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Dr Marina Bonomolo

Editorial Board Member

University of Palermo

Brief Bio

Marina Bonomolo was born in Palermo, Italy, in 1987. She received the Ph.D degree in Energy and information technologies with the Department of Engineering of the University of Palermo. She has co-authored books, papers on scientific journals, and conference proceedings. Her field of research is energy efficiency, HVAC systems, outdoor and indoor lighting, visual comfort, smart cities and smart buildings, day lighting performance and lighting control systems. She was involved in several research projects with the University of Palermo and with the Institute of High Performance and Networking (ICAR) of the National Research Council (CNR) in Palermo, Italy.

Research areas

Affiliations

Professor
University of Palermo
Viale delle Scienze Ed.9, Palermo 90128, Italia
Email: marina.bonomolo@deim.unipa.it
Tel: 3202223939

Publications

Assessing the electricity consumption of outdoor lighting systems in the presence of automatic control: The OL-BAC factors method
Journal: Sustainable Cities and Society
Published: 2020

A decentralized load control architecture for smart energy consumption in small islands
Journal: Sustainable Cities and Society
Published: 2020

Modeling of Light Pipes for the Optimal Disposition in Buildings
Journal: Energies
Published: 2019

Energy saving and user satisfaction for a new advanced public lighting system
Journal: Energy Conversion and Management
Published: 2019

Space syntax analysis applied to urban street lighting: Relations between spatial properties and lighting levels
Journal: Applied Sciences
Published: 2019

On the impact of safety requirements, energy prices and investment costs in street lighting refurbishment design
Journal: Energy
Published: 2019

A solar assisted seasonal borehole thermal energy system for a non-residential building in the Mediterranean area
Journal: Solar Energy
Published: 2018

Assessment of indoor illuminance and study on best photosensors' position for design and commissioning of Daylight Linked Control systems. A new method based on artificial neural networks
Journal: Energy
Published: 2017