Recently, broad applications can be found in optical remote sensing images (ORSI), such as in urban planning, military mapping, field survey, and so on. Target detection is one of its important applications. In the past few years, with the wings of deep learning, the target detection algorithm based on CNN has harvested a breakthrough. However, due to the different directions and target sizes in ORSI, it will lead to poor performance if the target detection algorithm for ordinary optical images is directly applied. Therefore, how to improve the performance of the object detection model on ORSI is thorny. Aiming at solving the above problems, premised on the one-stage target detection model-RetinaNet, this paper proposes a new network structure with more efficiency and accuracy, that is, a Transformer-Based Network with Deep Feature Fusion Using Carafe Operator (TRCNet). Firstly, a PVT2 structure based on the transformer is adopted in the backbone and we apply a multi-head attention mechanism to obtain global information in optical images with complex backgrounds. Meanwhile, the depth is increased to better extract features. Secondly, we introduce the carafe operator into the FPN structure of the neck to integrate the high-level semantics with the low-level ones more efficiently to further improve its target detection performance. Experiments on our well-known public NWPU-VHR-10 and RSOD show that mAP increases by 8.4% and 1.7% respectively. Comparison with other advanced networks also witnesses that our proposed network is effective and advanced.
{"title":"Transformer-Based Object Detection with Deep Feature Fusion Using Carafe Operator in Remote Sensing Image","authors":"Shenao Chen, Bingqi Wang, Chaoliang Zhong","doi":"10.4108/ew.3404","DOIUrl":"https://doi.org/10.4108/ew.3404","url":null,"abstract":"Recently, broad applications can be found in optical remote sensing images (ORSI), such as in urban planning, military mapping, field survey, and so on. Target detection is one of its important applications. In the past few years, with the wings of deep learning, the target detection algorithm based on CNN has harvested a breakthrough. However, due to the different directions and target sizes in ORSI, it will lead to poor performance if the target detection algorithm for ordinary optical images is directly applied. Therefore, how to improve the performance of the object detection model on ORSI is thorny. Aiming at solving the above problems, premised on the one-stage target detection model-RetinaNet, this paper proposes a new network structure with more efficiency and accuracy, that is, a Transformer-Based Network with Deep Feature Fusion Using Carafe Operator (TRCNet). Firstly, a PVT2 structure based on the transformer is adopted in the backbone and we apply a multi-head attention mechanism to obtain global information in optical images with complex backgrounds. Meanwhile, the depth is increased to better extract features. Secondly, we introduce the carafe operator into the FPN structure of the neck to integrate the high-level semantics with the low-level ones more efficiently to further improve its target detection performance. Experiments on our well-known public NWPU-VHR-10 and RSOD show that mAP increases by 8.4% and 1.7% respectively. Comparison with other advanced networks also witnesses that our proposed network is effective and advanced.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70857751","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}
P. Muthulakshmi, T. Tamilarasi, Tanmay Tapan Banerji, S. Albert, A. Raj, E. Aarthi
Climate change is one of the current threats facing the world. Pollution is the primary factor causing climate change, in it, air pollution plays a major part. Almost all developed and developing countries emit a lot of greenhouse gases (GHG). The transportation sector is responsible for the majority of GHG emissions. Nowadays, almost all nations make an effort to lower CO2 emissions from transportation. India also has a strategy to achieve zero emissions through several programmes. When considering ways to lower GHG emissions from the transportation sector, electric vehicles (EVs) are the first choice that comes to mind. The main goal of this case study is to identify why and how India is having trouble launching EVs. India faces significant obstacles in the areas of infrastructure, electricity, battery technology, and consumer behaviour. India already has the infrastructure necessary for the general usage of fuel-powered automobiles. Suddenly changing to another technology and expecting to complete the requirement is a little problematic in emerging nations like India. The majority of electric vehicles (EVs) use lithium-ion batteries, and India is in a position to buy these batteries from other nations. As a result, the battery is a little expensive in India. Nothing is difficult to overcome the barriers compared to the benefits of EVs. Finally, this study makes several recommendations for eliminating the barriers to India's EV adoption.
