Renewable Power for Sustainable Growth
Proceedings of ICRP 2024, Volume 2
- 2026
- Book
- Editors
- Hasmat Malik
- Sukumar Mishra
- Y.R. Sood
- Atif Iqbal
- Taha Selim Ustun
- Book Series
- Lecture Notes in Electrical Engineering
- Publisher
- Springer Nature Singapore
About this book
The proceedings is a collection of papers presented at International Conference on Renewal Power (ICRP 2024), held during 28 – 29 March 2024 in Maharaja Agrasen Institute of Technology, Delhi, India. The book covers different topics of renewal energy sources in modern power systems. The volume focusses on smart grid technologies and applications, renewable power systems including solar PV, solar thermal, wind, power generation, transmission and distribution, transportation electrification and automotive technologies, power electronics and applications in renewable power system, energy management and control system, energy storage in modern power system, active distribution network, artificial intelligence in renewable power systems, and cyber physical systems and internet of things in smart grid and renewable power.
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Table of Contents
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Frontmatter
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A Detailed Study for Power System Analysis in Transmission Substation (220/66 kV) Using ETAP
Aditya Mohan Vashistha, Neelam Kassarwani, Neelu Nagpal, Neelam SharmaThis chapter delves into a comprehensive analysis of a 220/66 kV transmission substation using ETAP software, focusing on load flow, short circuit, transient, and harmonic analyses. The study employs real data from a Delhi Transco Limited substation to evaluate the performance and reliability of the substation under various operational scenarios. Load flow analysis optimizes power flow and voltage profiles, while short circuit analysis ensures robust fault response. Transient analysis explores dynamic behavior during brief events, and harmonic analysis assesses distortion factors within the electrical waveform. The results highlight the substation's stability and efficiency, providing valuable insights for optimizing design and enhancing operational performance. This study fills a significant gap in the existing literature by offering a thorough examination of the substation's performance across various operational parameters, contributing to the field of power system engineering.AI Generated
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AbstractThrough the Electrical Transient Analyzer Program (ETAP) software, an in-depth load flow analysis of an operational substation belonging to Delhi Transco Ltd. has been conducted. Initially, a simulation model of this specific transmission 220/66 kV substation has been designed, in which each component is configured based on real-world data. Several simulation scenarios including short circuits, and transient conditions have been considered by replicating real power system operating conditions. A load flow analysis has been performed with the values of suitable parameters thoroughly observed and recorded. The assessment of the model is carried out by comparing simulation outcomes with actual substation data. Furthermore, for a comprehensive examination, frequency and harmonic analyses at different bus points have also been performed. Inference of the system behavior is drawn from simulation results. Finally, conclusions are drawn and prospects for further work are discussed. -
Recent Trends and Developments in Context of Fog Computing (FC)
Arun Kumar Pipersenia, Ananta Ojha, Ankita Agarwal, Rekha DhivraniThis chapter delves into the architecture and characteristics of fog computing, comparing it with cloud and edge computing. It explores the core technologies that underpin fog computing, including computing, communication, storage, naming, identification, resolution, and resource management. The text also highlights various applications of fog computing in healthcare, smart environments, vehicular systems, and IoT, demonstrating its versatility and potential. Furthermore, it addresses the challenges and unresolved issues in fog computing, such as security, privacy, control, management, and programming platforms, providing a comprehensive overview of the current state and future directions of this evolving technology.AI Generated
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AbstractThe Internet of Things (IoT) has facilitated extensive connectivity between widespread devices, leading to the development of large and diverse amounts of data, commonly referred to as data explosions. Cloud computing (CC) effectively handles the processing and storage of data, but it still faces issues including meeting real-time application requirements and dealing with limited network capacity. By extending cloud services to the network’s perimeter, fog computing (FC) introduces a novel concept. It results in improved mobility, security, and latency when computing, communication, and storage are set up in closer proximity to end-users. The present article presents the sequential paradigm of fog computing as an efficient alternative way to the computing paradigms of the cloud and perimeter. A thorough assessment of fundamental technologies ranging from computers, communication, and archiving is contained in this work. In addition, the paper proposes tangible examples that demonstrate the pragmatic application of these technologies underneath the industry arenas of automotive fog computing, augmented reality, and healthcare. By examining the intricacies of security and privacy, this work extends important conclusions that should inform future investigations pertaining to the on-going development of fog computing. -
