asset Management Based on Big Data BI Analysis – The Role of Renewable Energy Technologies","authors":"Du Zhong, Yao Haiyan","doi":"10.13052/spee1048-5236.4241","DOIUrl":"https://doi.org/10.13052/spee1048-5236.4241","url":null,"abstract":"With the advancement of the industrial Internet of Things era, and the use of renewable energy technologies, smart grid has become the main form of power grid, and data has become a key link. The problem of data islands is common, and the data value, especially the commercial value, has yet to be tapped. This phenomenon is particularly prominent in power grid enterprises. Therefore, a data management model and method for power grid enterprises are proposed. The model aims at data asset management of power grid enterprises, reveals the process of extracting, modeling, analyzing and value mining of power grid data based on big data BI technology, and puts forward a practical and easy-to-land data asset management method, which really solves the problems of how to collect, store, manage and use data. Finally, taking the linkage between power marketing data and power grid planning in a certain area of Hangzhou, Zhejiang Province as a specific scenario, the BI analysis conclusion of relevant marketing data is displayed, which realizes the echo of conventional application and advanced application, reduces investment practically, improves economic benefits, and demonstrates the feasibility and scientificity of the method.","PeriodicalId":35712,"journal":{"name":"Strategic Planning for Energy and the Environment","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49296509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-11DOI: 10.13052/spee1048-5236.4246
Junchao Yang, Tianfeng Li
In order to predict China’s electricity consumption demand under situation of fast growth of the new infrastructure, a medium- and long-term electricity consumption demand prediction model based on LEAP is proposed, which calculates the overall electricity consumption of the country according to the activity level and intensity of typical new infrastructure and other sectors. Five different scenarios are set for comparison. The results show that under the basic scenario, China’s electricity consumption will reach 7408 billion kWh in 2035, in which the consumption of new infrastructure accounts for 31.31%.While under the other four scenarios, China’s electricity consumption will reach to the minimum of 7319 billion kWh under the scenario of improvement of energy-saving technology, and the maximum of 7525 billion kWh under the scenario of fast development of the new infrastructure, with higher contributions of the consumption of commercial charging, data centers and 5G base station. Relevant suggestions are put forward from the aspects of new infrastructure construction, development of clean energy and technical standards to reduce the electricity consumption of new infrastructure.
{"title":"Medium- and Long-term Forecast of China’s Electricity Consumption Considering the Fast Growth of New Infrastructure","authors":"Junchao Yang, Tianfeng Li","doi":"10.13052/spee1048-5236.4246","DOIUrl":"https://doi.org/10.13052/spee1048-5236.4246","url":null,"abstract":"In order to predict China’s electricity consumption demand under situation of fast growth of the new infrastructure, a medium- and long-term electricity consumption demand prediction model based on LEAP is proposed, which calculates the overall electricity consumption of the country according to the activity level and intensity of typical new infrastructure and other sectors. Five different scenarios are set for comparison. The results show that under the basic scenario, China’s electricity consumption will reach 7408 billion kWh in 2035, in which the consumption of new infrastructure accounts for 31.31%.While under the other four scenarios, China’s electricity consumption will reach to the minimum of 7319 billion kWh under the scenario of improvement of energy-saving technology, and the maximum of 7525 billion kWh under the scenario of fast development of the new infrastructure, with higher contributions of the consumption of commercial charging, data centers and 5G base station. Relevant suggestions are put forward from the aspects of new infrastructure construction, development of clean energy and technical standards to reduce the electricity consumption of new infrastructure.","PeriodicalId":35712,"journal":{"name":"Strategic Planning for Energy and the Environment","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43058924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Regional low carbon will play an important role in the path of achieving the “double carbon” goal, and there are still many key technologies to be broken in its planning research. In this paper, an optimal scheduling model of integrated energy system with multiple energy supply devices is established by using Beetle Antennae Search-Particle Swarm Optimization (BAS-PSO) algorithm. First, in the scheduling model, a carbon trading mechanism is introduced and a stepped carbon trading cost model is constructed to constrain the carbon emissions of the plant. Then, using drosophila algorithm, the premise of whether wind power generation and photovoltaic power generation need to be built is determined by judging the economics of wind power generation and photovoltaic power generation in the construction area, and then the target power consumption curve and new energy power supply output curve are fitted. Then use the life cycle analysis method to analyze the carbon emissions generated by electric energy storage equipment, consider the carbon trading mechanism in the system economic operation model, and solve the model by BAS-PSO algorithm to overcome the problems of local optimum and slow convergence speed. Finally, a typical park integrated energy system is simulated to analyze the economic operation conditions and energy efficiency level of the system before and after participation in demand response. The innovation of this paper lies in considering the carbon trading mechanism and solving with the optimized BAS-PSO algorithm. Considering carbon trading can effectively improve the system wind power consumption capacity, and the optimized BAS-PSO algorithm improves the defects of traditional PSO. The simulation analysis results show that the established optimal scheduling model with multiple energy supply devices can realize the optimal operation of the integrated energy system of the park in the demand response environment; the improved BAS-PSO finds the lowest energy consumption within 100 iterations in 21 out of 50 iterations; the improved BAS-PSO algorithm reduces the energy consumption by 27.1 kW on average.
