This paper reviews the current state of research in data analytics and machine learning techniques, focusing on their applications in process industrial manufacturing, particularly in control and optimization. Key areas for future research include selection and transfer learning for process monitoring, addressing time-varying characteristics, and enhancing data-driven optimal control with domain-specific knowledge. Additionally, the paper explores reinforcement learning techniques and robust optimization, including distributional robust optimization, for high-level decision-making. Emphasizing the importance of historical knowledge of plants and processes, this paper aims to identify knowledge gaps and pave the way for future research in data-driven strategies for process industries, with a particular emphasis on energy efficiency and optimization.
{"title":"Enhancing Efficiency and Energy Optimization: Data-Driven Solutions in Process Industrial Manufacturing","authors":"Hui Liu, Guihao Zhang","doi":"10.4108/ew.6098","DOIUrl":"https://doi.org/10.4108/ew.6098","url":null,"abstract":"This paper reviews the current state of research in data analytics and machine learning techniques, focusing on their applications in process industrial manufacturing, particularly in control and optimization. Key areas for future research include selection and transfer learning for process monitoring, addressing time-varying characteristics, and enhancing data-driven optimal control with domain-specific knowledge. Additionally, the paper explores reinforcement learning techniques and robust optimization, including distributional robust optimization, for high-level decision-making. Emphasizing the importance of historical knowledge of plants and processes, this paper aims to identify knowledge gaps and pave the way for future research in data-driven strategies for process industries, with a particular emphasis on energy efficiency and optimization.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"3 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141268014","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 introduces an innovative seabed substrate detection model that harnesses the complementary strengths of Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) to analyze sonar data with a focus on energy efficiency. The model addresses the challenges of underwater sensing and imaging, including variable lighting conditions, backscattering effects, and acoustic sensor limitations, while minimizing energy consumption. By leveraging advanced machine learning techniques, the proposed model aims to enhance seabed classification accuracy, a crucial aspect for marine operations, ecological studies, and energy-intensive underwater applications.The introduced ShuffleNet-DSE architecture demonstrates significant improvements in both accuracy and stability for seabed sediment image classification, while maintaining energy-efficient performance. This robust tool offers a valuable asset for underwater exploration, research, and monitoring efforts, especially in environments where energy resources are limited.
{"title":"Energy-Efficient Design of Seabed Substrate Detection Model Leveraging CNN-SVM Architecture and Sonar Data","authors":"Keming Wang, Chengli Wang, Wenbing Jin, Liuming Qi","doi":"10.4108/ew.6097","DOIUrl":"https://doi.org/10.4108/ew.6097","url":null,"abstract":"This study introduces an innovative seabed substrate detection model that harnesses the complementary strengths of Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) to analyze sonar data with a focus on energy efficiency. The model addresses the challenges of underwater sensing and imaging, including variable lighting conditions, backscattering effects, and acoustic sensor limitations, while minimizing energy consumption. By leveraging advanced machine learning techniques, the proposed model aims to enhance seabed classification accuracy, a crucial aspect for marine operations, ecological studies, and energy-intensive underwater applications.The introduced ShuffleNet-DSE architecture demonstrates significant improvements in both accuracy and stability for seabed sediment image classification, while maintaining energy-efficient performance. This robust tool offers a valuable asset for underwater exploration, research, and monitoring efforts, especially in environments where energy resources are limited.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"7 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141265767","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}
Research in relation to land technology should be conducted guided by concerns for environmental sustainability. There must be a robust framework that regulates land use and development, taking into account changes in the environment due to biological, human-made substances and other factors. The research has shown how important it is to have all stakeholders involved in regulation process through Integrated Stakeholder Engagement Approach (ISEA) which is unique. Proposed ISEA approach can bring together different stakeholders including government agencies, corporate experts, environmental advocates as well as community groups to come up with appropriate regulatory frameworks. One model of reducing the impacts of a building is to build it on a strong foundation. It is necessary today for such studies to include simulation assessment so as to evaluate the effectiveness of the regulatory system. This review examines possible outcomes and environmental implications associated with specific regulations based on certain zoning policies are useful for decision-making and policy choices. By minimizing pollution while using simulation analysis techniques among different stakeholders, this initiative wants to facilitate resilient sustainable land improvement.