{"title":"Impact and challenges to Adopting Electric Vehicles in developing countries – a case study in India","authors":"P. Muthulakshmi, T. Tamilarasi, Tanmay Tapan Banerji, S. Albert, A. Raj, E. Aarthi","doi":"10.4108/ew.2665","DOIUrl":"https://doi.org/10.4108/ew.2665","url":null,"abstract":"Climate change is one of the current threats facing the world. Pollution is the primary factor causing climate change, in it, air pollution plays a major part. Almost all developed and developing countries emit a lot of greenhouse gases (GHG). The transportation sector is responsible for the majority of GHG emissions. Nowadays, almost all nations make an effort to lower CO2 emissions from transportation. India also has a strategy to achieve zero emissions through several programmes. When considering ways to lower GHG emissions from the transportation sector, electric vehicles (EVs) are the first choice that comes to mind. The main goal of this case study is to identify why and how India is having trouble launching EVs. India faces significant obstacles in the areas of infrastructure, electricity, battery technology, and consumer behaviour. India already has the infrastructure necessary for the general usage of fuel-powered automobiles. Suddenly changing to another technology and expecting to complete the requirement is a little problematic in emerging nations like India. The majority of electric vehicles (EVs) use lithium-ion batteries, and India is in a position to buy these batteries from other nations. As a result, the battery is a little expensive in India. Nothing is difficult to overcome the barriers compared to the benefits of EVs. Finally, this study makes several recommendations for eliminating the barriers to India's EV adoption.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44346485","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}
This study performed a gap analysis of data for urban transport planning in two countries, one developing, and one developed with a view to conducting a gap analysis in the two countries and then comparing the results. The study commenced with an exploration of the background study of the research area by highlighting the importance of data collection and the types of data that are collected for urban transport planning. The specific types of data that are identified as collected were listed in order to enable the contextualisation of the work to be carried out in the subsequent sections of the study. Furthermore, the identified data collection methods in transport planning were identified and discussed, the key methods were highlighted, and the future directions identified in the background area were discussed. Thereafter, the activities directed towards the collection of data and the actual collection of data for public transport planning in the UK and KSA were discussed. The gap analysis showed that the UK has a robust framework for the collection of data for urban transport planning which the KSA does not, and in fact it was discovered that the most importance concern of the KSA government is how to reduce the number of private motor vehicles on its roads and increase the number of buses, and thereby reduce greenhouse gas emissions with a currently a serious cause for concern. The UK also needs to concentrate more on the collection of data for the management of Connected and Autonomous Vehicles (CAVs), and Mobility as a Service (MaaS), in preparation for the deployment of both forms of transport.