{"title":"BAS-PSO Algorithm for Integrated Energy System Optimization of Multiple Energy Supply Facilities","authors":"Wei Xiong, Xiangyue Chen, Chengxiang Liu, Meng Huang, Jiapeng Tong","doi":"10.13052/spee1048-5236.4245","DOIUrl":"https://doi.org/10.13052/spee1048-5236.4245","url":null,"abstract":"Regional low carbon will play an important role in the path of achieving the “double carbon” goal, and there are still many key technologies to be broken in its planning research. In this paper, an optimal scheduling model of integrated energy system with multiple energy supply devices is established by using Beetle Antennae Search-Particle Swarm Optimization (BAS-PSO) algorithm. First, in the scheduling model, a carbon trading mechanism is introduced and a stepped carbon trading cost model is constructed to constrain the carbon emissions of the plant. Then, using drosophila algorithm, the premise of whether wind power generation and photovoltaic power generation need to be built is determined by judging the economics of wind power generation and photovoltaic power generation in the construction area, and then the target power consumption curve and new energy power supply output curve are fitted. Then use the life cycle analysis method to analyze the carbon emissions generated by electric energy storage equipment, consider the carbon trading mechanism in the system economic operation model, and solve the model by BAS-PSO algorithm to overcome the problems of local optimum and slow convergence speed. Finally, a typical park integrated energy system is simulated to analyze the economic operation conditions and energy efficiency level of the system before and after participation in demand response. The innovation of this paper lies in considering the carbon trading mechanism and solving with the optimized BAS-PSO algorithm. Considering carbon trading can effectively improve the system wind power consumption capacity, and the optimized BAS-PSO algorithm improves the defects of traditional PSO. The simulation analysis results show that the established optimal scheduling model with multiple energy supply devices can realize the optimal operation of the integrated energy system of the park in the demand response environment; the improved BAS-PSO finds the lowest energy consumption within 100 iterations in 21 out of 50 iterations; the improved BAS-PSO algorithm reduces the energy consumption by 27.1 kW on average.","PeriodicalId":35712,"journal":{"name":"Strategic Planning for Energy and the Environment","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49113477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-11DOI: 10.13052/spee1048-5236.4247
Medani P. Bhandari
The nexus between land use and climate change is a critical aspect of sustainable development, and few places show this inter-relationship better than Nepal. This paper uses Nepal as an example to explore the interconnections between land use and climate change, highlighting the key challenges and opportunities. Nepal, with its diverse topography and ecosystems, is highly vulnerable to the impacts of climate change. The country’s unique land use patterns, including agriculture, forest cover, and urbanization, play a significant role in shaping its climate resilience and carbon balance. This paper highlights the complex relationship between land use and climate change in such an environment. Balancing land use practices, conserving forests, and biodiversity, and promoting sustainable agriculture are essential for achieving climate resilience and sustainable development. The paper shows that only by addressing the nexus between land use and climate change, can Nepal move towards a more sustainable and climate-resilient future.
