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Editor(s)-in-Chief: Albert Lam, Emeritus Editors-in-Chief and Ghazanfar Safdar

EAI Endorsed Transactions on Energy Web is an open access, peer-reviewed scholarly journal focused on cross-section topics related to IT and Energy. The journal publishes research articles, review articles, commentaries, editorials, technical articles, and short communications with a continuous frequency.

INDEXING: Scopus (CiteScore: 2.2), Compendex, DOAJ, ProQuest, EBSCO, DBLP

  • Editors-in-Chief
  • Albert Lam, University of Hong Kong, HK
  • Area Editors
  • Mikhail Medvedev (Southern Federal University, Russia)
  • Vladimir Dyo (University of Bedfordshire, UK)
  • Andrey Mazalov (South Federal University, Russia)
  • Elena Gebel (Omsk State Technical University, Russia)
  • Irina Semykina (T. F. Gorbachev Kuzbass State Technical University, Russia)
  • Vyacheslav Potekhin (Peter the Great St. Petersburg Polytechnic University, Russia)
  • Sabu Thampi (Indian Institute of Information Technology and Management-Kerala (IIITM-K), India)
  • Manik Sharma (DAV University, India)
  • Amando P. Singun JR. (University of Technology and Applied Sciences, Muscat, Oman)
  • Irina Semykina (Sevastopol State University, Ukraine)
  • Abel C. Chen (Chunghwa Telecom Laboratories, Taiwan)
  • Vitor Monteiro (University of Minho, Portugal)
  • Joao L. Afonso (University of Minho, Portugal)
  • Abdul Shabeer (IBM India Pvt Ltd, Chennai, India)
  • Anandakumar H (Sri Eshwar College of Engineering, India)
  • Marta Chinnici (ENEA, Italy)
  • Howard NJOKU (University of Nigeria, Nigeria)
  • José Gabriel Oliveira Pinto (University of Minho, Portugal)
  • P Krishna (VIT University, India)
  • Jacinth Poornima (Hindusthan College of Engineering and Technology, India)
  • Karthikumar S (Anna University)
  • Duckki Lee (Yonam Institute of Technology, South Korea)
  • A. Hnatov (Kharkiv National Automobile and Highway University, Ukraine)
  • Dr. P. Karthikeyan (Jain University, India)
  • Sagheer Abbas (National College of Business Administration and Economics, Pakistan)
  • Ahmed Elngar (Beni-Suef University, Egypt)
  • Debnath Bhattacharyya (KL University, India)
  • Jatinder Manhas (University of Jammu, India)
  • Michele Mastroianni (University of Salerno, Italy)
  • Hitesh Mohapatra (KIIT University, India)
  • Brojo Kishore Mishra (NIST Berhampur, India)
  • Chin-Ling Chen (Chaoyang University of Technology, Taiwan)
  • Sudhakar Sengan (PSN College of Engineering and Technology, India)
  • Haris M. Khalid (University of Dubai, United Arab Emirates)
  • Emeritus Editors-in-Chief
  • Ghazanfar Safdar, University of Bedfordshire, UK

  • Harmonic Measurement Algorithm of Power System Integrating Wavelet Transform and Deep Learning

    Appears in:
    ew 24(1):

    Authors:
    Zeyang Liu, Zhu Liu, Yutian Li, Hanshu Jiang, Guanghao Wu

    Published:
    10th Dec 2024

    Abstract:
    INTRODUCTION: The problem of low accuracy in harmonic measurement is a significant challenge in power systems. Traditional methods often exhibit higher measurement errors, leading to unreliable detection of harmonics. To address this, the author proposes a new approach that integrates wavelet transform and deep learning techniques for enhanced harmonic measurement accuracy. OBJECTIVES: The primary goal of this study is to develop a more accurate harmonic measurement algorithm by combining full phase fast Fourier transform (FFT) and adaptive neural networks. The research aims to automatically detect power system harmonics with minimal error and improve upon the limitations of traditional methods. METHODS: The study implemented a harmonic measurement method using full phase FFT integrated with an adaptive neural network. This approach calculates harmonic amplitudes based on the fundamental component and its amplitude, while determining the precise start and end times of harmonics. The system also incorporates mean filtering for automatic detection of harmonics. The effectiveness of the proposed method was evaluated through experiments that compared it to traditional harmonic measurement techniques. RESULTS: Experimental results demonstrated that the proposed method achieved an average measurement error of 0.02V, with a maximum error of 0.03V, both of which are below the acceptable error limit. In contrast, traditional methods exhibited significantly higher average errors of 3.31V and a maximum error of 5.17V. The new method consistently showed higher accuracy in harmonic detection compared to conventional approaches. CONCLUSION: The study concludes that the proposed harmonic measurement algorithm significantly improves accuracy compared to traditional methods. With its lower measurement error and effective automatic detection capabilities, the method proves to be highly suitable for harmonic measurement in power systems.

