Modelling and controlling of integrated photovoltaic-module and converter systems for partial shading operation using artificial intelligence

The thesis has three main themes: analysis and optimal design of Cuk DC-DC converters; integration of Cuk DC-DC converters with photovoltaic (PV) modules to improve operation during partial shading; and an artificial intelligence model for the PV module, permitting an accurate maximum power point (MPP) tracking in the integrated system. The major contribution of the thesis is the control of an integrated photovoltaic module and DC-DC converter configuration for obtaining maximum power generation under non-uniform solar illumination. In place of bypass diodes, the proposed scheme embeds bidirectional Cuk DC-DC converters within the serially connected PV modules. A novel control scheme for the converters has been developed to adjust their duty ratios, enabling all the PV modules to operate at the MPPs corresponding to individual lighting conditions. A detailed analysis of a step-down Cuk converter has been carried out leading to four transfer functions of the converter in two modes, namely variable input - constant output voltage, and variable output - constant input voltage. The response to switch duty ratio variation is shown to exhibit a non-minimum phase feature. A novel scheme for selecting the circuit components is developed using the criteria of suppressing input current and output voltage ripple percentages at a steady state, and minimising the time integral of squared transient response errors. The designed converter has been tested in simulation and in practice, and has been shown to exhibit improved responses in both operating modes. A Neuro-Fuzzy network has been applied in modelling the characteristics of a PV module. Particle-Swarm-Optimisation (PSO) has been employed for the first time as the training algorithm, with which the tuning speed has been improved. The resulting model has optimum compactness and interpretability and can predict the MPPs of individual PV modules in real time. Experimental data have confirmed its improved accuracy. The tuned Neuro-Fuzzy model has been applied to a practical PV power generation system for MPP control. The results have shown an average error of 1.35% compared with the maximum extractable power of the panel used. The errors obtained, on average, are also about four times less than those using the genetic-algorithm-based model proposed in a previous research. All the techniques have been incorporated in a complete simulation system consisting of three PV panels, one boost and two bidirectional Cuk DC-DC converters. This has been compared under the same weather conditions as the conventional approach using bypass diodes. The results have shown that the new system can generate 32% more power

A POWER DISTRIBUTION SYSTEM BUILT FOR A VARIETY OF UNATTENDED ELECTRONICS

A power distribution system (PDS) delivers electrical power to a load safely and effectively in a pre-determined format. Here format refers to necessary voltages, current levels and time variation of either as required by the empowered system. This formatting is usually referred as "conditioning". The research reported in this dissertation presents a complete system focusing on low power energy harvesting, conditioning, storage and regulation. Energy harvesting is a process by which ambient energy present in the environment is captured and converted to electrical energy. In recent years, it has become a prominent research area in multiple disciplines. Several energy harvesting schemes have been exploited in the literature, including solar energy, mechanic energy, radio frequency (RF) energy, thermal energy, electromagnetic energy, biochemical energy, radioactive energy and so on. Different from the large scale energy generation, energy harvesting typically operates in milli-watts or even micro-watts power levels. Almost all energy harvesting schemes require stages of power conditioning and intermediate storage - batteries or capacitors that reservoir energy harvested from the environment. Most of the ambient energy fluctuates and is usually weak. The purpose of power conditioning is to adjust the format of the energy to be further used, and intermediate storage smoothes out the impact of the fluctuations on the power delivered to the load. This dissertation reports an end to end power distribution system that integrates different functional blocks including energy harvesting, power conditioning, energy storage, output regulation and system control. We studied and investigated different energy harvesting schemes and the dissertation places emphasis on radio frequency energy harvesting. This approach has proven to be a viable power source for low-power electronics. However, it is still challenging to obtain significant amounts of energy rapidly and efficiently from the ambient. Available RF power is usually very weak, leading to low voltage applied to the electronics. The power delivered to the PDS is hard to utilize or store. This dissertation presents a configuration including a wideband rectenna, a switched capacitor voltage boost converter and a thin film flexible battery cell that can be re-charged at an exceptionally low voltage. We demonstrate that the system is able to harvest energy from a commercially available hand-held communication device at an overall efficiency as high as 7.7 %. Besides the RF energy harvesting block, the whole PDS includes a solar energy harvesting block, a USB recharging block, a customer selection block, two battery arrays, a control block and an output block. The functions of each of the blocks have been tested and verified. The dissertation also studies and investigates several potential applications of this PDS. The applications we exploited include an ultra-low power tunable neural oscillator, wireless sensor networks (WSNs), medical prosthetics and small unmanned aerial vehicles (UAVs). We prove that it is viable to power these potential loads through energy harvesting from multiple sources

Energy Harvesting and Energy Storage Systems

This book discuss the recent developments in energy harvesting and energy storage systems. Sustainable development systems are based on three pillars: economic development, environmental stewardship, and social equity. One of the guiding principles for finding the balance between these pillars is to limit the use of non-renewable energy sources

Analysis, Design and implementation of Energy Harvesting Systems for Wireless Sensor Nodes.

Ph.DDOCTOR OF PHILOSOPH

IoT and Sensor Networks in Industry and Society

The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society

Renewable Energy

This book discusses renewable energy resources and systems as well as energy efficiency. It contains twenty-three chapters over six sections that address a multitude of renewable energy types, including solar and photovoltaic, biomass, hydroelectric, and geothermal. The information presented herein is a scientific contribution to energy and environmental regulations, quality and efficiency of energy services, energy supply security, energy market-based approaches, government interventions, and the spread of technological innovation

Industrial Applications: New Solutions for the New Era

This book reprints articles from the Special Issue "Industrial Applications: New Solutions for the New Age" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of twelve published articles. This special edition belongs to the "Mechatronic and Intelligent Machines" section