{"title":"Gap Analysis of data for urban transport planning in the developing countries: Comparative study of United Kingdom (UK) and the Kingdom of Saudi Arabia (KSA)","authors":"Raed Naif Alahamidi","doi":"10.4108/ew.3693","DOIUrl":"https://doi.org/10.4108/ew.3693","url":null,"abstract":"This study performed a gap analysis of data for urban transport planning in two countries, one developing, and one developed with a view to conducting a gap analysis in the two countries and then comparing the results. The study commenced with an exploration of the background study of the research area by highlighting the importance of data collection and the types of data that are collected for urban transport planning. The specific types of data that are identified as collected were listed in order to enable the contextualisation of the work to be carried out in the subsequent sections of the study. Furthermore, the identified data collection methods in transport planning were identified and discussed, the key methods were highlighted, and the future directions identified in the background area were discussed. Thereafter, the activities directed towards the collection of data and the actual collection of data for public transport planning in the UK and KSA were discussed. The gap analysis showed that the UK has a robust framework for the collection of data for urban transport planning which the KSA does not, and in fact it was discovered that the most importance concern of the KSA government is how to reduce the number of private motor vehicles on its roads and increase the number of buses, and thereby reduce greenhouse gas emissions with a currently a serious cause for concern. The UK also needs to concentrate more on the collection of data for the management of Connected and Autonomous Vehicles (CAVs), and Mobility as a Service (MaaS), in preparation for the deployment of both forms of transport.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70857863","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}
This research at supplying electricity to Ziway lake islanders in Ethiopia, through studying the wind, pumped hydro-storage (PHS), and solar energy potentials. A wind mast is erected, and measurements at 10,50, and 70m heights are taken for a year long. The wind is of class-4 with wind speeds of 7m/s at 50m, and 7.87m/s. The energy density is 318.8 kWh/m2 (50m). GIS-based 3D digital elevation model (DEM) is used to investigate the PHS, with the lake as lower-reservoir and a dried-out crater pond of an extinct volcano as upper reservoir. The head is extracted using optical remote sensing technology, DEM(LiDAR) 12.5m. Constraints considered are topography, area, head, and slope. Twelve upper reservoirs are identified within head range of 50-250,50-200, and 50-100m. The results showed a PHS capacity of 5976 KWh at head of 60m can be developed. The solar energy potential is 6.1KWh/m2 /day. The finding proved the viability of electricity supply to the community.
{"title":"Investigation of Sustainable Technology Options: Wind, Pumped-hydro-storage and Solar potential to Electrify Isolated Ziway Islanders in Ethiopia","authors":"Mintesnot Gizaw, Getachew Bekele","doi":"10.4108/ew.88","DOIUrl":"https://doi.org/10.4108/ew.88","url":null,"abstract":"This research at supplying electricity to Ziway lake islanders in Ethiopia, through studying the wind, pumped hydro-storage (PHS), and solar energy potentials. A wind mast is erected, and measurements at 10,50, and 70m heights are taken for a year long. The wind is of class-4 with wind speeds of 7m/s at 50m, and 7.87m/s. The energy density is 318.8 kWh/m2 (50m). GIS-based 3D digital elevation model (DEM) is used to investigate the PHS, with the lake as lower-reservoir and a dried-out crater pond of an extinct volcano as upper reservoir. The head is extracted using optical remote sensing technology, DEM(LiDAR) 12.5m. Constraints considered are topography, area, head, and slope. Twelve upper reservoirs are identified within head range of 50-250,50-200, and 50-100m. The results showed a PHS capacity of 5976 KWh at head of 60m can be developed. The solar energy potential is 6.1KWh/m2 /day. The finding proved the viability of electricity supply to the community. ","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47635423","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}
A. Tadjeddine, Mohammed Sofiane Bendelhoum, R. I. Bendjillali, H. Hamiani, S. Djelaila
The Fluctuations in demand and weather conditions have a significant impact on the frequency and the voltage of Algeria's isolated PIAT power grid. To maintain stability and reliable power supply, it is crucial to keep these quantities close to their expected levels. An automatic (FRR) is employed to regulate real-time frequency deviations caused by integrating variable renewable energy (VRE), specifically wind and solar power in the Kabertene region. In order to mitigate wind power fluctuations, a power system stabilizer is implemented, which helps dampen oscillations. The use of Maximum Power Point Tracking (MPPT) techniques optimizes the extraction of power from solar panels under varying conditions. For efficient scheduling and dispatch of VRE generation, particle swarm optimization (PSO)-based algorithms are used. These algorithms ensure optimal utilization of renewable energy sources by considering their intermittent nature. This study proves the effectiveness of these techniques in enhancing grid stability, reducing frequency deviations, and improving VRE integration. Valuable insights are provided on their practical implementation, playing a crucial role in transitioning to a cleaner and more sustainable energy system.