  • Research on Improvement Calculation Method of Grid Power Losses Based on New Energy Access Model

    Appears in:
    ew 24(1):

    Authors:
    Xiaofeng Feng, Xiashan Feng, Jun Zhang, Huakun QUE, Xiling Tang

    Published:
    4th Dec 2024

    Abstract:
    This research presents an improved calculation method for grid power losses, particularly focusing on the challenges posed by new energy access models. With the integration of electric vehicles and the rise of data centers, the demand for electrical energy has surged, leading to increased strain on grid stations and subsequent power losses. The proposed model aimed at reducing these power losses, while also examining existing systems to mitigate and analyze such issues. A significant contribution of this work is the application of the Random Forest machine learning algorithm, which enables efficient and accurate power flow calculations essential for optimizing grid performance. The proposed method is expected to enhance the grid’s ability to handle future energy demands and contribute to the sustainable development of electrical energy systems.

  • Using STAR-CCM+ Software in Aerodynamic Performance of Bogies under Crosswind Conditions

    Appears in:
    ew 24(1):

    Authors:
    Xiaoli Chen, Yongrong Jin

    Published:
    4th Dec 2024

    Abstract:
    INTRODUCTION: STAR-CCM+ is a CFD software that uses continuum mechanics numerical techniques and is a tool for thermodynamic and fluid dynamics analysis. STAR-CCM+has expanded the functions of surface treatment, such as surface wrapper, surface remesh, and volume mesh generation.With the increase of train speed, the aerodynamic phenomena become more prominent, and the aerodynamic phenomena of high-speed trains in crosswind environment become more complicated. OBJECTIVES: Bogie is an important part of high-speed train. It is of great significance to study the aerodynamic performance Three groups of trains operating in a strong wind environment are modeled, and the surface pressure distribution characteristics of the car body and bogie, as well as the aerodynamic and aerodynamic torque distribution characteristics of each car and bogie, are analyzed when the train operates at 350km/h under a Class 12 crosswind condition. RESULTS: The results of the study show the variation rules of surface pressure, aerodynamic force and aerodynamic moment of the car body and bogie with wind speed. CONCLUSION: The windward surface pressure of the vehicle body increases linearly with the increase of wind speed, and the surface pressure of the roof and leeward side decreases linearly with the increase of wind speed.

  • Optimization and privacy protection of microgrid power trading system based on attribute encryption technology

    Appears in:
    ew 24(1):

    Authors:
    Dejun Xiang, Rui Zhou, Xin Hu, Kangqian Huang

    Published:
    4th Dec 2024

    Abstract:
    This paper presents an effective technique and approach to deal with the dual challenges of performance optimization and privacy protection in microgrid power trading systems (MPTS) by utilizing attribute encryption technology. By embedding advanced cryptographic techniques into the operational substrate of microgrids, we introduce a novel approach to dramatically enhance the efficiency of energy distribution, while guaranteeing the privacy protection and integrity of participant data. The core objective of this technique is the application of attribute-based encryption (ABE), a method that offers fine-grained access control, ensuring sensitive information is made available only to eligible users based on their attributes, rather than their identities. In doing so, it meets the important requirement of securing data, without impairing the overall productivity of a power trading system. This paper presents a novel technique of ABE in the domain of MPTS, but also quantifies, through extensive theoretical analysis and simulations, how this integration leads to superior energy resource allocation and lower operational costs.

  • Effect of a resampling method on the effectiveness of multi-layer neural network models in PV power forecasting

    Appears in:
    ew 24(1):

    Authors:
    Zakaria Belboul, Abdellah Kouzou, Toual Belgacem, Abderrahman Bensalem

    Published:
    4th Dec 2024

    Abstract:
    The primary aim of this study was to explore the impact of employing the K-fold Cross Validation resampling method in contrast to the hold-out set validation approach on the efficacy of forecasting models utilizing Multi-layer Neural Networks (MNN) for predicting photovoltaic (PV) output power. Real data sourced from southern Algeria was utilized for this purpose. The performance of various configurations of MNN models, with differing learning rate values, was evaluated using the coefficient of variation of Root Mean Square Error (CV(RMSE)). The findings consistently demonstrate that models developed using K-fold Cross Validation exhibited superior performance across most scenarios. These results underscore the potential advantages of leveraging such resampling techniques in terms of both generalization and robustness of forecasting models.