Addressing Feasible Research Directions and Testing Aspects for Cloud-Based Systems: A Review for Energy Saving Aspect
Ravindra Kumar, Sri Prakash Pandey, Feon Jaison, Intekhab Alam, Asyraf AfthanorhanThis chapter delves into the critical aspects of software testing for cloud-based systems, emphasizing the need for verification and validation to ensure software accuracy and quality. It explores the challenges and advantages of cloud-based testing, including cost efficiency, standardized infrastructure, and enhanced communication. The text discusses various types of cloud testing, such as system integration, interoperability, performance/load, stress/recovery, and security testing. It also highlights the current status of cloud-based testing models, including techniques like Virtualization-Aware Automated Testing Service and Model-Based Testing Using Symbolic Execution. The chapter concludes by addressing the future scope of cloud-based testing, emphasizing the need for transparent pricing models and comprehensive service descriptions to fully harness the potential of Test-Support as a Service in cloud-based software.AI Generated
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AbstractCloud computing is a new way of accessing and using computing resources. It allows users to access and configure these resources without the usual difficulties of managing them easily and conveniently. The use of this approach goes against standard software licensing rules. Because of the increasing acceptance of services that are cloud-based, thorough testing needs to be done before consumer shipment. Reduced expenses, much greater flexibility, better collaboration, higher output, and—above all—a less time-to-market for key business software are merely some of the advantages of cloud-based testing. This chapter’s initial goals is to calculate the cost of cloud computing testing, clarify testing concepts, clarify between traditional and cloud testing techniques, and look at the various frameworks and models that are currently now accessible for cloud-based testing. This statement explores testing methods with Cloud settings, points out the benefit of creating automated test cases and provides options for those looking into the topic, giving useful knowledge about its development. -
Technological Advancements and Trends of Collaborative Robots (Cobots) in the Field of Manufacturing: A Summary
Sandeep Kumar Jain, Himansh Kumar, S. Adlin Jebakumari, Intekhab Alam, Asif BaltiThis chapter delves into the technological advancements and trends of collaborative robots, or cobots, in the manufacturing sector. It highlights the growing market share of cobots, projected to rise from 4% in 2018 to 33% by 2025, and their increasing market value. The text explores the unique features of cobots, such as their ability to work safely alongside humans, their flexibility, and their role in enhancing production efficiency. It also provides a detailed comparison of cobots with traditional industrial robots, emphasizing the advantages of cobots in terms of cost, space requirements, and adaptability. The chapter discusses various applications of cobots in manufacturing, including assembly, machine tending, pick and place, quality inspection, welding, palletizing, packaging, material handling, and logistics. It also examines the future trends of cobots, including the integration of AI, machine learning, and advanced sensor technologies. The conclusion summarizes the main findings and suggests areas for future research, such as the incorporation of cloud computing, 5G networks, and advanced analytics into cobot technology.AI Generated
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AbstractAs the name implies, Collaborative robots are machines that operate alongside humans in a specific workspace. Unlike regular robots, these engage in close human interaction rather than being housed in enclosed safety zones. Even if this is the case, suitable precautions are taken to ensure human safety when developing these robots. These robots are accustomed to changing with the times and receiving regular updates. They have the flexibility to complete difficult jobs. These qualities make them a valuable asset in the industrial industry. Cobots have been a part of the industry for several years now. Thus, this is the ideal moment to examine the different production uses of cobots. The paper begins with a brief introduction and a detailed literature review that was organized after examining 70 research papers and articles that came after the introduction. It draws a few crucial conclusions at the end. This paper explores the benefits and various uses of cobots in the industrial industry. It also emphasizes the future of cobots and how advantageous they will be in a technologically advanced environment. -