{"title":"VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene","authors":"A. Tadjeddine, Mohammed Sofiane Bendelhoum, R. I. Bendjillali, H. Hamiani, S. Djelaila","doi":"10.4108/ew.3378","DOIUrl":"https://doi.org/10.4108/ew.3378","url":null,"abstract":"The Fluctuations in demand and weather conditions have a significant impact on the frequency and the voltage of Algeria's isolated PIAT power grid. To maintain stability and reliable power supply, it is crucial to keep these quantities close to their expected levels. An automatic (FRR) is employed to regulate real-time frequency deviations caused by integrating variable renewable energy (VRE), specifically wind and solar power in the Kabertene region. In order to mitigate wind power fluctuations, a power system stabilizer is implemented, which helps dampen oscillations. The use of Maximum Power Point Tracking (MPPT) techniques optimizes the extraction of power from solar panels under varying conditions. For efficient scheduling and dispatch of VRE generation, particle swarm optimization (PSO)-based algorithms are used. These algorithms ensure optimal utilization of renewable energy sources by considering their intermittent nature. This study proves the effectiveness of these techniques in enhancing grid stability, reducing frequency deviations, and improving VRE integration. Valuable insights are provided on their practical implementation, playing a crucial role in transitioning to a cleaner and more sustainable energy system.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46741118","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}
INTRODUCTION: With the deepening of the application of big data technology, the power sector attaches great importance to power outage judgment. However, many factors affect the judgment result of power outage, and the analysis process is very complicated, which can not achieve the corresponding accuracy.
OBJECTIVES: Aiming at the problem that it is impossible to accurately judge the result in judging power failure, a deep mining model of big data is proposed.
METHODS: Firstly, the research data set is established using power outage big data technology to ensure the results meet the requirements. Then, the power failure judgment data are classified using big data theory, and different judgment methods are selected. Using big data theory, the accuracy of power failure judgment is verified.
RESULTS: The deep mining model of big data can improve the accuracy of power failure judgment and shorten the judgment time of power failure under big data, and the overall result is better than the statistical method of power failure.
CONCLUSION: The deep mining model based on power outage big data proposed can accurately judge the power outage fault and shorten the analysis time.
{"title":"Power Outage Fault Judgment Method Based on Power Outage Big Data","authors":"Xinyang Zhang","doi":"10.4108/ew.3906","DOIUrl":"https://doi.org/10.4108/ew.3906","url":null,"abstract":"INTRODUCTION: With the deepening of the application of big data technology, the power sector attaches great importance to power outage judgment. However, many factors affect the judgment result of power outage, and the analysis process is very complicated, which can not achieve the corresponding accuracy.
 OBJECTIVES: Aiming at the problem that it is impossible to accurately judge the result in judging power failure, a deep mining model of big data is proposed.
 METHODS: Firstly, the research data set is established using power outage big data technology to ensure the results meet the requirements. Then, the power failure judgment data are classified using big data theory, and different judgment methods are selected. Using big data theory, the accuracy of power failure judgment is verified.
 RESULTS: The deep mining model of big data can improve the accuracy of power failure judgment and shorten the judgment time of power failure under big data, and the overall result is better than the statistical method of power failure.
 CONCLUSION: The deep mining model based on power outage big data proposed can accurately judge the power outage fault and shorten the analysis time.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135755947","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}
Miguel Bernabé-Custodio, W. Marín-Rodriguez, Daniel Andrade Girón, A. Neri-Ayala, J. Ausejo-Sánchez, A. Muñoz-Vilela, Santiago Ramos-y Yovera, Angel Campos-Diaz, Ernesto Díaz-Ronceros
This research presents the methodology and results of implementing energy efficiency management in the brick industry, given the problem of high electricity consumption in the production processes. Based on the ISO 50001 standard, energy efficiency management has as its structure the PHVA methodology of the Deming cycle and indicators that meet the standard's requirements. Energy consumption in tons of bricks produced is established as an indicator, allowing proposals for improving performance and efficient energy use, as well as implementing a management system, minimizing energy waste, and implementing engineering tools in the processes. Energy consumption data were collected before and after implementation, these data were analyzed, and the decrease in monthly electricity consumption was verified through a pre-test conducted at the beginning of the research, recording parameters of 543,800 kWh. After implementation, a post-test was conducted, recording parameters of 500,296 kWh, resulting in a saving of 43,504 kWh; in monetary units, the saving is S/18,067.21 for each month of production. Obtaining an annual decrease of 522,048 kWh, represented in monetary units S/216,806.53 (US$ 59,891.30 exchange rate S/3.62). Therefore, it is proven that implementing the methodology is feasible through the management of energy efficiency based on ISO 50001 and contributes strategically to the brick industry by increasing the efficiency associated with the reduction of 8% monthly electricity consumption.