{"title":"Legal Framework of Land Engineering: Compliance with Environmental Regulations to Reduce Pollution","authors":"Xuewen Du","doi":"10.4108/ew.5762","DOIUrl":"https://doi.org/10.4108/ew.5762","url":null,"abstract":" Research in relation to land technology should be conducted guided by concerns for environmental sustainability. There must be a robust framework that regulates land use and development, taking into account changes in the environment due to biological, human-made substances and other factors. The research has shown how important it is to have all stakeholders involved in regulation process through Integrated Stakeholder Engagement Approach (ISEA) which is unique. Proposed ISEA approach can bring together different stakeholders including government agencies, corporate experts, environmental advocates as well as community groups to come up with appropriate regulatory frameworks. One model of reducing the impacts of a building is to build it on a strong foundation. It is necessary today for such studies to include simulation assessment so as to evaluate the effectiveness of the regulatory system. This review examines possible outcomes and environmental implications associated with specific regulations based on certain zoning policies are useful for decision-making and policy choices. By minimizing pollution while using simulation analysis techniques among different stakeholders, this initiative wants to facilitate resilient sustainable land improvement.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"16 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140661492","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: In an in-depth study of the application of sustainable energy in cross-border e-commerce, a comprehensive assessment and model optimization of its life cycle are conducted to promote the practical application of sustainable development in e-commerce. With the increasing global concern for renewable energy and environmental protection, e-commerce, as an international business model, has attracted much attention in terms of the environmental and social impacts of its sustainability.OBJECTIVES: The aim is to provide scientific assessment methods and effective model optimization strategies to promote the feasibility and sustainability of cross-border e-commerce for sustainable energy.METHODS: A comprehensive life cycle assessment (LCA) model was constructed using the system life cycle assessment (SLCA) methodology by collecting data from various aspects of sustainable energy cross-border e-commerce. The model considers the entire life cycle process from energy production, logistics, transportation, and product manufacturing to final consumption and integrates various factors such as resource utilization, environmental emissions, and social responsibility. Based on the assessment, a series of model optimization strategies are proposed, including suggestions for improving supply chain efficiency, promoting green energy applications, and strengthening social responsibility.RESULTS: This study achieved significant life cycle assessment and model optimization results. In terms of energy use, promoting the application of renewable energy significantly reduces carbon emissions; in terms of supply chain management, optimization leads to an overall efficiency improvement and a reduction in resource wastage; and in terms of social responsibility, the enterprise strengthens employee training and community involvement, which enhances its social image. These results show that sustainable energy cross-border e-commerce can better achieve sustainable development goals through systematic assessment and optimization.CONCLUSION: Life cycle assessment and model optimization provide scientific assessment methods and practical suggestions for sustainable energy cross-border e-commerce. In global sustainable development, the e-commerce industry should actively adopt sustainable energy and minimize its negative impacts on the environment and society by optimizing production and supply chain management. Future research can continue to expand the assessment model and deeply explore the potential of sustainable energy in e-commerce to provide more precise guidance for the industry's sustainable development.
{"title":"Life Cycle Assessment and Model Optimization for Sustainable Energy Cross-Border E-Commerce","authors":"Hongli Liu, Ruiling Cui","doi":"10.4108/ew.5493","DOIUrl":"https://doi.org/10.4108/ew.5493","url":null,"abstract":"INTRODUCTION: In an in-depth study of the application of sustainable energy in cross-border e-commerce, a comprehensive assessment and model optimization of its life cycle are conducted to promote the practical application of sustainable development in e-commerce. With the increasing global concern for renewable energy and environmental protection, e-commerce, as an international business model, has attracted much attention in terms of the environmental and social impacts of its sustainability.OBJECTIVES: The aim is to provide scientific assessment methods and effective model optimization strategies to promote the feasibility and sustainability of cross-border e-commerce for sustainable energy.METHODS: A comprehensive life cycle assessment (LCA) model was constructed using the system life cycle assessment (SLCA) methodology by collecting data from various aspects of sustainable energy cross-border e-commerce. The model considers the entire life cycle process from energy production, logistics, transportation, and product manufacturing to final consumption and integrates various factors such as resource utilization, environmental emissions, and social responsibility. Based on the assessment, a series of model optimization strategies are proposed, including suggestions for improving supply chain efficiency, promoting green energy applications, and strengthening social responsibility.RESULTS: This study achieved significant life cycle assessment and model optimization results. In terms of energy use, promoting the application of renewable energy significantly reduces carbon emissions; in