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EAI Endorsed Transactions on Energy Web最新文献

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State-of-the-art review on energy management systems, challenges and top trends of renewable energy based microgrids 基于可再生能源的微电网的能源管理系统、挑战和主要趋势的最新回顾
Q3 Engineering Pub Date : 2024-01-08 DOI: 10.4108/ew.4124
Yefan Wu, JinZhu Cui, Caiyan Liu
Due to the increasing demand for electrical energy worldwide and environmental concerns, modern power systems are looking for a fundamental change. These changes include reducing dependence on the primary electricity grid and using renewable energy sources on a large scale. The emergence of microgrids in electrical energy systems will improve the level of these systems due to technical, economic, and environmental benefits. In this research work, the authors have conducted extensive studies on control methods, types of power sources, and the size of microgrids and analyzed them in tabular form. In addition, the review of communication technologies and standards in microgrids, as well as the review of microgrid energy management systems to optimize the efficiency of microgrids, is one of the main goals of the authors in this article. Also, in this article, the top 10 trends of microgrids in 2023 have been examined to increase the flexibility of network infrastructure, which helps readers to improve their strategic decisions by providing an overview of emerging technologies in the energy industry.
由于全球范围内对电能的需求日益增长以及对环境的担忧,现代电力系统正在寻求根本性的变革。这些变革包括减少对一次电网的依赖和大规模使用可再生能源。由于技术、经济和环境效益,微电网在电能系统中的出现将提高这些系统的水平。在这项研究工作中,作者对微电网的控制方法、电源类型和规模进行了广泛研究,并以表格形式进行了分析。此外,回顾微电网中的通信技术和标准,以及回顾微电网能源管理系统以优化微电网效率,也是作者在本文中的主要目标之一。此外,本文还研究了 2023 年微电网的十大发展趋势,以提高网络基础设施的灵活性,通过概述能源行业的新兴技术,帮助读者改进战略决策。
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引用次数: 0
Green Economic Policies, Strategies & Initiatives of India 印度的绿色经济政策、战略和倡议
Q3 Engineering Pub Date : 2023-12-20 DOI: 10.4108/ew.4659
Ajit Singh, M.M.H. College, G. F. R. P. Extension, Pallav Puram, Meerut Modi Puram
Sustainable economic development is crucial to secure human welfare and eliminate social inequality. Global leaders have recently made progress towards reaching an agreement on how to convert the current unsustainable economic trends into sustainable green economic growth. The viability of the green economy depends on several variables, including governmental policy, the business climate, and environmental concerns. The presented paper examines the implementation of green economic policies and analyses government strategies and initiatives taken by the government at the national level. The study uses a descriptive-analytical approach. The study finds India is putting many regulations and initiatives into place to encourage the effective use of energy in a variety of economic areas, including green building, equipment, farming, mobility, and fuels. These green growth initiatives lower the economy's carbon intensity and provide a sizable number of green jobs.
可持续经济发展对于保障人类福祉和消除社会不平等至关重要。全球领导人最近在就如何将当前不可持续的经济趋势转变为可持续的绿色经济增长达成一致方面取得了进展。绿色经济的可行性取决于多个变量,包括政府政策、商业环境和环境问题。本文探讨了绿色经济政策的实施情况,分析了政府在国家层面采取的战略和举措。研究采用了描述性分析方法。研究发现,印度正在出台许多法规和举措,鼓励在绿色建筑、设备、农业、交通和燃料等多个经济领域有效利用能源。这些绿色增长举措降低了经济的碳强度,并提供了大量绿色就业机会。
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引用次数: 0
Climate Smart Agriculture Practices in India 印度的气候智能型农业实践
Q3 Engineering Pub Date : 2023-12-19 DOI: 10.4108/ew.4645
Manisha Singh, Fatima Qasim Hasan
According to the World Bank, Climate-smart agriculture encompasses the comprehensive management of landscapes, including land under cultivation, livestock, woodland areas, and aquatic resources, addressing the interconnected issues of food security and climate change. United Nations Population Fund or UNFPAs Population dashboard shows India’s population at 1406.6 million with an annual average rate of population increase at 0.9% from 2020-25. To meet this food demand, it is imperative for India to adapt sustainable agricultural practices. The IPCC (Inter-governmental panel on climate change) report has pointed out that climate change has affected food security due to global warming and extremes of temperatures around the World. In light of these facts, India faces the unique challenge of developing a path of enhancing the country’s food supply, ensuring water availability while minimizing agricultural GHGs (Greenhouse emissions) which are estimated to be 14% of its total GHG emissions. In the 2021 Global Climate Risk Index (CRI), India was ranked 7th, with a CRI score of 16.67. This paper aims at understanding the theoretical and conceptual framework of climate smart agriculture and presents an insight into how the objectives of food sufficiency, change in climatic conditions and greenhouse gas emissions are being met in India through policies, institutions and financial models.