  • Optimal Placement and sizing of DG Units Using LCA Algorithm

    Appears in:
    ew 24(1):

    Authors:
    Abdelouahab Necira, Abdelhafid Rouina, Djemoui Benkhetta

    Published:
    4th Dec 2024

    Abstract:
    The motivation of this paper is to present an approach that relies on the league championship algorithm (LCA) to determine the most effective number, placement, and size of distributed generations (DG) within distribution systems. The primary objective of this approach is to minimize the losses of the power system, as well as to enhance the voltage profiles and stability index of the voltage. The optimal location of the DG units is determined through the use of the Loss Sensitivity Factor (LSF), while the optimal size of the DG units is found through the use of LCA. The IEEE 33-bus and 69-bus radial distribution systems were both tested to validate the proposed method, and the results obtained from LCA were compared to those of other methods found in the literature. The simulated results have shown that the LCA method proposed in this paper is highly effective and performs exceptionally well when addressing the problem of optimal location and sizing of DG units in radial networks.  

  • Design and Application of Global Energy Trade Cross Border E-commerce Optimization Model

    Appears in:
    ew 24(1):

    Authors:
    Jianing Shan

    Published:
    4th Dec 2024

    Abstract:
    INTRODUCTION: With the continuous advancement of global economic integration, cross-border energy trade activities internationally are becoming increasingly frequent. OBJECTIVES: To improve the efficiency of energy trade, this study is devoted to exploring the optimization model of cross-border e-commerce in global energy trade. Introducing advanced information technology and e-commerce platforms aims to facilitate the digital transformation of energy trade, improve transaction efficiency, reduce costs, and promote sustainable energy development. METHODS: This study adopts a comprehensive methodology, including a literature review, case analysis, and model construction. First, relevant literature on global energy trade and cross-border e-commerce was thoroughly studied to understand the current development status and existing problems. Second, the successful experiences and challenges of cross-border e-commerce in enhancing the efficiency of energy trade are summarized through the analysis of several international cases. Finally, a set of optimization models that comprehensively consider market demand, technical conditions, and policy environment are constructed to guide the development of cross-border e-commerce in global energy trade. RESULTS: The empirical analysis of the optimization model reveals that cross-border e-commerce has significant potential in international energy trade. The model can effectively improve transaction efficiency, reduce the risk of information asymmetry, and promote the balanced development of the global energy market. It is also observed that digital transformation significantly affects the promotion of sustainable energy, providing a more sustainable path for global energy transition. CONCLUSION: By establishing a cross-border e-commerce optimization model for international energy trade, this study provides substantial theoretical and empirical support for promoting the digital transformation of energy trade. In the future, governments, enterprises, and international organizations can draw on the conclusions of this study to formulate relevant policies and strategies to promote global energy trade jointly toward a more efficient and sustainable development path.

  • Input-Output Performance Evaluation of Science and Technology Enterprises Based on DEA Model

    Appears in:
    ew 24(1):

    Authors:
    Guoliang Sun, Bayi Guan

    Published:
    4th Dec 2024

    Abstract:
    INTRODUCTION: For enterprises, the results of performance evaluation will be affected by the selected input and output factors, so the indicators of the evaluation system should be representative and characteristic, and the evaluation method should be reasonable. OBJECTIVES: According to the characteristics of science and technology industry, this paper establishes the performance evaluation index system, and the evaluation model of the input-output performance for the science and technology enterprises. METHODS: With the evaluation model, this paper empirically analyses the evaluation index data of 30 science and technology enterprises in recent 3 years, and verifies the effectiveness of the selection of management performance evaluation index of science and technology enterprises. RESULTS: Finally, according to the empirical analysis results of the evaluation model. CONCLUSION: This paper puts forward some countermeasures to improve the business performance of science and technology enterprises.