{"title":"Using Nepal to understand the Nexus of Climate Change and Land-Use","authors":"Medani P. Bhandari","doi":"10.13052/spee1048-5236.4247","DOIUrl":"https://doi.org/10.13052/spee1048-5236.4247","url":null,"abstract":"The nexus between land use and climate change is a critical aspect of sustainable development, and few places show this inter-relationship better than Nepal. This paper uses Nepal as an example to explore the interconnections between land use and climate change, highlighting the key challenges and opportunities. \u0000Nepal, with its diverse topography and ecosystems, is highly vulnerable to the impacts of climate change. The country’s unique land use patterns, including agriculture, forest cover, and urbanization, play a significant role in shaping its climate resilience and carbon balance. This paper highlights the complex relationship between land use and climate change in such an environment. Balancing land use practices, conserving forests, and biodiversity, and promoting sustainable agriculture are essential for achieving climate resilience and sustainable development. The paper shows that only by addressing the nexus between land use and climate change, can Nepal move towards a more sustainable and climate-resilient future.","PeriodicalId":35712,"journal":{"name":"Strategic Planning for Energy and the Environment","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42732231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-11DOI: 10.13052/spee1048-5236.4243
Wangming Hu, Gulong Wang
In order to study the impact of modern community sustainable landscape design under deep learning nonlinear data and its role in public environmental perception, this paper discusses the traditional landscape design concept and the modern community sustainable landscape design concept under deep learning nonlinear data, and compares and analyzes the relevant elements, the functional performance of landscape architecture and the comprehensive effect through statistical methods. The results are statistically significant. Through analysis and verification, modern community sustainable landscape design based on deep learning nonlinear data can better promote the integration of landscape, humanities and environment, improve the quality of community environment, so as to improve the physical and mental health of the public and meet the public’s needs for the environment.
{"title":"Research on Sustainable Landscape Design and Public Environmental Perception of Modern Communities Based on Deep Learning Nonlinear Data","authors":"Wangming Hu, Gulong Wang","doi":"10.13052/spee1048-5236.4243","DOIUrl":"https://doi.org/10.13052/spee1048-5236.4243","url":null,"abstract":"In order to study the impact of modern community sustainable landscape design under deep learning nonlinear data and its role in public environmental perception, this paper discusses the traditional landscape design concept and the modern community sustainable landscape design concept under deep learning nonlinear data, and compares and analyzes the relevant elements, the functional performance of landscape architecture and the comprehensive effect through statistical methods. The results are statistically significant. Through analysis and verification, modern community sustainable landscape design based on deep learning nonlinear data can better promote the integration of landscape, humanities and environment, improve the quality of community environment, so as to improve the physical and mental health of the public and meet the public’s needs for the environment.","PeriodicalId":35712,"journal":{"name":"Strategic Planning for Energy and the Environment","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43026793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-11DOI: 10.13052/spee1048-5236.4242
Chun Hyunjin, Huynh Thanh Quyen
The environment changes rapidly due to climate change. This situation has a great influence on the agricultural sector. In particular, prices of agricultural products rise as space for producing agricultural products around the world decreases. To solve this problem, smart farm is recognized as major technologies in the future society. In particular, in the era of the 4th Industrial Revolution, new technologies such as the Internet of Things (IOT) and artificial intelligence will be installed in smart farm. In addition, with the development of the Internet of Things (IOT) technology, temperature, humidity, and concentration of fluids in plant factories can be monitored and controlled with smart-phone through various sensors. This IoT technology is recognized as a very important technology for smart farm. In addition, a sustainable smart farm model by converging with eco-friendly IT technology is also important. Therefore, in this paper, a study was conducted on the system design of eco-friendly smart farm using the Internet of Thing. Such smart farm technology can remotely manage plants through the Internet of Things. The research methods of this study are as follows. First, a literature study was conducted in this paper. Based on this literature study, the researcher conducted a field survey on smart farm. The researcher visited this space in person and conducted in-depth interviews with operators and researchers. The researcher analyzed the results derived through this survey and suggested the design principle for the eco-friendly smart farm system. In addition, this study proposes a method for using the Internet of Things and renewable energy for smart farms in preparation for the era of climate change. The results of this study can be theoretical basic data for changes in the agricultural field in the era of the Fourth Industrial Revolution.
