This study examines the electrical performance and management of hybrid solar street lighting systems with the objective of optimizing their operation for sustainable urban development. Hybrid solar streetlights, which integrate photovoltaic panels with additional power sources, offer resilience and reliability that are crucial for urban settings. A hybrid solar streetlamp was installed in a city in central Italy and monitored for over a year to analyze its electrical behavior and the illuminances obtainable under different boundary conditions and operational programs. The measured data permit the development of an optimization algorithm in a Python program for the optimal management of the solar streetlamp and the forecasting of the battery charging/discharging cycles, as well as the electricity taken from the grid. The simulation scenarios permit the development of a novel management algorithm that is capable of optimizing the battery usage with a minimal draw on the grid in order to achieve a state of near self-sufficiency for the solar streetlamp. The results demonstrate that tilted solar panels enhance energy production, while optimized LED power profiles and system management enhance efficiency. The study highlights the importance of maintaining the state of charge (SOC) of the battery above 20% to extend its lifetime and reduce replacement needs. Economic analysis indicates significant potential energy savings, emphasizing the necessity of system optimization for economic viability and environmental sustainability in urban lighting. Despite initial investment costs and challenges, adopting hybrid solar lighting in urban environments presents substantial benefits, paving the way for a more sustainable and energy-efficient urban future.
Applications of hybrid solar streetlamps: electrical performance measurements and development of algorithms for their optimal management / Belloni, Elisa; Lunghi, Leandro; Celli, Irene; Massaccesi, Andrea; Moscatiello, Cristina; Martirano, Luigi. - In: IEEE ACCESS. - ISSN 2169-3536. - 12:(2024), pp. 119602-119614. [10.1109/access.2024.3446969]
Applications of hybrid solar streetlamps: electrical performance measurements and development of algorithms for their optimal management
Belloni, Elisa;Massaccesi, Andrea;Moscatiello, Cristina;Martirano, Luigi
2024
Abstract
This study examines the electrical performance and management of hybrid solar street lighting systems with the objective of optimizing their operation for sustainable urban development. Hybrid solar streetlights, which integrate photovoltaic panels with additional power sources, offer resilience and reliability that are crucial for urban settings. A hybrid solar streetlamp was installed in a city in central Italy and monitored for over a year to analyze its electrical behavior and the illuminances obtainable under different boundary conditions and operational programs. The measured data permit the development of an optimization algorithm in a Python program for the optimal management of the solar streetlamp and the forecasting of the battery charging/discharging cycles, as well as the electricity taken from the grid. The simulation scenarios permit the development of a novel management algorithm that is capable of optimizing the battery usage with a minimal draw on the grid in order to achieve a state of near self-sufficiency for the solar streetlamp. The results demonstrate that tilted solar panels enhance energy production, while optimized LED power profiles and system management enhance efficiency. The study highlights the importance of maintaining the state of charge (SOC) of the battery above 20% to extend its lifetime and reduce replacement needs. Economic analysis indicates significant potential energy savings, emphasizing the necessity of system optimization for economic viability and environmental sustainability in urban lighting. Despite initial investment costs and challenges, adopting hybrid solar lighting in urban environments presents substantial benefits, paving the way for a more sustainable and energy-efficient urban future.File | Dimensione | Formato | |
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