{"title":"Energy efficiency management according to ISO 50001: A case study in the brick industry","authors":"Miguel Bernabé-Custodio, W. Marín-Rodriguez, Daniel Andrade Girón, A. Neri-Ayala, J. Ausejo-Sánchez, A. Muñoz-Vilela, Santiago Ramos-y Yovera, Angel Campos-Diaz, Ernesto Díaz-Ronceros","doi":"10.4108/ew.3560","DOIUrl":"https://doi.org/10.4108/ew.3560","url":null,"abstract":"This research presents the methodology and results of implementing energy efficiency management in the brick industry, given the problem of high electricity consumption in the production processes. Based on the ISO 50001 standard, energy efficiency management has as its structure the PHVA methodology of the Deming cycle and indicators that meet the standard's requirements. Energy consumption in tons of bricks produced is established as an indicator, allowing proposals for improving performance and efficient energy use, as well as implementing a management system, minimizing energy waste, and implementing engineering tools in the processes. Energy consumption data were collected before and after implementation, these data were analyzed, and the decrease in monthly electricity consumption was verified through a pre-test conducted at the beginning of the research, recording parameters of 543,800 kWh. After implementation, a post-test was conducted, recording parameters of 500,296 kWh, resulting in a saving of 43,504 kWh; in monetary units, the saving is S/18,067.21 for each month of production. Obtaining an annual decrease of 522,048 kWh, represented in monetary units S/216,806.53 (US$ 59,891.30 exchange rate S/3.62). Therefore, it is proven that implementing the methodology is feasible through the management of energy efficiency based on ISO 50001 and contributes strategically to the brick industry by increasing the efficiency associated with the reduction of 8% monthly electricity consumption.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70857929","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}
INTRODUCTION: Artificial intelligence is a product of high-end technological development since the 21st century, which has subverted people's traditional cognition in many aspects and greatly enriched and improved people's lives. Artificial intelligence has covered every aspect of life, and the distribution network overhead line project is also one of them. The combination of the two symbolizes the combination of modern technology and infrastructure construction, which is of great significance for modern economic and social development and transformation and upgrading. OBJECTIVES: In order to solve the practical problems in the design of artificial intelligence and distribution network overhead line engineering, this paper focuses on the practical use of such artificial intelligence as robots in distribution network overhead line engineering. METHODS: The models of spatial perception, target recognition and automatic calculation are established, and some key technical problems of robots put into actual engineering are simulated and calculated. RESULTS: In the spatial perception model, the combination of robotic arm and laser device is utilized to solve the problem of direct sunlight, which affects the localization. In the target recognition model, combining the algorithms of minimum spanning tree and maximum critical path, the computational accuracy is improved to 1 mm. in the automatic computation model, the introduction of auxiliary lines and the secondary confirmation of manpower make the error of the work further reduced. CONCLUSION: This paper's simulation algorithm for the reality of the distribution network overhead line project provides a more detailed solution to improve the technical content of the distribution network overhead line project and the quality of construction management is not a simple task, the need for the relevant distribution network overhead line project enterprises as well as the corresponding distribution network overhead line project personnel to take targeted measures.