terms of supply chain management, optimization leads to an overall efficiency improvement and a reduction in resource wastage; and in terms of social responsibility, the enterprise strengthens employee training and community involvement, which enhances its social image. These results show that sustainable energy cross-border e-commerce can better achieve sustainable development goals through systematic assessment and optimization.CONCLUSION: Life cycle assessment and model optimization provide scientific assessment methods and practical suggestions for sustainable energy cross-border e-commerce. In global sustainable development, the e-commerce industry should actively adopt sustainable energy and minimize its negative impacts on the environment and society by optimizing production and supply chain management. Future research can continue to expand the assessment model and deeply explore the potential of sustainable energy in e-commerce to provide more precise guidance for the industry's sustainable development.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"22 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140671526","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: It is of great research significance to explore whether China can achieve the "two-carbon target" on time. The MLP model combines nonlinear modeling principles with other techniques, possessing powerful adaptive learning capabilities, and providing a viable solution for carbon emission prediction. OBJECTIVES: This study models and forecasts carbon emissions in Jiangsu Province, one of China's largest industrial provinces, aiming to forecast whether Jiangsu province will achieve the two-carbon target on time plan and provide feasible pathways and theoretical foundations for achieving dual carbon goals. METHODS: Based on the analysis of the contributions of relevant indicators using the Grey Relational Analysis method, a comprehensive approach integrating the STIRPAT model, Logistic model, and ARIMA model is adopted. Ultimately, an MLP prediction model for carbon emission variations is established. Using this model, simulations are conducted to analyze the carbon emission levels in Jiangsu Province under different scenarios from 2021 to 2060. RESULTS: The time to reach carbon peak and the likelihood of achieving carbon neutrality vary under three scenarios. Under the natural scenario of no human intervention, achieving carbon neutrality is not feasible. While under human-made intervention scenarios including baseline and intervention scenarios, Jiangsu Province is projected to achieve the carbon neutrality target as scheduled, attaining the peak carbon goal, however, proves challenging to realize by the year 2030. CONCLUSION: The MLP model exhibits high accuracy in predicting carbon emissions. To expedite the realization of dual carbon goals, proactive government intervention is necessary.
{"title":"Carbon Emission Forecast Based on Multilayer Perceptron Network and STIRPAT Model","authors":"Ning Zhao, Chengyu Li","doi":"10.4108/ew.5808","DOIUrl":"https://doi.org/10.4108/ew.5808","url":null,"abstract":"INTRODUCTION: It is of great research significance to explore whether China can achieve the \"two-carbon target\" on time. The MLP model combines nonlinear modeling principles with other techniques, possessing powerful adaptive learning capabilities, and providing a viable solution for carbon emission prediction. \u0000OBJECTIVES: This study models and forecasts carbon emissions in Jiangsu Province, one of China's largest industrial provinces, aiming to forecast whether Jiangsu province will achieve the two-carbon target on time plan and provide feasible pathways and theoretical foundations for achieving dual carbon goals. \u0000METHODS: Based on the analysis of the contributions of relevant indicators using the Grey Relational Analysis method, a comprehensive approach integrating the STIRPAT model, Logistic model, and ARIMA model is adopted. Ultimately, an MLP prediction model for carbon emission variations is established. Using this model, simulations are conducted to analyze the carbon emission levels in Jiangsu Province under different scenarios from 2021 to 2060. \u0000RESULTS: The time to reach carbon peak and the likelihood of achieving carbon neutrality vary under three scenarios. Under the natural scenario of no human intervention, achieving carbon neutrality is not feasible. While under human-made intervention scenarios including baseline and intervention scenarios, Jiangsu Province is projected to achieve the carbon neutrality target as scheduled, attaining the peak carbon goal, however, proves challenging to realize by the year 2030. \u0000CONCLUSION: The MLP model exhibits high accuracy in predicting carbon emissions. To expedite the realization of dual carbon goals, proactive government intervention is necessary.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"18 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140696565","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 integrated energy systems (IES) is of paramount significance in addressing climate change and other challenges. Ensuring the rapid and accurate calculation of energy flow states is crucial for their efficient operation. However, the difference in response time of various heterogeneous energy flows in IES will lead to the inaccuracy of the steady-state model. OBJECTIVES: This paper proposes a model for multi-stage multi-energy flow IES of electricity, gas, and heat based on heterogeneous energy flow characteristics. Methods: IES was divided into fast variable networks and slow variable networks, and a multi-energy flow multi-stage model was established. Suitable models were matched for different subnets at different stages to improve the calculation accuracy. RESULTS: Selected a practical Electrical-Gas-Heat IES as a case study for simulation. Through case studies, the effectiveness and accuracy of the proposed method are demonstrated. CONCLUSION: The multi-stage model proposed in this paper can improve the accuracy of multi-energy flow in IES.