据世界银行称,气候智能型农业包含对地貌的综合管理,包括耕地、牲畜、林地和水产资源,以解决粮食安全和气候变化等相互关联的问题。联合国人口基金人口仪表板显示,印度人口为 1.4066 亿,2020-25 年间年均人口增长率为 0.9%。为满足这一粮食需求,印度必须采用可持续的农业生产方式。政府间气候变化专门委员会(IPCC)的报告指出,由于全球变暖和世界各地的极端气温,气候变化已经影响到粮食安全。鉴于这些事实,印度面临着一个独特的挑战,即如何发展一条既能增加国家粮食供应、确保水资源供应,又能最大限度减少农业温室气体排放的道路,据估计,农业温室气体排放占其温室气体排放总量的 14%。在 2021 年全球气候风险指数(CRI)中,印度排名第七,CRI 得分为 16.67。本文旨在了解气候智能型农业的理论和概念框架,并深入探讨印度如何通过政策、机构和金融模式来实现粮食充足、气候条件变化和温室气体排放等目标。
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引用次数: 0
Energizing Tomorrow: Analyzing the Transformative Potential of Electric Vehicle Adoption 为明天注入活力:分析电动汽车应用的变革潜力
Q3 Engineering Pub Date : 2023-12-15 DOI: 10.4108/ew.4611
Neha Seth, Saif Siddiqui, Muhammed Asif PC, Anu Agnihotri, Muskan Gupta
INTRODUCTION: A developing economy lacks the infrastructure required to produce renewable energy sources on a large scale that can be coupled with conventional resources. This prevents the economy from taking advantage of these types of resources. The emergence of the electric vehicles (EVs) industry has been a primary catalyst for both the expansion of the economy and the production of new employment opportunities. The manufacturing and distribution of electronic automobiles have cleared the way for the construction of new manufacturing locations as well as a supply chain. This has been made possible as a result of the increased demand for EVs. OBJECTIVES: The objectives of this article are to know the overall impact of EVs on the environment through a review of the literature and to study if ongoing changes affect the economy of India. METHODS: The systematic review of literature is used to fulfil the objectives of the study. RESULTS: EVs offer a solution to reducing air pollution and greenhouse gas emissions due to their zero tailpipe emissions. They eliminate pollutants like nitrogen oxide and particulate matter, improving air quality and public health. EVs, powered by renewable energy sources like solar, wind, or hydroelectric power, reduce reliance on fossil fuels. Their higher energy efficiency and technological advancements in batteries also create employment and innovative economic opportunities. Additionally, EVs contribute to quieter and more serene environments, especially in densely populated areas, due to their silent operation. CONCLUSION: It can be concluded that the adoption of EVs has both positive and negative impacts on economy countries. But as compared to negative impacts, positive impacts are very high on the economic condition of any country.