{"title":"Optimization and application of artificial intelligence in robotic automated distribution network overhead line engineering","authors":"Xue Li, Meng Li, Yi Tan, Yunhui Wang","doi":"10.4108/ew.3718","DOIUrl":"https://doi.org/10.4108/ew.3718","url":null,"abstract":"INTRODUCTION: Artificial intelligence is a product of high-end technological development since the 21st century, which has subverted people's traditional cognition in many aspects and greatly enriched and improved people's lives. Artificial intelligence has covered every aspect of life, and the distribution network overhead line project is also one of them. The combination of the two symbolizes the combination of modern technology and infrastructure construction, which is of great significance for modern economic and social development and transformation and upgrading. \u0000OBJECTIVES: In order to solve the practical problems in the design of artificial intelligence and distribution network overhead line engineering, this paper focuses on the practical use of such artificial intelligence as robots in distribution network overhead line engineering. \u0000METHODS: The models of spatial perception, target recognition and automatic calculation are established, and some key technical problems of robots put into actual engineering are simulated and calculated. \u0000RESULTS: In the spatial perception model, the combination of robotic arm and laser device is utilized to solve the problem of direct sunlight, which affects the localization. In the target recognition model, combining the algorithms of minimum spanning tree and maximum critical path, the computational accuracy is improved to 1 mm. in the automatic computation model, the introduction of auxiliary lines and the secondary confirmation of manpower make the error of the work further reduced. \u0000CONCLUSION: This paper's simulation algorithm for the reality of the distribution network overhead line project provides a more detailed solution to improve the technical content of the distribution network overhead line project and the quality of construction management is not a simple task, the need for the relevant distribution network overhead line project enterprises as well as the corresponding distribution network overhead line project personnel to take targeted measures.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70858109","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}
INTRODUCTION: Hybrid stand-alone Small Wind Solar Energy System offers a feasible solution in remote areas where grid connectivity is either financially or physically unavailable. A small wind turbine (SWT) and a solar photovoltaic system are part of the hybrid energy system, which is effectively employed to meet the energy needs of rural household loads. OBJECTIVE: This research suggests an effective analysis of wind solar hybrid system controllers taking energy demands into account. The controller should be designed in such a way as to intelligently monitor the availability of wind energy and solar energy and store the energy without spilling it out. METHODS: In order to cope with the challenging factors involved in designing the controller, intelligent power tracking with an artificially intelligent neural network (AI-NN) is designed. Added to that, the whole process has been designed and analysed with the MATLAB SIMULINK tool. RESUSTS: The results of the simulation, infer that AI-NN achieved the regression value of 0.99 when compared with the Perturb & Observe algorithm (P&O), and the Fuzzy Logic Control (FLC) algorithm, and has a higher tracking speed. Also, the AI-NN attained 2.62kW whereas the P&O has attained 2.52kW and Fuzzy logic has attained 2.43W of power which is 3.89% higher than P&O algorithm and 7.52% higher than fuzzy MPPT algorithm. CONCLUSION: The designed controller module enhances the system by artificially intelligent algorithm. The AI-NN attains the better power performance with lesser tracking time and higher efficiency. Thus, it is evident that AI-NN MPPT suits well for the hybrid system.
