About this Research Topic
Solar energy systems are considered one of the most important solutions to the continuous increase of global energy demand and environmental concerns. However, the high cost and limited energy conversion are still challenging aspects that need further investigation. Moreover, the intermittent nature of solar energy requires the development of advanced techniques to minimize the investment, maximize the system performance and reliability, and minimize operation and maintenance cost.
This Research Topic aims to provide a platform to showcase the latest research and advancements on the application of optimization techniques, particularly from the operations research (OR) and artificial intelligence (AI) domains, in the realm of solar energy systems. Moreover, the investigation and optimization of various aspects in solar photovoltaic and solar thermal systems are essential to enhance their economic viability, operational efficiency, and environmental sustainability.
We invite researchers, experts, and practitioners from diverse disciplines to contribute original research, review articles, and case studies that explore the diverse aspects of optimization techniques to optimize solar energy systems. The goal is to facilitate knowledge exchange and foster advancements in this field, ultimately driving the transition towards more efficient and sustainable solar energy utilization.
The scope of this Research Topic includes, but is not limited to:
• Integration of optimization techniques in solar energy system design, encompassing aspects such as component selection, system configuration, and performance modelling.
• Maximize energy generation and minimize installation costs, optimal control strategies for energy storage in solar systems
• Economic and environmental optimization of solar energy systems: identify the most sustainable solutions for solar energy implementation, including the assessment of life cycle costs, carbon footprint analysis, and economic feasibility studies.
• Optimize the energy dispatchability, storage and distribution, and optimizing the cooling, cleaning, and tracking of photovoltaic systems
• The use of solar hybrid systems and the optimization of its overall efficiency
• Application of cutting-edge optimization algorithms, such as genetic algorithms, particle swarm optimization, and machine learning approaches, to enhance the performance and efficiency of solar energy systems.
This Research Topic aims to provide a platform to showcase the latest research and advancements on the application of optimization techniques, particularly from the operations research (OR) and artificial intelligence (AI) domains, in the realm of solar energy systems. Moreover, the investigation and optimization of various aspects in solar photovoltaic and solar thermal systems are essential to enhance their economic viability, operational efficiency, and environmental sustainability.
We invite researchers, experts, and practitioners from diverse disciplines to contribute original research, review articles, and case studies that explore the diverse aspects of optimization techniques to optimize solar energy systems. The goal is to facilitate knowledge exchange and foster advancements in this field, ultimately driving the transition towards more efficient and sustainable solar energy utilization.
The scope of this Research Topic includes, but is not limited to:
• Integration of optimization techniques in solar energy system design, encompassing aspects such as component selection, system configuration, and performance modelling.
• Maximize energy generation and minimize installation costs, optimal control strategies for energy storage in solar systems
• Economic and environmental optimization of solar energy systems: identify the most sustainable solutions for solar energy implementation, including the assessment of life cycle costs, carbon footprint analysis, and economic feasibility studies.
• Optimize the energy dispatchability, storage and distribution, and optimizing the cooling, cleaning, and tracking of photovoltaic systems
• The use of solar hybrid systems and the optimization of its overall efficiency
• Application of cutting-edge optimization algorithms, such as genetic algorithms, particle swarm optimization, and machine learning approaches, to enhance the performance and efficiency of solar energy systems.
Keywords: optimization, solar photovoltaic, solar thermal, solar hybrid systems, AI methods, techno-economic assessment, environmental effects
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