导言:发展中经济体缺乏大规模生产可与传统资源相结合的可再生能源所需的基础设施。这阻碍了经济利用这些类型的资源。电动汽车(EV)产业的出现是经济扩张和创造新就业机会的主要催化剂。电子汽车的制造和分销为建设新的生产基地和供应链扫清了道路。由于对电动汽车的需求增加,这才成为可能。目标:本文旨在通过文献综述了解电动汽车对环境的总体影响,并研究正在发生的变化是否会影响印度的经济。方法:为实现研究目标,对文献进行了系统回顾。结果:电动汽车尾气零排放,为减少空气污染和温室气体排放提供了解决方案。电动汽车可消除氮氧化物和颗粒物等污染物,改善空气质量和公众健康。电动汽车以太阳能、风能或水电等可再生能源为动力,减少了对化石燃料的依赖。电动汽车更高的能效和电池技术的进步也创造了就业和创新经济机会。此外,电动汽车的静音运行还有助于营造更安静、更宁静的环境,尤其是在人口稠密的地区。结论:可以得出结论,电动汽车的采用对经济国家既有积极影响,也有消极影响。但与负面影响相比,正面影响对任何国家的经济状况都非常重要。
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引用次数: 0
The Use of Artificial Intelligence to Optimize the Routing of Vehicles and Reduce Traffic Congestion in Urban Areas 利用人工智能优化车辆行驶路线,缓解城市交通拥堵状况
Q3 Engineering Pub Date : 2023-12-15 DOI: 10.4108/ew.4613
Srishti Dikshit, Areeba Atiq, Mohammad Shahid, Vinay Dwivedi, Aarushi Thusu
The swift urbanization of cities has given rise to an unparalleled surge in vehicular traffic, leading to substantial congestion, heightened pollution, and a diminished quality of life. This investigation explores the capacity of artificial intelligence (AI) to transform urban mobility by optimizing vehicle routing and alleviating traffic congestion. The objective is to create AI-powered solutions that augment transportation efficiency, diminish travel times, and mitigate environmental repercussions. This paper thoroughly scrutinizes existing AI algorithms, vehicle routing, and traffic management techniques. The study integrates real-time traffic data, road network characteristics, and individual travel patterns to formulate intelligent routing strategies. The proposed AI system adjusts to dynamic traffic conditions through machine learning and optimization algorithms, pinpointing optimal routes and redistributing traffic flows to minimize congestion hotspots. To assess the effectiveness of the AI-driven approach, extensive simulations and case studies are conducted in representative urban areas. Performance metrics, including travel time reduction, fuel consumption, and emissions reduction, are employed to quantify the impact of the proposed system on traffic congestion and environmental sustainability. Furthermore, the study evaluates the scalability, feasibility, and economic viability of implementing AI-based traffic management solutions on a larger scale. The outcomes of this research provide valuable insights into the potential advantages of AI in reshaping urban mobility. By optimizing vehicle routing and diminishing traffic congestion, the proposed AI-driven system has the potential to elevate overall transportation efficiency, reduce energy consumption, and contribute to a healthier urban environment. The findings carry substantial implications for policymakers, urban planners, and transportation authorities seeking innovative solutions to tackle the challenges of contemporary urbanization while promoting sustainable development.