Internet of Things for Energy Saving: Present State of the Art, Applications, Protocols and Enabling Technologies
Trapty Agarwal, Gaurav Jha, Mohd. Saleem, Ramkumar Krishnamoorthy, Nuzhat FatemaThis chapter delves into the Internet of Things (IoT) and its potential for energy saving, covering the current state of the art, applications, protocols, and enabling technologies. It begins with an overview of IoT's architecture, highlighting a five-layer model that includes the Objects Layer, Object Abstraction Layer, Service Management Layer, Application Layer, and Business Layer. The chapter also explores the complete landscape of IoT usage by industries, with a focus on healthcare, manufacturing, and urban infrastructure. It discusses various enabling technologies such as RFID, edge computing, and cloud computing, and their roles in IoT. Furthermore, the chapter presents a projected market share of IoT applications by 2025, indicating significant growth in sectors like healthcare and manufacturing. The conclusion emphasizes the rapid growth of IoT and its potential to improve the quality of life through smart devices and M2M developments. This chapter provides a comprehensive understanding of IoT's components and its impact on various industries, making it an essential read for professionals seeking to stay ahead in this innovative field.AI Generated
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AbstractThe Internet of Things (IoT) is a collection of technological advancements that enable communication between the physical and the digital. It is crucial to understand what it is, its uses, rules, traditions, difficulties, and enabling advancements since it will have a significant impact on the globe. This study sheds light mostly on aforementioned IoT components in order to achieve this goal. IoT has several enabling advancements that may result in new implementations and strategies. As IoT may break down any wall across actual tangible and digital objects, there could be significant changes in how technology is used. Smart cities, building automation, smart transportation systems, and ongoing unemployment security are a few examples of IoT use cases. It develops fundamental leadership models continuously. This article provides an overview of IoT, including its architecture, component elements, metrics, problems or challenges, implementations, and rules. It includes IoT-compatible communication developments as well as differentiating proof techniques like radio frequency identification (RFID) and near field communication (NFC). Consideration is given to the relationship between IoT and other advancements like parallelization and analysis methods. Unique norms and technologies focused on management are also discussed. -
Blockchain Technology Employment Opportunity for Energy Management: A Critical Review
Megha Pandeya, Khushboo Sharma, Aishwary Awasthi, Feon Jaison, Mashhood HasanThis chapter delves into the transformative potential of blockchain technology in military operations, focusing on data integrity, security, and transparency. It explores how blockchain can address the limitations of centralized systems, such as single points of failure, and presents a new framework for Network Enabled Military Operations. The chapter highlights key characteristics of blockchain, including permanence, trustlessness, and information provenance, and discusses their relevance to military applications. Three detailed case studies illustrate the benefits of implementing blockchain in military logistics and ammunition management. The chapter concludes by emphasizing the need for further research and development to fully integrate blockchain technology into military operations, offering a vision for enhanced data prevalence, situational awareness, and decision-making in complex military environments.AI Generated
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AbstractMilitary operations supported by networks generate, transmit, collect, and analyse mission-critical data to give commanders at all levels superior decision-making capabilities to accomplish the goals. On the battlefield, a range of heterogeneous factors, including people and equipment, produce this data. In such a setting, it is crucial to guarantee the data’s high level of integrity, secrecy, and accessibility as well as its endurance in hostile situations. This paper is a definitive discourse on the applicability of blockchain technology to achieve authenticity and traceability of data to support military activities that are dependent on networked systems to facilitate the resiliency of the networks. It addresses principles of blockchain as well as their different variations. Besides, the article applies the Network-Enabled Model in Military Operations to model the situations in which network-enabled military endeavors are executed. Three case studies that are pertinent to the current situation have been used to assess the workable framework and architecture for integrating Block-chain technology to meet security needs. -
Blockchain Implementation in Smart Grids