{"title":"A Study on the System Design of Eco-Friendly Smart Farm Using the Internet of Things and Renewable Energy","authors":"Chun Hyunjin, Huynh Thanh Quyen","doi":"10.13052/spee1048-5236.4242","DOIUrl":"https://doi.org/10.13052/spee1048-5236.4242","url":null,"abstract":"The environment changes rapidly due to climate change. This situation has a great influence on the agricultural sector. In particular, prices of agricultural products rise as space for producing agricultural products around the world decreases. To solve this problem, smart farm is recognized as major technologies in the future society. In particular, in the era of the 4th Industrial Revolution, new technologies such as the Internet of Things (IOT) and artificial intelligence will be installed in smart farm. In addition, with the development of the Internet of Things (IOT) technology, temperature, humidity, and concentration of fluids in plant factories can be monitored and controlled with smart-phone through various sensors. This IoT technology is recognized as a very important technology for smart farm. In addition, a sustainable smart farm model by converging with eco-friendly IT technology is also important. Therefore, in this paper, a study was conducted on the system design of eco-friendly smart farm using the Internet of Thing. Such smart farm technology can remotely manage plants through the Internet of Things. The research methods of this study are as follows. First, a literature study was conducted in this paper. Based on this literature study, the researcher conducted a field survey on smart farm. The researcher visited this space in person and conducted in-depth interviews with operators and researchers. The researcher analyzed the results derived through this survey and suggested the design principle for the eco-friendly smart farm system. In addition, this study proposes a method for using the Internet of Things and renewable energy for smart farms in preparation for the era of climate change. The results of this study can be theoretical basic data for changes in the agricultural field in the era of the Fourth Industrial Revolution.","PeriodicalId":35712,"journal":{"name":"Strategic Planning for Energy and the Environment","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47417231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.13052/spee1048-5236.4233
Chang Da, Tianyi Zhang, Guohan Ma, Jingfeng Wang, Ruochen Liu
In the power system, power marketing is a very important work. How to evaluate whether the currently used power marketing strategy is efficient and useful has always been the most important concern of the power system. This paper proposes an efficient electricity marketing strategy evaluation method based on multi-dimensional clustering algorithm, aiming to evaluate whether a new policy has an incentive effect on enterprises through the means of big data. First, we use big data to group motivated users, and then analyze the effect of personalized marketing and key marketing on target customer groups. Based on the existing marketing methods, the influence of different target groups is analyzed, and finally the feasibility of the proposed method is verified through two experiments. In the A and B companies selected in Experiment 1, the average errors of the predicted value and the actual value are 1.4% and 1.2%, respectively. For the 12 industries in the C area selected in experiment 2, the average error between the predicted value and the actual value is 0.55%. Both experiments show that the method proposed in this paper has certain applicability. The method in this paper can be applied to the marketing process of the power supply company, and the corresponding promotion strategy is put forward, which is helpful to improve the management level of the power supply enterprise and increase the economic income of the power supply enterprise.