{"title":"Stand-alone Micro Grid based on Artificially Intelligent Neural Network (AI-NN)","authors":"Jenitha R., K. Rajesh","doi":"10.4108/ew.v9i6.147","DOIUrl":"https://doi.org/10.4108/ew.v9i6.147","url":null,"abstract":"INTRODUCTION: Hybrid stand-alone Small Wind Solar Energy System offers a feasible solution in remote areas where grid connectivity is either financially or physically unavailable. A small wind turbine (SWT) and a solar photovoltaic system are part of the hybrid energy system, which is effectively employed to meet the energy needs of rural household loads.\u0000OBJECTIVE: This research suggests an effective analysis of wind solar hybrid system controllers taking energy demands into account. The controller should be designed in such a way as to intelligently monitor the availability of wind energy and solar energy and store the energy without spilling it out.\u0000METHODS: In order to cope with the challenging factors involved in designing the controller, intelligent power tracking with an artificially intelligent neural network (AI-NN) is designed. Added to that, the whole process has been designed and analysed with the MATLAB SIMULINK tool.\u0000RESUSTS: The results of the simulation, infer that AI-NN achieved the regression value of 0.99 when compared with the Perturb & Observe algorithm (P&O), and the Fuzzy Logic Control (FLC) algorithm, and has a higher tracking speed. Also, the AI-NN attained 2.62kW whereas the P&O has attained 2.52kW and Fuzzy logic has attained 2.43W of power which is 3.89% higher than P&O algorithm and 7.52% higher than fuzzy MPPT algorithm.\u0000CONCLUSION: The designed controller module enhances the system by artificially intelligent algorithm. The AI-NN attains the better power performance with lesser tracking time and higher efficiency. Thus, it is evident that AI-NN MPPT suits well for the hybrid system.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70858424","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}
INTRODUCTION: The development of artificial intelligence technology in the context of the intelligent era shows vigorous vigor and vitality, and artificial intelligence fusion of robotic automation technology can assist manpower to complete all kinds of difficult operations, distribution network overhead line as the current power transmission lines equipped with the main way for domestic power transmission and regional power safety is of great significance. OBJECTIVES: In order to reduce the labor intensity of operators, reduce the occurrence of power outages, and ensure the reliability of power supply, we discuss the application of robotic automation technology of machine-assisted and artificial intelligence in the distribution network overhead line project. METHODS: Distribution network with power operation intelligent robot will grid lines in the wave speed information through the sensor transmission to the computer system, the computer system will grid lines in the wave speed converted to the wave speed of the overhead line, can be mixed lines in the wave speed inconsistent problem to provide a good solution. RESULTS: At the scene of the work, the artificial intelligence distribution network power-carrying operation robot integrating artificial intelligence technology has a good application effect for the wiring in the distribution network overhead line project. CONCLUSION: Robot automation technology incorporates the advantages of artificial intelligence, can rely on sensor systems and computer systems to perceive and identify things, and can autonomously control their own behavior, automated processing of complex actions, with a certain degree of perception, planning and collaborative ability, can be applied to the distribution network overhead line project.
{"title":"Application of robot automation technology based on machine assisted and artificial intelligence in distribution network overhead line engineering","authors":"Yi Tan, Yunhui Wang, Xue Li, Meng Li","doi":"10.4108/ew.3717","DOIUrl":"https://doi.org/10.4108/ew.3717","url":null,"abstract":"INTRODUCTION: The development of artificial intelligence technology in the context of the intelligent era shows vigorous vigor and vitality, and artificial intelligence fusion of robotic automation technology can assist manpower to complete all kinds of difficult operations, distribution network overhead line as the current power transmission lines equipped with the main way for domestic power transmission and regional power safety is of great significance. \u0000OBJECTIVES: In order to reduce the labor intensity of operators, reduce the occurrence of power outages, and ensure the reliability of power supply, we discuss the application of robotic automation technology of machine-assisted and artificial intelligence in the distribution network overhead line project. \u0000METHODS: Distribution network with power operation intelligent robot will grid lines in the wave speed information through the sensor transmission to the computer system, the computer system will grid lines in the wave speed converted to the wave speed of the overhead line, can be mixed lines in the wave speed inconsistent problem to provide a good solution. \u0000RESULTS: At the scene of the work, the artificial intelligence distribution network power-carrying operation robot integrating artificial intelligence technology has a good application effect for the wiring in the distribution network overhead line project. \u0000CONCLUSION: Robot automation technology incorporates the advantages of artificial intelligence, can rely on sensor systems and computer systems to perceive and identify things, and can autonomously control their own behavior, automated processing of complex actions, with a certain degree of perception, planning and collaborative ability, can be applied to the distribution network overhead line project. \u0000 ","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70857903","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}
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