Chetan Chaudhary, Manish Srivastava, Monika Abrol, Manju Bargavi, Mohammad Junaid KhanThis chapter delves into the transformative potential of blockchain technology in smart grids, focusing on its ability to enhance security, transparency, and efficiency. It explores the need for blockchain in smart grid systems, addressing challenges in power management, utility trading, privacy, and micro-grid management. The text provides a roadmap for integrating blockchain with smart grids, highlighting applications in security and privacy, intelligent energy management, microgrids, electric vehicles, and energy trading. It also discusses the benefits of smart contracts and the different types of blockchain systems, such as public, consortium, and private blockchains. The chapter concludes with a comparison of various blockchain-based solutions and their potential to optimize power distribution, demand-side management, and fair power pricing. Additionally, it touches on current privacy and security risks with smart grids and how blockchain can mitigate these issues. The chapter aims to serve as a fundamental guide for the advancement of blockchain-enabled smart grids, emphasizing the importance of interdisciplinary collaboration.AI Generated
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AbstractA surge in interest in blockchain technology in recent years has resulted in the creation of several applications based on the platform that use its fault tolerance, decentralization, transparency, and high security. However, there are issues with the block-chain technology itself, such as sluggish processing times and insufficient privacy protection. Therefore, in order to maximise the advantages of block-chain and minimise its disadvantages, it is imperative to do research on how to more effectively integrate block-chain with smart grids. This article investigates novel methods for integrating the developing block-chain technology along with smart grids. This study aims to address the need for integrating block-chain into various smart grid components, highlight the frameworks and methodologies used to do so, and highlight the issues with current solutions. We also provide in-depth comparative studies of block-chain-based solutions for smart grids from multiple aspects in order to shed light on how to connect block-chain and smart grids to perform various management tasks. Last but not least, we give a rundown of the on-going initiatives and projects that serve as examples of the present practice-side endeavour. -
Blockchain Technology in the Energy Sector: A Brief Technical Review
Ankita Agarwal, Satendra Singh, Rajesh Gupta, Ramkumar Krishnamoorthy, Mohammad Junaid KhanThis chapter delves into the transformative impact of blockchain technology on the energy sector, focusing on its ability to enhance grid management, promote sustainability, and facilitate peer-to-peer energy trading. It explores the role of blockchain in decentralizing energy systems, ensuring transparency, and enabling secure transactions. The text also examines the architecture of blockchain technology, its applications in various energy use cases, and the future prospects of this innovative technology. Additionally, it discusses the potential of blockchain to streamline energy trading, improve metering and billing processes, and support the integration of renewable energy sources. The chapter concludes by highlighting the need for further research and development to fully realize the potential of blockchain in the energy sector.AI Generated
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AbstractMany people from academia, governments, financial institutions, and energy sector have become very interested in distributed ledger technology, also referred to as blockchain technology. Many experts in various fields agree that it is capable of providing major benefits and encouraging creative ideas. The use of trustworthy, tamper-proof, and secure systems by blockchain, and integrated with smart contracts, makes it possible to develop modern business structures. First, this article explains the core elements of blockchain, such as its system structure and types of agreement, and then goes on to cover uses of blockchain in the energy area. We thoroughly analyze both the existing literature and real-world commercial applications to provide an accurate depiction of the current status of progress in this field. To our knowledge, this is one of the first scholarly books that thoroughly examine blockchain initiatives and their impact on the energy industry. This report examines over 140 blockchain research projects and uses their data to assess the potential and feasibility of blockchain in the energy industry. Additionally, the study offers a roadmap for start-up enterprises in this field. The study's conclusion discusses the challenges and market limitations that the technology must overcome to cope with the hype stage, show that it is commercially viable, and finally win over the general public. -
An Overview of Challenges of Implementation of Blockchain Technology in Various Applications of Energy Domain