  • Key players in renewable energy and artificial intelligence research

    Appears in:
    ew 24(1):

    Authors:
    Rolando Eslava-Zapata, Emma Juaneda-Ayensa, Verenice Sánchez-Castillo

    Published:
    4th Dec 2024

    Abstract:
    INTRODUCTION: As countries work on the transition towards renewable energies that comply with the 2030 Agenda and the sustainable development goals, Artificial Intelligence is presented as a tool that is being adopted to promote the generation of renewable energies such as solar or wind power. , given the support it offers to automation, assisted decisions, and production efficiency. OBJECTIVES: To analyze the key players in renewable energy and artificial intelligence research. METHODS: The Scopus database is used to obtain the scientific articles for the period 2013-2023, and the Visualization of Similarities program (VOSviewer 1.6.18) is used for data processing and analysis. RESULTS: An analysis of 822 articles shows that the countries with the highest scientific production are China (148), India (136) and the United States (81). In this regard, it is clear that there is significant collaboration between countries. With regard to the analysis of Co-occurrence - Author Keywords, three clusters are generated. The first cluster, identified with the color red, is related to artificial intelligence management; the second cluster, identified with the color green, is related to artificial intelligence innovation; and the third cluster, identified with the color blue, is related to energy models. CONCLUSION: Researchers are facing new challenges every day to respond to the irruption of the use of new algorithms in the generation of renewable energies, given the range of available tools such as deep learning or neural networks. Research results have revealed that in recent years, scientific production has understood that AI is not a trend but rather a challenge facing society, industry, countries, or education in order to achieve sustainable development.

  • Study on the Influence of Land Use Change on Carbon Emissions Using System Modeling under the Framework of Dual Carbon Goals

    Appears in:
    ew 24(1):

    Authors:
    Qianqian Ma, Hongfei Liu, Hongchao Li, Jia Jia, Jingjing Huang, Zhengyu Yang, Pingli Zhang

    Published:
    4th Dec 2024

    Abstract:
    At the crucial period of addressing climate change, especially to the carbonization of land use change, it is vital that relevant actions are taken to enable two ambitious dual-carbon goals, namely, ensuring that carbon emissions peak before 2030 and achieving carbon neutrality before 2060. This research investigates the impacts of land use changes on carbon emissions using a novel approach that integrates Light Detection and Ranging (LiDAR) with Geographic Information System (GIS). This approach is innovative due to its high quality three-dimensional representation to quantified exact carbon stock and forest emissions occurring due to specific land-use change. Therefore, through actual LiDAR, this research helps demarcate the pattern emitting different land-use measures, including deforestation, urban programs, agricultural differences, and forest and land changes, over historical change records and verified carbonization formulas. Similar qualitative levels between LiDAR and GIS analysis help determine the varying degrees of carbonization occurring due to enhanced deforestation, urban additions, and agricultural contributions while reporting the possible procedural carbons acquired during reforestation and other measurements. The results helped clarify that the most distinct level of land utilization shows the least level of carbon sent into the air. Therefore, the implication is that strategic land use measures and better working conditions can curb carbon indications. These signals support land-use policy and preparedness goals in a low carbon level. This study creates valuable records for the land utilization and cartograph, created through the power of LiDAR and GIS analysis.

  • The Use of Artificial Intelligence to Optimize the Routing of Vehicles and Reduce Traffic Congestion in Urban Areas

    Appears in:
    ew 23(1):

    Authors:
    Srishti Dikshit, Vinay Dwivedi, Aarushi Thusu, Mohammad Shahid, Areeba Atiq

    Downloads:
    786

    Abstract:
    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.

  • A Short Literature on Linear Programming Problem

    Appears in:
    ew 23(1):

    Authors:
    R. Kumar, Shubham Kumar Tripathi

    Downloads:
    740

    Abstract:
    Researchers and scientists have developed various approaches and methodologies over time to model and analyze different types of linear programming problems, such as assignment problems and parametric programming problems. This paper provides a critical review and classification of existing modelling approaches and solution methods related to linear programming problems. Moreover, the simplex method is discussed in detail through a comprehensive literature review. The paper concludes by presenting an integrated research framework that is directly applicable to the present context, along with suggestions for future research directions.