{"title":"Multi-stage Multi-energy Flow Integrated Energy Systems of Electricity, Gas, and Heat Based on Heterogeneous Energy Flow Characteristics","authors":"Qinglong Gou, Yansong Wang, Qingzeng Yan","doi":"10.4108/ew.5799","DOIUrl":"https://doi.org/10.4108/ew.5799","url":null,"abstract":"INTRODUCTION: The development of integrated energy systems (IES) is of paramount significance in addressing climate change and other challenges. Ensuring the rapid and accurate calculation of energy flow states is crucial for their efficient operation. However, the difference in response time of various heterogeneous energy flows in IES will lead to the inaccuracy of the steady-state model. \u0000OBJECTIVES: This paper proposes a model for multi-stage multi-energy flow IES of electricity, gas, and heat based on heterogeneous energy flow characteristics. \u0000Methods: IES was divided into fast variable networks and slow variable networks, and a multi-energy flow multi-stage model was established. Suitable models were matched for different subnets at different stages to improve the calculation accuracy. \u0000RESULTS: Selected a practical Electrical-Gas-Heat IES as a case study for simulation. Through case studies, the effectiveness and accuracy of the proposed method are demonstrated. \u0000CONCLUSION: The multi-stage model proposed in this paper can improve the accuracy of multi-energy flow in IES.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"8 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140696184","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 advent of the "bidding era" and "parity era" in the wind power market, the competition of the whole machine factory is becoming more and more fierce, and the capacity of the single fan is getting larger and larger, which becomes the key to the design of the fan electrical system of the large-capacity unit (5.XMW or more). At present, the low-voltage wind power system (690V,1140V) is the common solution for wind turbines. However, due to the limitation of the cable section of low-voltage electrical system and the increase of the rated current of the generator, the increase of the capacity of a single machine makes more cables from the generator side to the grid, and the cost also increases. OBJECTIVES: Aiming at the future large megawatt wind power market, the medium voltage Doubly-Fed electrical system solution is proposed to increase the higher generation and electricity income of wind farms and reduce the manufacturing cost of wind farms. METHODS: The technology and economy of medium voltage and low voltage electrical system are compared. RESULTS: With the gradual increase of single capacity, the economy of medium pressure wind power generation system is getting better and better, and the higher the height of the tower, the better the economy. At the same time, the reduction of the rated current of the generator brings about the reduction of line loss and the increase of power generation. The number of cables is greatly reduced, and the construction cost and difficulty of cable laying will be greatly reduced. CONCLUSION: In response to the technical trend of large-capacity wind turbines in the future, the medium-voltage wind power generation system has a good application prospect, both from the economic and technical point of view.