M. S. Nidhya, Chetan Chaudhary, Kunal Sharma, Ratish Sharma, Noor Aina AmirahThis chapter delves into the transformative impact of blockchain technology across various sectors, highlighting its unique advantages such as decentralization, transparency, and security. It begins by examining the fundamental structure of blockchain, including its types, hash functions, nodes, and consensus protocols. The text then explores the practical applications of blockchain in diverse fields like energy, healthcare, IoT, and voting systems, discussing both the benefits and challenges associated with each. The article also provides a detailed analysis of blockchain's role in the manufacturing sector, including adoption rates and potential obstacles. Additionally, it compares the use of blockchain across different continents and industries, offering insights into its global impact. The conclusion emphasizes the revolutionary potential of blockchain technology, despite the challenges it faces, and suggests areas for future research and development.AI Generated
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AbstractBlockchain uses distributed technology to save and deal with data at different locations. Due to the data set’s easy accessibility for all users, it delivers a transparent and safe system thanks to its distributed structure. Bitcoin blockchain-based apps have gained popularity because to its reliability, toughness, and efficiency. As a result, the blockchain is made accessible to huge populations. The blockchain has a variety of downsides that vary depending on the application, despite being the technology of the future. This study evaluated the effectiveness of several block chains in various applications. This system’s benefits and drawbacks, which are compared carefully, are described as the “future technology.” -
High-Performance Incipient Fault Classification of Transformer with Modified Optimized Artificial Data Integration
Atul Jaysing Patil, Ram Naresh, R. K. Jarial, Hasmat Malik, Megharani Atul Patil, Arush Singh, Kiran KumarThis chapter explores the development and validation of a high-performance machine learning model for transformer incipient fault classification. The study focuses on the integration of a 4GM graphical algorithm with a KNN classifier, enhanced by artificial data generation techniques. Key topics include the identification of transformer faults based on dissolved gas analysis, the challenges of traditional diagnostic methods, and the advantages of machine learning approaches. The research demonstrates significant improvements in fault classification accuracy, particularly for partial discharges (PD), low-energy discharges (D1), and thermal faults (T1+T2). The study also compares the proposed method with existing approaches, showcasing its superior performance and efficiency. By addressing data imbalances and refining the artificial data generation process, the model achieves an overall accuracy of 85.35%, making it a valuable tool for proactive maintenance and transformer longevity.AI Generated
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AbstractThe incipient faults classification of transformers is crucial for preventing failures and ensuring reliable operation. This paper presents a machine learning (ML) model designed for transformer fault identification, integrating modified artificial data with a novel 4GM graphical algorithm. The study trains the KNN model on a 4GM-based dataset of 1022 transformers specifically for fault identification. The model’s performance is validated using the IEC TC 10 database, demonstrating effective accuracy in fault classification. Additionally, a modified Artificial Data Generation (ADG) technique is introduced to enhance the dataset, addressing data imbalances and improving model robustness. Initial integration of the ADG technique led to reduced accuracy, necessitating further adjustments. Through iterative modifications, the combination of the 4GM algorithm and the enhanced ADG technique resulted in improved accuracy and robustness. This research will help many researchers in this fields for further improvement of ML performance when data imbalance, low database problem occurred. -
A Summary of Recent Trends and Developments in Agricultural Sector Using Blockchain Technology: Exploring Affordable and Clean Energy
Garima Goswami, Jayashree M. Kudari, Awakash Mishra, Manish Vishnoi, Syed Hamid Hussain MadniThis chapter delves into the recent trends and developments in the agricultural sector driven by blockchain technology, focusing on affordable and clean energy solutions. It explores the fundamental principles, widely used platforms, and a range of applications of blockchain in agriculture. The text tackles obstacles and presents remedies, providing valuable perspectives for future advancements. It also examines the integration of blockchain with other emerging technologies and offers a practical demonstration of blockchain implementation. The chapter covers key roles of blockchain in agriculture, such as improving food safety, security, quality monitoring, traceability, data analysis, and cost-effective transactions. It also discusses the use of blockchain in supply chain management, smart farming, and food safety traceability. The text highlights the challenges and potential solutions for widespread adoption of blockchain in agriculture, including scalability, security, and privacy concerns. A case study on managing food supply chains post-COVID-19 is presented, showcasing the potential of blockchain to enhance data transparency, accountability, and develop sustainable solutions. The chapter concludes with a summary of key findings and potential directions for future research.AI Generated
