دانلود کتاب هوش محاسباتی و فناوری‌های هوشمند در سیستم‌های حرارتی خورشیدی، اصول و کاربردها

In the quest for sustainable energy solutions, solar thermal systems have emerged as a key technology, harnessing the sun’s power to provide heating, cooling, and electricity across various applications. However, the efficiency and optimization of these systems remain perennial challenges, necessitating innovative approaches to enhance their performance and integration into the broader energy ecosystem. It is within this context that Computational Intelligence and Smart Technologies in Solar Thermal Systems: Principles and Applications was conceived. The genesis of this book lies in the recognition of the transformative potential of artificial intelligence (AI) and machine learning (ML) in revolutionizing solar thermal technologies. As computational intelligence continues to evolve, its application in solar thermal systems offers unprecedented opportunities for optimization, predictive maintenance, and smart integration with global energy networks. This book aims to bridge the gap between the complex theoretical underpinnings of AI and ML and their practical applications in improving solar thermal energy systems. Our journey in compiling this work involved extensive research, collaboration with experts in the fields of renewable energy, AI, and ML, and a deep dive into both the technical and practical aspects of solar thermal systems. This book covers a broad spectrum of topics, from the basics of solar thermal energy and computational intelligence to sophisticated AI and ML algorithms tailored for system optimization and reliability within 14 chapters. Chapters 1 to 8 present the foundation stone of the book, showcasing the integration of AI and ML with solar thermal energy systems. Chapter 1 introduces the burgeoning field of smart solar thermal energy technologies. It explores diverse applications, from heating and power generation to industrial processes. The chapter emphasizes the integration of AI and IoT for enhanced efficiency and reliability. Future directions focus on advanced materials, intelligent control systems, and sustainable energy solutions, highlighting the transformative potential of these technologies. Chapter 2 reviews machine learning’s role in greenhouse-type solar dryers. It explores how ML optimizes drying processes, enhancing efficiency and product quality. The chapter details various ML models used for predicting drying kinetics, temperature, and humidity, offering insights into their practical applications and potential for advancing sustainable drying technologies. Chapter 3 explores how sensor data, remote monitoring, and automated control enhance drying efficiency and product quality. Real-time data on temperature, humidity, and airflow enables precise adjustments. This chapter highlights IoT’s potential to optimize solar drying processes, reducing energy consumption and ensuring consistent, high-quality dried products. Chapter 4 explores the development of a computer-based interface for online monitoring of solar dryer parameters. This system enables real-time data acquisition and analysis, crucial for optimizing drying processes. It details the hardware and software components, focusing on sensor integration and user-friendly interface design. The aim is to enhance efficiency and control in solar drying applications through precise, automated parameter tracking. Chapter 5 explores AIdriven solar power prediction, comparing support vector regression (SVR), artificial neural networks (ANN), and Random Forest Regression (RFR). It explores their methodologies, highlighting each model’s strengths and weaknesses in forecasting solar generation. Chapter 6 explores maximizing solar energy capture through a dual-axis tracking system. It explores optimization strategies, detailing the system’s design and functionality. Real-time monitoring enhances performance, ensuring optimal panel alignment with the sun. This chapter examines the system’s efficiency gains and practical applications, highlighting its role in advancing solar energy utilization. Chapter 7 details the optimized design and modeling of a 4kW hybrid solar EV charging station. It explores system architecture, component selection, and performance analysis. Utilizing simulation tools, it optimizes energy flow and efficiency. The chapter showcases the integration of solar PV and grid power, demonstrating a sustainable and reliable EV charging solution. Chapter 8 highlights the performance of a five-level inverter in solar photovoltaic systems. It analyzes the inverter’s efficiency, harmonic distortion, and switching behavior under varying solar irradiance and load conditions. The chapter presents experimental results and simulations, demonstrating the inverter’s suitability for grid-connected and standalone PV applications, highlighting its advantages in improving power quality and reducing losses. Chapter 9 explores the environmental impact of agrivoltaic systems in hot, arid climates. It evaluates performance through key metrics, analyzing how integrating solar panels with agriculture affects resource use, land efficiency, and ecosystem health. The chapter explores the balance between energy production and agricultural yield, assessing the sustainability of this dual-purpose land use in challenging environments. Chapter 10 explores the frontier of solar energy, exploring next-generation power plants. It examines technological advancements like tandem cells and AI-driven optimization, alongside challenges such as grid integration and material sustainability. Future aspects, including space-based solar and advanced storage, are discussed, outlining the path toward a more efficient and sustainable solarpowered future. In continuation, Chapter 11 explores the cutting-edge of solar cell technology, focusing on novel hybrid materials. It delves into the design and application of these materials, aiming to enhance efficiency and sustainability in next-generation solar cells. The chapter examines advancements in material science, highlighting their potential to revolutionize solar energy conversion and contribute to a greener future. Chapter 12 explores solar thermal collectors for decentralized cooking, a critical need in many regions. It reviews diverse designs, from simple box cookers to advanced concentrating systems, analyzing their efficiency and suitability. Implementation strategies, including material choices, local manufacturing, and user adoption, are discussed. This chapter highlights the potential of solar cooking to address energy poverty and promote sustainable living. Chapter 13 offers a comprehensive review of solar dryer advancements. It examines diverse designs, from traditional to cutting-edge technologies, emphasizing efficiency and application. This chapter analyzes performance metrics, material innovations, and integrated systems, highlighting the role of solar drying in sustainable agriculture and food preservation. It provides a critical overview of current trends and future directions in solar dryer technology. The conclusive Chapter 14 explores the promising future of wind-solar-hydrogen hybrid energy systems. It analyzes the integration of these renewable sources for stable, continuous power. The chapter delves into system design, efficiency, and economic viability, highlighting hydrogen’s role in energy storage. It assesses current technologies and future prospects, emphasizing the potential for sustainable, off-grid solutions and grid stabilization, paving the way for a cleaner energy landscape. The field of solar thermal energy is at an inflection point, with AI and ML poised to propel it into a new era of efficiency and sustainability. We hope that this book will catalyze further innovation and exploration, contributing to the global transition toward a more sustainable energy future.