{"title":"Research on the Technical and Economic Development of Large Megawatt Wind Turbines Based on Medium-Voltage Electrical System","authors":"Wei Liu, Rui Wang, Chen Chen","doi":"10.4108/ew.5801","DOIUrl":"https://doi.org/10.4108/ew.5801","url":null,"abstract":"INTRODUCTION: With the advent of the \"bidding era\" and \"parity era\" in the wind power market, the competition of the whole machine factory is becoming more and more fierce, and the capacity of the single fan is getting larger and larger, which becomes the key to the design of the fan electrical system of the large-capacity unit (5.XMW or more). At present, the low-voltage wind power system (690V,1140V) is the common solution for wind turbines. However, due to the limitation of the cable section of low-voltage electrical system and the increase of the rated current of the generator, the increase of the capacity of a single machine makes more cables from the generator side to the grid, and the cost also increases. \u0000OBJECTIVES: Aiming at the future large megawatt wind power market, the medium voltage Doubly-Fed electrical system solution is proposed to increase the higher generation and electricity income of wind farms and reduce the manufacturing cost of wind farms. \u0000METHODS: The technology and economy of medium voltage and low voltage electrical system are compared. \u0000RESULTS: With the gradual increase of single capacity, the economy of medium pressure wind power generation system is getting better and better, and the higher the height of the tower, the better the economy. At the same time, the reduction of the rated current of the generator brings about the reduction of line loss and the increase of power generation. The number of cables is greatly reduced, and the construction cost and difficulty of cable laying will be greatly reduced. \u0000CONCLUSION: In response to the technical trend of large-capacity wind turbines in the future, the medium-voltage wind power generation system has a good application prospect, both from the economic and technical point of view.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"16 s23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140694989","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}
Yuan Hu, Qiuyan Gao, Peng Wu, Shuai Zhang, Yan Li, P. Zhao, Ming Gao, Song Qiao
The vigorous development of new energy has effectively reduced carbon emissions, but it has also brought fluctuating impacts on the carrying capacity of the power grid. In order to improve the voltage stability after integrating new energy sources and promote the scientific consumption of more new energy, this paper proposes the use of Distributed Static Synchronous Compensator (DSSC) devices for flexible and controllable voltage regulation in new energy integration. An improved particle swarm optimization algorithm is then developed to optimize the reactive power considering the regulation of DSSC. The paper conducts power flow calculations based on the DSSC power injection model and establishes a reactive power optimization mathematical model with objectives of minimizing active power loss, minimizing node voltage deviation, and maximizing voltage stability margin in the grid with new energy integration. The improved particle swarm optimization algorithm is utilized to achieve the reactive power optimization. Experimental simulations are conducted using the IEEE 33-node system to analyze the voltage improvement before and after adopting the improved particle swarm optimization algorithm considering the DSSC device in the grid with new energy integration. It is found that the proposed method effectively reduces active power loss and stabilizes voltage fluctuations, demonstrating its practical value.
{"title":"Study on Reactive Power Optimization Including DSSC for New Energy Access to the Power Grid","authors":"Yuan Hu, Qiuyan Gao, Peng Wu, Shuai Zhang, Yan Li, P. Zhao, Ming Gao, Song Qiao","doi":"10.4108/ew.5806","DOIUrl":"https://doi.org/10.4108/ew.5806","url":null,"abstract":"The vigorous development of new energy has effectively reduced carbon emissions, but it has also brought fluctuating impacts on the carrying capacity of the power grid. In order to improve the voltage stability after integrating new energy sources and promote the scientific consumption of more new energy, this paper proposes the use of Distributed Static Synchronous Compensator (DSSC) devices for flexible and controllable voltage regulation in new energy integration. An improved particle swarm optimization algorithm is then developed to optimize the reactive power considering the regulation of DSSC. The paper conducts power flow calculations based on the DSSC power injection model and establishes a reactive power optimization mathematical model with objectives of minimizing active power loss, minimizing node voltage deviation, and maximizing voltage stability margin in the grid with new energy integration. The improved particle swarm optimization algorithm is utilized to achieve the reactive power optimization. Experimental simulations are conducted using the IEEE 33-node system to analyze the voltage improvement before and after adopting the improved particle swarm optimization algorithm considering the DSSC device in the grid with new energy integration. It is found that the proposed method effectively reduces active power loss and stabilizes voltage fluctuations, demonstrating its practical value.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"24 32","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140696398","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}
In the sparsely populated areas without electricity, the hydro photovoltaic power station is a feasible solution for electricity supply. The strategy of distributing the power among the inverters is critical to the efficiency of them. The conventional distributing strategies result in low efficiency of the inverters. In order to improve the efficiency, this paper analysed the loss and efficiency characteristics of the inverter and expressed the power distributing problem as an optimal control problem minimizing the total loss for the inverters. The optimal control problem was solved with particle swarm optimization and the efficiency optimum power distribution strategies in three operation scenarios were obtained. The quantitative analysis method was adopted to evaluate the effect of the efficiency optimum power distribution strategies. The total efficiency of the inverters with the optimal strategies and the conventional strategies were calculated respectively. The optimal distribution strategies were compared quantitatively with conventional power distribution strategies on the basis of the efficiency. The results demonstrated the validity of the strategies obtained in this paper in improving the total efficiency of the inverters.