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AbstractBlockchain technology is becoming increasingly important in agricultural applications, as it addresses several requirements such as improving transparency in food safety, implementing quality control based on the IoT, ensuring traceability of origin, and optimising contract exchanges. Ensuring an ideal balance between efficiency and integrity is critical in the intricate farm-to-fork pipeline that involves untrusted entities such as small-scale farmers, processors, logistics firms, and retailers. The study discusses the potential for blockchain in agriculture and looks closely at the important parts of its design, such as data organization, encryption methods, and various innovative solutions. Current agricultural Blockchain applications are classified and evaluated see, and it shows real use. The text reveals the widespread use of platforms and smart contracts, and demonstrates their application in agricultural development. The report discusses key barriers and examines current efforts and possible solutions. The enhanced post-COVID food supply chain is a prime example of how blockchain technology is significantly improving transparency and efficiency in agriculture. -
Utilizing Centrifugal Shift to Recognize Electric Failures in Stimulating Engines
Rishi Sikka, K. Suneetha, Ankita Agarwal, Ajay Kumar, Md Fahim AnsariThis chapter delves into the innovative use of centrifugal shift to recognize electrical failures in induction motors, a critical component in 90% of rotating equipment. The focus is on the detection of rotor and stator issues through the analysis of axial flux and the implementation of measuring coils. The text begins with a literature review, highlighting the prevalence and reliability of induction motors, and the importance of condition monitoring to prevent unplanned shutdowns. It then explores the functioning of motor coils and the types of rotors, providing a solid foundation for understanding the subsequent laboratory research. The laboratory research methodology involves the use of a specially constructed small power AC motor to model various fault conditions, including short circuits and rotor defects. The results of this research demonstrate the effectiveness of measuring coils in detecting faults, with a particular emphasis on the impact of duty ratio and the severity of rotor cage failures on the RMS voltage values. The chapter concludes with a discussion on the future scope of this diagnostic method, suggesting the integration of neural networks and other AI techniques to automate the testing process. This comprehensive approach makes the chapter a valuable resource for professionals seeking to enhance their understanding of motor fault detection and maintenance.AI Generated
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AbstractThe paper discusses the potential of detecting mechanical defects in inductive loads using a longitudinal current. Details for a malfunctioning rotor rat cage but a stator coil relatively brief are presented in the paper. The study of ailments derived from the Fourier Transform Fast of a voltage caused by an axial flux in a measuring coil is the foundation for identifying and diagnosing faults. Leveraging Solid works software, research investigation on a modest power inductor was carried out. -
Role of Quantum Computation (QC) in Addressing Computational Challenges of Electrical Systems: A Review
Satish Kumar Jangid, Shubhendra Pratap Singh, Haripriya, Kalyan Acharjya, Suhail HusainThis chapter delves into the role of quantum computing (QC) in tackling the computational challenges faced by electrical systems. It begins with a foundational overview of QC, explaining key concepts such as superposition, entanglement, and quantum algorithms. The text then explores the application of QC in power systems, highlighting recent advances and specific algorithms designed to address issues like grid analytics, contingency analysis, and state estimation. The chapter also discusses the potential of QC in optimizing power grids and managing decentralized assets. It concludes by examining the future scope of QC in the energy sector, including its potential to enhance battery development, weather forecasting, and customer analytics. The chapter provides a detailed summary of the current state and future directions of QC in power systems, making it a valuable resource for professionals looking to stay ahead in this rapidly evolving field.AI Generated
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AbstractThe basics of quantum computation (QC) originate in quantum mechanics (QM), which helps develop unusual methods for working on difficult computing problems. The potential of quantum computing in physics and computer science is clear, but its prospective role in the energy sector is half-explored and not well-studied yet. It is the main goal of this study to see if quantum computing can address the growing challenges faced by today’s power systems. It starts with an explanation of the origin and basic theories of quantum computing before going into its current applications. After that, the text shows where quantum computing can make a difference in solving complex problems in the power system. Some of the main subjects are calculating AC and DC power on the network, assessing reliability in case of outages, keeping track of grid conditions, modeling sudden voltage bursts, locating malfunctions quickly, choosing how much power to produce, and planning the layout of new power plants. To some extent, because of the technical limits of present-day quantum computers, quantum computing has the power to make a huge difference in how we manage power grids. Researches show that with the expected progress in quantum technology, running quantum computers can have a major impact on resolving large-scale energy problems in the real world soon. Besides pointing out what quantum computing is used for, this research also motivates more scientists to research and explore new possibilities in this field. -