城市的快速城市化带来了无与伦比的车辆交通流量激增,导致严重拥堵、污染加剧和生活质量下降。本研究探讨了人工智能(AI)通过优化车辆路线和缓解交通拥堵来改变城市交通的能力。其目的是创建由人工智能驱动的解决方案,以提高交通效率、缩短出行时间并减轻环境影响。本文深入研究了现有的人工智能算法、车辆路由和交通管理技术。研究整合了实时交通数据、路网特征和个人出行模式,以制定智能路由策略。所提出的人工智能系统通过机器学习和优化算法来适应动态交通状况,精确定位最佳路线并重新分配交通流,以尽量减少拥堵热点。为了评估人工智能驱动方法的有效性,我们在具有代表性的城市地区进行了广泛的模拟和案例研究。采用的性能指标包括旅行时间减少、燃料消耗和排放减少,以量化拟议系统对交通拥堵和环境可持续性的影响。此外,研究还评估了在更大范围内实施基于人工智能的交通管理解决方案的可扩展性、可行性和经济可行性。这项研究的成果为人工智能在重塑城市交通方面的潜在优势提供了宝贵的见解。通过优化车辆路线和减少交通拥堵,拟议的人工智能驱动系统有可能提高整体交通效率、减少能源消耗,并为营造更健康的城市环境做出贡献。这些发现对寻求创新解决方案的决策者、城市规划者和交通管理部门具有重大意义,他们可以在促进可持续发展的同时,应对当代城市化带来的挑战。
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引用次数: 0
Analysis of Factors Influencing Successful Implementation of ODA Projects for Rural Development: The Case of Kyrgyzstan 影响农村发展官方发展援助项目成功实施的因素分析:以吉尔吉斯斯坦为例
Q3 Engineering Pub Date : 2023-11-14 DOI: 10.4108/ew.4387
Young-Chool Choi, Yanghoon Song, Ki Seo Kong, Ahyoun Lee
This paper aims to identify factors that influence the successful implementation of ODA rural development projects for developing countries. To this end, it has analysed the implementation process of a project, ‘The Integrated Rural Development Project in Kyrgyz Republic’, currently being carried out in Kyrgyzstan via Good Neighbors International (GNI) with support from KOICA (Korean International Cooperation Agency). The analysis method employed in this study is decision tree analysis. By means of a review of previous studies on the implementation of ODA projects, variables that are believed to have an impact on the successful implementation of ODA rural development projects were derived. The values of each variable for thirty villages in Kyrgyzstan were derived and used as independent variables, and decision tree analysis was performed using the overall execution performance score for each village as the dependent variable. As a result, it was found that co-operation between field managers active at the project site and village residents was the most important determining factor of success.
本文旨在确定影响发展中国家成功实施官方发展援助农村发展项目的因素。为此目的,它分析了“吉尔吉斯斯坦共和国农村综合发展项目”的实施过程,该项目目前在韩国国际协力团的支持下,通过“好邻居国际”(GNI)在吉尔吉斯斯坦实施。本研究采用的分析方法是决策树分析。通过审查以前关于执行官方发展援助项目的研究,得出了被认为对成功执行官方发展援助农村发展项目有影响的变量。推导了吉尔吉斯斯坦30个村庄的每个变量的值,并将其用作自变量,并使用每个村庄的总体执行绩效得分作为因变量进行决策树分析。结果发现,在项目现场活动的实地管理人员与村庄居民之间的合作是成功的最重要决定因素。
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引用次数: 0
Dynamic Voltage Restorer to Mitigate Voltage Sag/Swell using Black Widow Optimization Technique with FOPID Controller 基于FOPID控制器的黑寡妇优化技术的动态电压恢复系统
Q3 Engineering Pub Date : 2023-11-08 DOI: 10.4108/ew.4331
B. Srikanth Goud, M. Kiran Kumar, Narisetti Ashok Kumar, CH. Naga Sai Kalyan, Mohit Bajaj, Subhashree Choudhury, Swati Shukla
The efficiency with which electrical equipment use electricity is essential for several reasons. First, superior power quality (PQ) improves efficiency and facilitates peak performance in electronic equipment. This article's goal is to make the advantages of installing a Dynamic Voltage Restorer (DVR) to enhance PQ for energy users clearer. To improve DVR dependability and user friendliness, the suggested technique uses a hysteresis voltage control system that works with variable switching frequency. Simulation findings show that voltage compensation is successful under disturbances when a black widow optimization (BWO) based Factional order proportional derivative (FOPID) controller is used. This paper proposed is to improve PQ using a BWO- FOPID controller and compare the outcomes to those achieved from a previously developed PI controller in a distribution power system using MATLAB.