{"title":"Improvement of Efficiency of Inverters in Hydro Photovoltaic Power Station with Particle Swarm Optimization","authors":"Huijie Xue, Ning Xiao","doi":"10.4108/ew.5807","DOIUrl":"https://doi.org/10.4108/ew.5807","url":null,"abstract":"In the sparsely populated areas without electricity, the hydro photovoltaic power station is a feasible solution for electricity supply. The strategy of distributing the power among the inverters is critical to the efficiency of them. The conventional distributing strategies result in low efficiency of the inverters. In order to improve the efficiency, this paper analysed the loss and efficiency characteristics of the inverter and expressed the power distributing problem as an optimal control problem minimizing the total loss for the inverters. The optimal control problem was solved with particle swarm optimization and the efficiency optimum power distribution strategies in three operation scenarios were obtained. The quantitative analysis method was adopted to evaluate the effect of the efficiency optimum power distribution strategies. The total efficiency of the inverters with the optimal strategies and the conventional strategies were calculated respectively. The optimal distribution strategies were compared quantitatively with conventional power distribution strategies on the basis of the efficiency. The results demonstrated the validity of the strategies obtained in this paper in improving the total efficiency of the inverters.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"3 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140697847","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}
Hu Tan, Xiaoliang Wang, Tingting Xu, Ke Zhao, Lianchao Su, Wenyu Zhang, Zheng Xin
Under the guidance of the 'dual carbon' goals and 'rural revitalization' strategy, the development of microgrids primarily based on wind, solar, and biogas energy is rapidly advancing in rural areas. A critical and challenging area of current research is how to optimally configure the capacity of these microgrids of varying sizes, taking into account the availability of resources in the system's environment and specific climatic conditions, to maximize economic benefits. Based on this, the article constructs a model of a hybrid AC/DC microgrid system powered by wind, solar, and biogas energy. It undertakes multi-objective optimization to achieve the highest utilization of renewable energy, the most economical cost, and the minimum carbon emissions while ensuring the reliability of the system's power supply. The study explores the economically and technically optimal configuration of this microgrid energy system under certain climatic conditions. The results indicate that the optimal configuration for a rural microgrid powered by wind, solar, and biogas energy should include a 2.6 kW biogas generator, 30.00 kW solar panels, 5.24 kW wind turbines, a 2.6 kW battery storage system, and a 10.00 kW bidirectional inverter. This configuration results in the lowest total net cost of the system, achieving optimal outcomes in terms of total net cost, cost per kilowatt-hour, and supply reliability.
{"title":"Study on the Economic and Technical Optimization of Hybrid Rural Microgrids Integrating Wind, Solar, Biogas, and Energy Storage with AC/DC Conversion","authors":"Hu Tan, Xiaoliang Wang, Tingting Xu, Ke Zhao, Lianchao Su, Wenyu Zhang, Zheng Xin","doi":"10.4108/ew.5803","DOIUrl":"https://doi.org/10.4108/ew.5803","url":null,"abstract":"Under the guidance of the 'dual carbon' goals and 'rural revitalization' strategy, the development of microgrids primarily based on wind, solar, and biogas energy is rapidly advancing in rural areas. A critical and challenging area of current research is how to optimally configure the capacity of these microgrids of varying sizes, taking into account the availability of resources in the system's environment and specific climatic conditions, to maximize economic benefits. Based on this, the article constructs a model of a hybrid AC/DC microgrid system powered by wind, solar, and biogas energy. It undertakes multi-objective optimization to achieve the highest utilization of renewable energy, the most economical cost, and the minimum carbon emissions while ensuring the reliability of the system's power supply. The study explores the economically and technically optimal configuration of this microgrid energy system under certain climatic conditions. The results indicate that the optimal configuration for a rural microgrid powered by wind, solar, and biogas energy should include a 2.6 kW biogas generator, 30.00 kW solar panels, 5.24 kW wind turbines, a 2.6 kW battery storage system, and a 10.00 kW bidirectional inverter. This configuration results in the lowest total net cost of the system, achieving optimal outcomes in terms of total net cost, cost per kilowatt-hour, and supply reliability.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"8 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140696370","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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