A Detailed Overview of Optimal Approaches to Enhance the Applicability of Renewable Energy Systems
Dinesh Kumar Yadav, R. Raghavendra, Intekhab Alam, Devendra Kumar Doda, Tahir KhurshaidThis chapter delves into the critical need for sustainable energy solutions and the role of hybrid renewable energy systems in meeting global energy demands. It explores various optimization strategies, such as genetic algorithms, particle swarm optimization, and simulated annealing, to determine the optimal size of hybrid systems. The text also examines commercial software tools like HOMER for system design and evaluates the efficiency of different optimization methods. Additionally, it discusses promising future approaches like the Ant Colony Algorithm and Artificial Immune System Algorithm, providing insights into their potential applications. The chapter concludes with a comprehensive overview of the current state and future directions in optimizing hybrid renewable energy systems, highlighting the importance of these strategies in advancing sustainable energy solutions.AI Generated
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AbstractSince people are worried about the environment and energy costs, several governments have chosen to concentrate on renewable sources in their new energy strategies. Renewable energy sources are capable of being widely used and are environmentally sustainable. Examples of these are wind, solar, and hydro power. In comparison to standalone systems, hybrid systems provide a more affordable, sustainable, and stable power supply under various load demand situations by integrating these renewable energy sources with backup units. An essential element of these hybrid systems entails adjusting the dimensions of components to guarantee they satisfy load requirements while minimizing investment and operational expenses. Amid the extensive acceptance of renewable energy sources, several research have surfaced that concentrate on refining and determining the appropriate scale of hybrid renewable energy systems. This research conducts a thorough examination of current optimal sizing methods discussed in existing literature. The objective is to contribute significantly to the wider incorporation of renewable energy by improving economic feasibility and system suitability. -
Classification and Applications of Variants of Fuzzy Logic Models in Renewable Energy Systems: A Review
Beemkumar Nagappan, Savita, Kunal Sharma, Himansh Kumar, Shahdab MurshidThis chapter reviews the classification and applications of fuzzy logic models in renewable energy systems, focusing on their role in optimizing energy management and addressing the variability of renewable energy sources. It explores various fuzzy logic techniques, including fuzzy decision support systems, fuzzy data envelopment analysis, and fuzzy multicriteria decision-making models, and their integration with other methods like neural networks, genetic algorithms, and optimization techniques. The review highlights the use of fuzzy logic in solar, wind, and bioenergy systems, demonstrating its effectiveness in improving system performance, reducing emissions, and enhancing economic viability. Additionally, the chapter discusses the future scope of fuzzy logic in renewable energy research, emphasizing the need for integrated models that combine fuzzy logic with advanced optimization techniques for improved decision outcomes.AI Generated
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AbstractOver the past few years, people have been using more energy because of globalization and as many countries have moved from farm-based to industrial and knowledge-based economies. As a result of this change, there are greater demands for energy and emissions have gone up. Because of these issues, fuzzy logic, neural networks, and genetic algorithms are used more often to help with energy planning and policies, which promotes both economic growth and conservation of nature. This study looks in detail at how fuzzy logic plays a role in solar, wind, bioenergy, microgrids, and hybrids. Results discovered that fuzzy logic is most often used during site scouting, for renewable energy installations, finding the highest energy point, and optimizing several important factors. According to the review, fuzzy models are dependable and useful for finding effective, accurate outcomes in many renewable energy fields. -
An Exploratory Analysis of Current and Future Trends of Artificial Neural Network (ANN) Paradigms in Wind Energy Systems