{"title":"Evaluation Method of Efficient Power Marketing Strategy Based on Multi-dimensional Clustering Algorithm","authors":"Chang Da, Tianyi Zhang, Guohan Ma, Jingfeng Wang, Ruochen Liu","doi":"10.13052/spee1048-5236.4233","DOIUrl":"https://doi.org/10.13052/spee1048-5236.4233","url":null,"abstract":"In the power system, power marketing is a very important work. How to evaluate whether the currently used power marketing strategy is efficient and useful has always been the most important concern of the power system. This paper proposes an efficient electricity marketing strategy evaluation method based on multi-dimensional clustering algorithm, aiming to evaluate whether a new policy has an incentive effect on enterprises through the means of big data. First, we use big data to group motivated users, and then analyze the effect of personalized marketing and key marketing on target customer groups. Based on the existing marketing methods, the influence of different target groups is analyzed, and finally the feasibility of the proposed method is verified through two experiments. In the A and B companies selected in Experiment 1, the average errors of the predicted value and the actual value are 1.4% and 1.2%, respectively. For the 12 industries in the C area selected in experiment 2, the average error between the predicted value and the actual value is 0.55%. Both experiments show that the method proposed in this paper has certain applicability. The method in this paper can be applied to the marketing process of the power supply company, and the corresponding promotion strategy is put forward, which is helpful to improve the management level of the power supply enterprise and increase the economic income of the power supply enterprise.","PeriodicalId":35712,"journal":{"name":"Strategic Planning for Energy and the Environment","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41674477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.13052/spee1048-5236.4232
Etaib Alamin, N. Kamaruzaman, H. Kamar
Energy-efficient measures are being increasingly implemented in the building sector to reduce the increasing energy consumption with the growing population and the rapid development of urban building layouts. In hot and humid climates, energy-saving measures for the building envelope elements have attracted increasing interest in research and practice due to their effectiveness in upgrading the building energy performance by reducing the amount of heat gain and solar glare to the building’s indoor environments. Accordingly, as evidenced by our review of the literature, an increasing number of publications on energy-saving measures for the building envelope are being published in peer-reviewed articles. However, a few literature overviews covering all possible energy-saving measures of building envelope elements, which can provide insight into determining the value of their effective parameters to achieve the best performance and evaluate the feasibility of energy efficiency improvements. This paper attempts to fill that gap by reviewing recent advances in energy-saving measures for building envelope elements and comparing their various parameters to suggest the best design options. This study summarised that applying individual measures to a certain degree is straightforward energy-saving potential. Otherwise, high energy-saving levels must incorporate an optimum combination of many energy-saving measures and balance their conflicting influences on energy performance criteria. This study may be handy for stakeholders responsible for decision-making during the design of new or retrofitting existing buildings.
{"title":"Building Envelopes Toward Energy-Savings in Hot and Humid Climates: A Review","authors":"Etaib Alamin, N. Kamaruzaman, H. Kamar","doi":"10.13052/spee1048-5236.4232","DOIUrl":"https://doi.org/10.13052/spee1048-5236.4232","url":null,"abstract":"Energy-efficient measures are being increasingly implemented in the building sector to reduce the increasing energy consumption with the growing population and the rapid development of urban building layouts. In hot and humid climates, energy-saving measures for the building envelope elements have attracted increasing interest in research and practice due to their effectiveness in upgrading the building energy performance by reducing the amount of heat gain and solar glare to the building’s indoor environments. Accordingly, as evidenced by our review of the literature, an increasing number of publications on energy-saving measures for the building envelope are being published in peer-reviewed articles. However, a few literature overviews covering all possible energy-saving measures of building envelope elements, which can provide insight into determining the value of their effective parameters to achieve the best performance and evaluate the feasibility of energy efficiency improvements. This paper attempts to fill that gap by reviewing recent advances in energy-saving measures for building envelope elements and comparing their various parameters to suggest the best design options. This study summarised that applying individual measures to a certain degree is straightforward energy-saving potential. Otherwise, high energy-saving levels must incorporate an optimum combination of many energy-saving measures and balance their conflicting influences on energy performance criteria. This study may be handy for stakeholders responsible for decision-making during the design of new or retrofitting existing buildings.","PeriodicalId":35712,"journal":{"name":"Strategic Planning for Energy and the Environment","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43713626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.13052/spee1048-5236.4236
Pengfei Mu, Yadong Ji, Yang Zhou, Z. Shi, De-qin Li
As China pays more attention to the protection of water resources, there are overlapping areas between the planned reservoir conservation area and planned coal mine field. In the coal mining process, a water-conducting fracture zone is formed after the roof of the goaf is damaged, and cracks also generated on the surface of the mining area. In order to study the effect of coal mining on the recharge of surface water into the reservoir in the land conservation area, FLAC3D and Visual MODFLOW are used to simulate the development law of water-conducting fracture zone and surface subsidence cracks in the roof of the coal seam after coal mining in the land conservation area of the reservoir. Prediction and analysis on the change of the reservoir recharge capacity after coal mining in the land reserve are conducted. The results show that the maximum growth height of the water-conducting fracture zone in the overlying strata of the goaf after coal mining in the secondary land conservation area of the reservoir is not connected with the surface subsidence fracture. However, coal mining induces partial aquifer drainage in the roof of the coal seam, increasing the amount of surface water flowing to groundwater. Therefore, the maximum drop in the water level of the reservoir is 0.19 m, and the maximum recharge of the reservoir is 52,900 m33/a, accounting for 0.89% of the total recharge. It demonstrates that coal mining in the secondary land conservation area has little effect on the recharge of the reservoir. On the basis of good ecological compensation, water saving and comprehensive utilization of mine water, coal mines need to further carry out research on mitigating the adverse effects of coal mining on the reservoir’s land conservation area.