出于几个原因,电气设备用电的效率是必不可少的。首先,卓越的电能质量(PQ)提高了效率,促进了电子设备的峰值性能。本文的目标是使安装动态电压恢复器(DVR)以提高电能用户PQ的优势更加清晰。为了提高DVR的可靠性和用户友好性,建议的技术使用可变开关频率的滞后电压控制系统。仿真结果表明,当采用基于黑寡妇优化(BWO)的分阶比例导数(FOPID)控制器时,在干扰下电压补偿是成功的。本文提出使用BWO- FOPID控制器来改善PQ,并使用MATLAB将其结果与先前开发的配电系统PI控制器的结果进行比较。
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引用次数: 0
A Novel Approach for Earthquake Prediction Using Random Forest and Neural Networks 一种基于随机森林和神经网络的地震预测新方法
Q3 Engineering Pub Date : 2023-11-08 DOI: 10.4108/ew.4329
Nidhi Agarwal, Ishika Arora, Harsh Saini, Ujjwal Sharma
INTRODUCTION: This research paper presents an innovative method that merges neural networks and random forest algorithms to enhance earthquake prediction. OBJECTIVES: The primary objective of the study is to improve the precision of earthquake prediction by developing a hybrid model that integrates seismic wave data and various extracted features as inputs. METHODS: By training a neural network to learn the intricate relationships between the input features and earthquake magnitudes and employing a random forest algorithm to enhance the model's generalization and robustness, the researchers aim to achieve more accurate predictions. To evaluate the effectiveness of the proposed approach, an extensive dataset of earthquake records from diverse regions worldwide was employed. RESULTS: The results revealed that the hybrid model surpassed individual models, demonstrating superior prediction accuracy. This advancement holds profound implications for earthquake monitoring and disaster management, as the prompt and accurate detection of earthquake magnitudes is vital for effective mitigation and response strategies. CONCLUSION: The significance of this detection technique extends beyond theoretical research, as it can directly benefit organizations like the National Disaster Response Force (NDRF) in their relief efforts. By accurately predicting earthquake magnitudes, the model can facilitate the efficient allocation of resources and the timely delivery of relief materials to areas affected by natural disasters. Ultimately, this research contributes to the growing field of earthquake prediction and reinforces the critical role of data-driven approaches in enhancing our understanding of seismic events, bolstering disaster preparedness, and safeguarding vulnerable communities.
摘要:本文提出了一种将神经网络与随机森林算法相结合的地震预测方法。目的:本研究的主要目的是通过开发一种将地震波数据和各种提取特征作为输入的混合模型来提高地震预测的精度。 方法:通过训练神经网络学习输入特征与地震震级之间的复杂关系,并采用随机森林算法增强模型的泛化和鲁棒性,实现更准确的预测。为了评估所提出方法的有效性,使用了来自全球不同地区的地震记录的广泛数据集。 结果:混合模型的预测精度优于单个模型。这一进展对地震监测和灾害管理具有深远的影响,因为及时准确地探测地震震级对于有效的减灾和应对战略至关重要。结论:这种检测技术的意义超越了理论研究,因为它可以直接使国家灾害响应部队(NDRF)等组织在救灾工作中受益。该模型通过对地震震级的准确预测,有利于资源的有效配置和救灾物资的及时送达。最终,这项研究有助于不断发展的地震预测领域,并加强数据驱动方法在增强我们对地震事件的理解、加强灾害准备和保护脆弱社区方面的关键作用。
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 OBJECTIVES: The primary objective of the study is to improve the precision of earthquake prediction by developing a hybrid model that integrates seismic wave data and various extracted features as inputs.
 METHODS: By training a neural network to learn the intricate relationships between the input features and earthquake magnitudes and employing a random forest algorithm to enhance the model's generalization and robustness, the researchers aim to achieve more accurate predictions. To evaluate the effectiveness of the proposed approach, an extensive dataset of earthquake records from diverse regions worldwide was employed.
 RESULTS: The results revealed that the hybrid model surpassed individual models, demonstrating superior prediction accuracy. This advancement holds profound implications for earthquake monitoring and disaster management, as the prompt and accurate detection of earthquake magnitudes is vital for effective mitigation and response strategies.