Amandeep Gill, Shreshta Bandhu Rastogi, Beemkumar Nagappan, Savita, Tahir KhurshaidThis chapter delves into the transformative role of artificial neural networks (ANNs) in wind energy systems, focusing on their application in forecasting, design optimization, fault detection, and control optimization. It begins by highlighting the significance of wind energy as a sustainable resource and the need for enhancing the efficiency and reliability of wind energy systems (WES). The study explores how ANNs, with their ability to process large amounts of data and adapt to complex situations, are being used to address various challenges in the wind energy sector. It provides a detailed classification of ANN techniques according to their specific goals, with a particular emphasis on forecasting and prediction, fault detection and diagnosis (FDD), and design and control optimization. The chapter also discusses the use of ANNs in predicting wind speed and power, designing wind turbines and farms, and detecting faults in various components of wind turbines. It concludes by providing a statistical analysis of the literature, showing how ANN applications in wind turbines have advanced over the previous ten years and where they are now. This comprehensive overview offers valuable insights into the current and future trends of ANN paradigms in wind energy systems, making it an essential resource for professionals seeking to understand and leverage these advanced technologies.AI Generated
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AbstractWind energy is an important part of renewable energy. It requires complex wind energy conversion technologies and creative ways based on advanced analytics. This study provides a comprehensive analysis of artificial neural networks (ANNs) in wind energy systems, focusing on the most often used techniques in various applications. The research demonstrates that ANNs are effective substitutes for traditional methods, particularly in recent times. The methods are divided into four main application areas: optimal control, finding faults, examinations, optimized design, and modelling and predictions. A detailed analysis of every application area highlights the benefits and drawbacks of various ANN topologies, while a statistical research assesses the current state and potential trends in this sector. The study does a quantitative analysis of significant references, offering fresh statistical perspectives on the state of the field now and its potential futures. Furthermore, based on the conclusions of the literature analysis, the article concisely describes the primary challenges and technical shortcomings that occur while using ANNs in the context of wind turbines. A thorough table provides a concise summary of important references categorized by application categories and case studies, giving a consolidated viewpoint. -
Deployment of AI Algorithms and Sensors in Interface Development for Smart Homes: A Bibliographic Survey
Aasheesh Raizada, A. Prabhu, Vaishali Singh, Sandeep Gautam, Muhammad M. RoomiThis chapter delves into the deployment of AI algorithms and sensors in the development of smart home interfaces, focusing on their potential to improve the quality of life for the elderly and reduce healthcare costs. The text explores the tiered architecture of smart homes, which includes layers for data collection, processing, communication, and user interaction. It highlights the use of various sensors, such as passive infrared sensors and physiological sensors, to monitor activities and health indicators. The chapter also discusses different AI techniques like decision trees, fuzzy logic, and neural networks for data processing and activity recognition. Additionally, it addresses the challenges and future scope of smart home technologies, including privacy, security, and the integration of new residents and activities. Readers will gain insights into the current state of smart home technologies, their applications in healthcare, and the key technologies driving this field forward.AI Generated
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AbstractThe abstract outlines a comprehensive exploration of Smart Home (SH) technology, emphasizing its role in enhancing residents’ quality of life while ensuring privacy. However, to enrich the study’s relevance to the conference on renewable power, it is advisable for the authors to incorporate examples where renewable power sources and sensors are integrated into SH systems, leveraging AI algorithms for efficient energy management. By illustrating how AI-driven analytics can optimize energy consumption based on renewable sources and sensor data, the study can provide valuable insights into the intersection of SH technology and renewable energy, thereby contributing to advancements in sustainable living environments. Integrating such examples will not only enhance the study’s applicability to the conference theme but also showcase its potential impact on promoting renewable energy adoption within smart home ecosystems.
- Title
- Renewable Power for Sustainable Growth
- Editors
-
Hasmat Malik
Sukumar Mishra
Y.R. Sood
Atif Iqbal
Taha Selim Ustun
- Copyright Year
- 2026
- Publisher
- Springer Nature Singapore
- Electronic ISBN
- 978-981-9533-89-3
- Print ISBN
- 978-981-9533-88-6
- DOI
- https://doi.org/10.1007/978-981-95-3389-3
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