  • Platformization and the Metaverse: Opportunities and Challenges for Urban Sustainability and Economic Development

    Appears in:
    ew 23(1):

    Authors:
    Aram Mohammed-Amin Qadir, Ava Omar Fatah

    Downloads:
    633

    Abstract:
    In simpler terms, our day-to-day life, from various urban sectors to all deep corners of city life, is becoming hugely influenced by digital platforms' data systems, economic tactics, and ways of management. This is a trend that we call "platformization." It's taken us to a point where we now live in what's often described as a "platform society" because these platforms now largely control urban civilizations. What's fascinating is that this platformization trend has created something pretty striking: the Metaverse. The Metaverse is an impressive global platform project launched by Meta, the company we used to know as Facebook. This project brings to life a potential "virtual world" that mirrors our reality. The idea is that the Metaverse can serve as a virtual version of the future cities – not too different from what we think of as smart cities. Thanks to cutting-edge technologies like Artificial Intelligence, Big Data, Internet of Things (IoT), and Digital Twins, we now have enough resources and understanding of human behavior to make a project like the Metaverse possible. The promise is that the Metaverse can revolutionize how we design cities and deliver public services, making cities more efficient, accountable, and with a higher quality performance. But of course, the arrival of the Metaverse isn't without its worries. There are many questions over the ethical, human, social, and cultural implications the Metaverse may have. Particularly, there are concerns about the kind of impact it may have on the quality of human social relationships and how it may reshape urban life. To unpack all of these, this research work aims to thoroughly examine available literature on this topic. The paper further looks into the new products and services coming into being because of the Metaverse, examining how they might help smart cities, especially those aiming for better environment, economy, and social sustainability. The insights gathered here could help city leaders understand the Metaverse's potential for technology-driven urban practices and future city plans. It also takes a critical stance, challenging whether the Metaverse might significantly change how reality is constructed in our increasingly platform-driven urban world. This discussion, hopefully, can fuel future research and critical conversation on this hot topic.

  • Analysis of Artificial Intelligence Design Incorporated into Design of Street Space in Small Cities

    Appears in:
    ew 24(1):

    Authors:
    Lei Song

    Downloads:
    528

    Abstract:
    INTRODUCTION: At present, China's urbanization continues to develop, but the level of urban planning and design has not kept pace with the progress of development, especially the creation of street space in small cities, which is still not able to adapt to the current needs of people's cultural life. With the development of the economy and science and technology, artificial intelligence and other information technologies are constantly integrated into daily life. Therefore, utilizing artificial intelligence for street space design research is significant. OBJECTIVES: To improve the development level of artificial intelligence, information technology, and the application level of artificial intelligence in China; to solve the problem of the relatively low level of street space design in the current city, especially in small towns, to meet the needs of people's cultural life; to promote the improvement of the level of artificial intelligence in China for the convenience of civil life, and to further improve the level of street space design in China. METHODS: Firstly discusses the theories, such as the principles of street space design in small cities, to illustrate the necessity of integrating AI into street space design in small towns; secondly, the model established by AI is used to optimize the street space in small cities; finally, the feasibility of integrating AI design into street space design in small towns is illustrated through cases and examples. RESULTS: Street space design in small cities in China needs more design aesthetics, and artificial intelligence needs to be integrated into street space design. Artificial intelligence has a noticeable optimization effect on street space design, and using artificial intelligence can improve the design level of limited space. Also illustrates that artificial intelligence can be better integrated into the street space design of small cities through cases. CONCLUSION: In the context of the digital era, the street space design of small cities needs to apply artificial intelligence. In modernization-oriented urban construction, the street space design level of small towns should be further strengthened to improve the modernization level of cities.

  • The Advancement of Electronic Gadgets in 21st Century

    Appears in:
    ew 23(1):

    Authors:
    Divjot Singh, Radha R, Arjun Vishanth, Nirav Bhatt

    Downloads:
    511

    Abstract:
    The 21st Century was full of innovation when it came to the Tech Sector alone, be it the introduction of the Iphone, or the launch of the big conglomerates such as Facebook and Twitter. The 21st Century gave rise to the concepts of the Curved Displays on phones and the Foldable phones. There were numerous problems which were associated with the flat screen displays, and the shortcomings have been overcome by the Curved Displays and the Foldable phones as discussed in the paper. They have revolutionized the Technological market since their launch. Many Conglomerates such as Samsung, Honor, Xiaomi have invested millions of dollars in availing this new technology. However, currently Samsung has the lead over all its Chinese competitors, and with different companies investing in the new technology, the competition is predicted to become more intense. This will surely give customers a huge variety of phones to choose from. However, this technology did not come without its drawbacks. There were multiple issues associated with the Foldable Phones such as the weight associated with the phone when folded, the tensile strength of the Foldable phones is very low, and the User Interface is not something one could get excited about. Similar issues existed with Curved Displays as well, including costly repair costs, and it is harder to get a grip on compared to the Foldable phones due to the thinning of the edges. The paper discusses in depth the shortcomings of all the types of Phones, as well as which would be the best fit for the user, along with the current trend of the users, and what the Future holds for this segment of Technology.