 CONCLUSION: The significance of this detection technique extends beyond theoretical research, as it can directly benefit organizations like the National Disaster Response Force (NDRF) in their relief efforts. By accurately predicting earthquake magnitudes, the model can facilitate the efficient allocation of resources and the timely delivery of relief materials to areas affected by natural disasters. Ultimately, this research contributes to the growing field of earthquake prediction and reinforces the critical role of data-driven approaches in enhancing our understanding of seismic events, bolstering disaster preparedness, and safeguarding vulnerable communities.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"32 S111","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135343214","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}
引用次数: 0
Empirical Study on Influencing Factors of Rural Environmental Behavior in Informatization 信息化背景下农村环境行为影响因素实证研究
Q3 Engineering Pub Date : 2023-11-03 DOI: 10.4108/ew.4301
Jianming Cai, Hong Ling, Chao Yang, Jianfeng Gu
INTRODUCTION: With the advent of the information technology era, rural areas face new environmental protection challenges and opportunities. The rapid development of information technology provides new possibilities for changes in rural ecological behavior. However, understanding the influencing factors of rural environmental behavior in the context of information technology remains an important research topic. OBJECTIVES: This study aims to reveal the influencing factors of rural environmental behavior in the context of information technology to help governments and policymakers develop effective environmental protection strategies. Specifically, the researchers will focus on the extent to which factors such as education level, ecological awareness, economic status, and social participation influence the environmental behavior of rural residents. METHODS: A questionnaire survey was used in this study, and residents of a particular rural area were selected as the research subjects. A questionnaire containing questions on education level, environmental awareness, economic status, social participation, and environmental behavior was designed, and a large amount of data was collected through random sampling. Statistical analysis methods, such as regression and correlation analyses, were used to process and interpret the data. RESULTS: The study's results showed that the education level significantly affected the environmental behavior of rural residents. Residents with higher levels of education were more inclined to take positive ecological protection actions such as waste separation and energy conservation. In addition, environmental awareness was also found to be closely related to environmental behavior, with residents with higher ecological awareness being more concerned about environmental protection and taking action accordingly. Economic status and social participation affected rural residents' environmental behavior to a certain extent but to a lesser extent than education level and ecological awareness. CONCLUSION: Rural environmental behavior in the context of informatization is affected by a combination of factors. To promote rural ecological protection, the government should strengthen investment in education and improve rural residents' education level and environmental awareness. In addition, social organizations and public participation should also be supported to encourage rural residents to actively participate in environmental protection actions. These measures will help to promote a change in ecological behavior in rural areas and achieve the goal of sustainable development.
引言:随着信息技术时代的到来,农村环境保护面临着新的挑战和机遇。信息技术的快速发展为农村生态行为的变化提供了新的可能。然而,了解信息技术背景下农村环境行为的影响因素仍然是一个重要的研究课题。 目的:本研究旨在揭示信息技术背景下农村环境行为的影响因素,以帮助政府和决策者制定有效的环境保护策略。具体而言,研究人员将关注教育水平、生态意识、经济地位和社会参与等因素对农村居民环境行为的影响程度。 方法:采用问卷调查的方法,选取某农村地区的居民作为研究对象。设计了包含受教育程度、环境意识、经济状况、社会参与、环境行为等问题的调查问卷,采用随机抽样的方式收集了大量数据。采用回归分析、相关分析等统计分析方法对数据进行处理和解释。 结果:研究结果表明,受教育程度显著影响农村居民的环境行为。受教育程度越高的居民更倾向于采取垃圾分类、节能等积极的生态保护行动。此外,环境意识也与环境行为密切相关,生态意识越高的居民对环境保护的关注程度越高,并采取相应的行动。经济地位和社会参与对农村居民环境行为有一定影响,但影响程度低于教育水平和生态意识。 结论:信息化背景下农村环境行为受到多种因素的综合影响。为促进农村生态保护,政府应加大对教育的投入,提高农村居民的教育水平和环保意识。此外,还应支持社会组织和公众参与,鼓励农村居民积极参与环境保护行动。这些措施将有助于促进农村生态行为的转变,实现可持续发展的目标。
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 OBJECTIVES: This study aims to reveal the influencing factors of rural environmental behavior in the context of information technology to help governments and policymakers develop effective environmental protection strategies. Specifically, the researchers will focus on the extent to which factors such as education level, ecological awareness, economic status, and social participation influence the environmental behavior of rural residents.