{"title":"Based on the Numerical Simulation Analysis of the Impact of Coal Mining in the Land Conservation Area","authors":"Pengfei Mu, Yadong Ji, Yang Zhou, Z. Shi, De-qin Li","doi":"10.13052/spee1048-5236.4236","DOIUrl":"https://doi.org/10.13052/spee1048-5236.4236","url":null,"abstract":"As China pays more attention to the protection of water resources, there are overlapping areas between the planned reservoir conservation area and planned coal mine field. In the coal mining process, a water-conducting fracture zone is formed after the roof of the goaf is damaged, and cracks also generated on the surface of the mining area. In order to study the effect of coal mining on the recharge of surface water into the reservoir in the land conservation area, FLAC3D and Visual MODFLOW are used to simulate the development law of water-conducting fracture zone and surface subsidence cracks in the roof of the coal seam after coal mining in the land conservation area of the reservoir. Prediction and analysis on the change of the reservoir recharge capacity after coal mining in the land reserve are conducted. The results show that the maximum growth height of the water-conducting fracture zone in the overlying strata of the goaf after coal mining in the secondary land conservation area of the reservoir is not connected with the surface subsidence fracture. However, coal mining induces partial aquifer drainage in the roof of the coal seam, increasing the amount of surface water flowing to groundwater. Therefore, the maximum drop in the water level of the reservoir is 0.19 m, and the maximum recharge of the reservoir is 52,900 m33/a, accounting for 0.89% of the total recharge. It demonstrates that coal mining in the secondary land conservation area has little effect on the recharge of the reservoir. On the basis of good ecological compensation, water saving and comprehensive utilization of mine water, coal mines need to further carry out research on mitigating the adverse effects of coal mining on the reservoir’s land conservation area.","PeriodicalId":35712,"journal":{"name":"Strategic Planning for Energy and the Environment","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48651953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.13052/spee1048-5236.4235
H. Arora, N. Anwer, S. Narula
The study examines the sustainability disclosures of the Indian energy companies and maps these with respect to Sustainable Development Goals (SDGs). As a part of the study, eighteen energy companies’ publicly available sustainability disclosure data from their sustainability reports were analysed with respect to their performance towards their SDGs. The study has mapped sustainability disclosures and analysed the company’s contribution towards the SDGs by assessing the linked Global Reporting Initiative (GRI) indicators with the SDGs. To analyse the contribution towards SDGs, the criteria were applied to the GRI – compliant sustainability reports for the selected eighteen major energy companies. As a part of the methodology, the companies were categorized by the size of the companies (market capitalization), type (Govt. Vs Private) and Industry (as per UNFCCC segmentation under the Energy sector). The study discloses that SDG 10 and SDG 11 are among the SDGs for which most of the companies have not disclosed sustainability performance, whereas SDG 4, SDG 5 and SDG 9 are the SDGs for which the most contribution is evident as compared to other SDGs. The study contributes to the understanding of sustainability disclosure practises of the companies that are in different stages of adoption of sustainability reporting. The findings of the study contribute to making the disclosures of the company is more relevant to SDGs. Particularly, it is one of the first studies on Indian energy companies to assess sustainability disclosure performance in the context of SDGs.
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