Md Waseem Ahmad – författare

Discover comprehensive insights into the latest advancements in solar PV technology, including power electronics, maximum power point tracking schemes, and forecasting techniques, with a focus on improving the performance of PV systems.

A huge number of research articles and books have been published in the last two decades, covering different issues of PV efficiency, circuits, and systems for power processing and their related control. Books that have been published cover one or more topics but altogether fail to give a complete picture of the different aspects of PV systems. Photovoltaic Systems Technology aims to close the gap by providing a comprehensive review of techniques/practices that are dedicated to improving the performance of PV systems.

The book is divided into three parts: the first part is dedicated to advancements in power electronic converters for PV systems; tools and techniques for maximum power point tracking of PV systems will be covered in the second part of the book; and the third part covers advancements in techniques for solar PV forecasting. The overall focus of the book is to highlight the advancements in modeling, design, performance under faulty conditions, forecasting, and application of solar photovoltaic (PV) systems using metaheuristic, evolutionary computation, machine learning, and AI approaches. It is intended for researchers and engineers aspiring to learn about the latest advancements in solar PV technology with emphasis on power electronics involved, maximum power point tracking (MPPT) schemes, and forecasting techniques.

Discover comprehensive insights into the latest advancements in solar PV technology, including power electronics, maximum power point tracking schemes, and forecasting techniques, with a focus on improving the performance of PV systems.

A huge number of research articles and books have been published in the last two decades, covering different issues of PV efficiency, circuits, and systems for power processing and their related control. Books that have been published cover one or more topics but altogether fail to give a complete picture of the different aspects of PV systems. Photovoltaic Systems Technology aims to close the gap by providing a comprehensive review of techniques/practices that are dedicated to improving the performance of PV systems.

The book is divided into three parts: the first part is dedicated to advancements in power electronic converters for PV systems; tools and techniques for maximum power point tracking of PV systems will be covered in the second part of the book; and the third part covers advancements in techniques for solar PV forecasting. The overall focus of the book is to highlight the advancements in modeling, design, performance under faulty conditions, forecasting, and application of solar photovoltaic (PV) systems using metaheuristic, evolutionary computation, machine learning, and AI approaches. It is intended for researchers and engineers aspiring to learn about the latest advancements in solar PV technology with emphasis on power electronics involved, maximum power point tracking (MPPT) schemes, and forecasting techniques.

This book brings together state-of-the-art advances in intelligent data analytics as driver of the future evolution of PaE systems. In the modern power and energy (PaE) domain, the increasing penetration of renewable energy sources (RES) and the consequent empowerment of consumers as a central and active solution to deal with the generation and development variability are driving the PaE system towards a historic paradigm shift. The small-scale, diversity, and especially the number of new players involved in the PaE system potentiate a significant growth of generated data. Moreover, advances in communication (between IoT devices and M2M: machine to machine, man to machine, etc.) and digitalization hugely increased the volume of data that results from PaE components, installations, and systems operation. This data is becoming more and more important for PaE systems operation, maintenance, planning, and scheduling with relevant impact on all involved entities, from producers, consumer,s and aggregators to market and system operators. However, although the PaE community is fully aware of the intrinsic value of those data, the methods to deal with it still necessitate substantial enhancements, development and research. Intelligent data analytics is thereby playing a fundamental role in this domain, by enabling stakeholders to expand their decision-making method and achieve the awareness on the PaE environment. The editors also included demonstrated codes for presented problems for better understanding for beginners.