 METHODS: A questionnaire survey was used in this study, and residents of a particular rural area were selected as the research subjects. A questionnaire containing questions on education level, environmental awareness, economic status, social participation, and environmental behavior was designed, and a large amount of data was collected through random sampling. Statistical analysis methods, such as regression and correlation analyses, were used to process and interpret the data.
 RESULTS: The study's results showed that the education level significantly affected the environmental behavior of rural residents. Residents with higher levels of education were more inclined to take positive ecological protection actions such as waste separation and energy conservation. In addition, environmental awareness was also found to be closely related to environmental behavior, with residents with higher ecological awareness being more concerned about environmental protection and taking action accordingly. Economic status and social participation affected rural residents' environmental behavior to a certain extent but to a lesser extent than education level and ecological awareness.
 CONCLUSION: Rural environmental behavior in the context of informatization is affected by a combination of factors. To promote rural ecological protection, the government should strengthen investment in education and improve rural residents' education level and environmental awareness. In addition, social organizations and public participation should also be supported to encourage rural residents to actively participate in environmental protection actions. These measures will help to promote a change in ecological behavior in rural areas and achieve the goal of sustainable development.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"26 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135820396","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}
引用次数: 0
Frequency control of power system with electric vehicles using hybrid african vultures optimization algorithm and pattern search tuned fuzzy PID controller 基于混合非洲秃鹫优化算法和模式搜索调谐模糊PID控制器的电动汽车电力系统频率控制
Q3 Engineering Pub Date : 2023-10-30 DOI: 10.4108/ew.135
P M Dash, A K Baliarsingh, Sangram K Mohapatra
This work suggests a hybrid African Vultures Optimization Algorithm (AVOA) and Pattern search (hAVOA-PS) based Fuzzy PID (FPID) structure for frequency control of a nonlinear power system with Electric Vehicles (EVs). To illustrate the dominance of the projected hAVOA-PS algorithm, initially PI controllers are considered and results are compared with AVOA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods. To further enhance the dynamic performance, PID and FPID controllers are considered. The dominance of FPID over PID and PI controllers is shown. In the next step, EVs are incorporated in the test system and a comparative analysis of hAVOA-PS based PI/PID/FPID and FPID+EV is presented. To exhibit the superiority of projected frequency control scheme in maintaining the stability of system under different disturbance conditions like load increase in area-1 only, load decrease/increase in all areas, and large load increase in all areas are considered. It is noticed that the suggested hAVOA-PS based FPID controller n presence of EV is able to maintain system stability for all the considered cases where as other compared approaches fail to maintain stability in some cases.
本文提出了一种基于非洲秃鹫优化算法(AVOA)和模式搜索(hAVOA-PS)的混合模糊PID (FPID)结构,用于电动汽车非线性电力系统的频率控制。为了说明投影hAVOA-PS算法的优势,首先考虑了PI控制器,并将结果与AVOA、遗传算法(GA)和粒子群优化(PSO)方法进行了比较。为了进一步提高系统的动态性能,采用了PID和FPID控制器。显示了FPID优于PID和PI控制器的优势。接下来,将电动汽车纳入测试系统,并对基于hAVOA-PS的PI/PID/FPID和FPID+EV进行了比较分析。考虑了1区负荷仅增加、所有区域负荷均增加/减少、所有区域负荷均大幅增加等不同扰动条件下,投影频率控制方案在保持系统稳定性方面的优越性。值得注意的是,在存在EV的情况下,建议的基于hAVOA-PS的FPID控制器能够在所有考虑的情况下保持系统稳定性,而其他比较方法在某些情况下无法保持稳定性。
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引用次数: 0
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