  • Green Economic Policies, Strategies & Initiatives of India

    Appears in:
    ew 23(1):

    Authors:
    Ajit Singh, Monica

    Downloads:
    443

    Abstract:
    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.

  • State-of-the-art review on energy management systems, challenges and top trends of renewable energy based microgrids

    Appears in:
    ew 24(1):

    Authors:
    JinZhu Cui, Yefan Wu, Caiyan Liu

    Downloads:
    431

    Abstract:
    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.

  • Adaptive FPA Algorithm based OPF with Unified Power Flow Controller

    Appears in:
    ew 22(40): e4

    Authors:
    Nageswara Rao Atyam, Challa Babu, Immanuel A., Pavan Kumar Naidu R., Sudheer P.

    Downloads:
    424

    Abstract:
    In this work a novel modified flower pollination algorithm has been developed to solve the problem of single and multi-objective Optimal Power Flow operations for Unified power Flow Controller in Flexible Alternating Current Transmission Systems. In the proposed Adaptive Flower Pollination Algorithm the best initial solution can be chosen from the fittest and also the weights are adaptively adjusted to get better convergence characteristics. The nature of the objective functions is non-linear and difficult to get best possible solutions within the boundary conditions of total power demand. The weak nodes are determined in the system to locate the UPFC with Fuzzy approach considering input parameters as L-Index and voltage magnitudes. The projected method is validated using IEEE-30 and IEEE-57 bus systems for three objective functions, namely, system real power loss minimization, fuel cost minimization and the combination of total generating cost and system real power loss. Results of Fuzzy- Adaptive Flower Pollination Algorithm based OPF optimization for UPFC produced optimum results for the considered objectives of total fuel cost, real power loss and for the multiobjective.

  • Thermodynamic Simulation of Producer Gas Combustion from Biomass Gasification

    Appears in:
    ew 22(5): e1

    Authors:
    Fajri Vidian, Arif Rahman Hakim

    Downloads:
    420

    Abstract:
    The use of new and renewable energy for the application on gas burners is beneficial for the environment. This study aims to determine the effect of excess air during the combustion of producer gas from biomass gasification to release heat used as a fuel gas burner. Simulations are carried out by applying mass and energy balance, showing that an increase in excess air will decrease the non-adiabatic and adiabatic flame temperature. The result showed that an increase in excess of air reduces the amount of heat released to the environment for the same flame temperature. The maximum adiabatic flame temperature is at 1725.430C, while the non-adiabatic ranges from 600 to 8000C. Furthermore, heat is released in the range of 20.1 kW to 28.8 kW, and excess air from 0 to 40%. 

  • Seven Level Symmetric Cascaded H-Bridge Multilevel Inverter for Solar Photovoltaic System

    Appears in:
    ew 23(5): e3

    Authors:
    Dr. T. Padmavathi, C Dinakaran

    Downloads:
    411

    Abstract:
    Among different types of Non-Conventional Energy Sources, Solar Power has become highly prominent with exhausting suitable to innovation in Power Electronic Systems. The primary intention of the advised performance must limit the number of switches to enhance the output waveforms with a preferred harmonic profile. This topology moderates the estimate about switches, isolated DC origin, expenditure, and intensity of the circuit substantially as correlated to other topologies. The proposed method uses the MPPT approach to exploit the maximum energy from solar photovoltaic to load entirely. The Proposed method provides almost sinusoidal output waveforms by developing a few power switches. The SPV arrangement was simulated and constitution through SPV arrays, a DC-DC buck converter, and a sliding mode MPPT regulation. Based on the cascaded H-Bridge multilevel converters, The strong constraint enforced confined DC voltage sources considering separately Cascaded H-Bridge. This constitution converter worth along with diminishing the constancy based on the system. The system gives boosting voltages with improves the harmonic profile. Performance of the arrangement demonstrated in MATLAB SIMULINK as well as PROTEUS. 
Publisher
EAI
ISSN
2032-944X
Number of Volumes
12
Last Published
2024-11-04
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