Publications by Nahid Mohajeri Pour Rayeni

Using Machine Learning to estimate the technical potential of shallow ground-source heat pumps with thermal interference

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Alina Ursula Rosa Walch, Roberto Castello

The increasing use of ground-source heat pumps (GSHPs) for heating and cooling of buildings raises questions regarding the technical potential of GSHPs and their impact on the temperature in the shallow subsurface. In this paper, we develop a method using ...

IOP PUBLISHING LTD2021

Residential density classification for sustainable housing development using a machine learning approach

Nahid Mohajeri Pour Rayeni, Dan Assouline, Alina Ursula Rosa Walch

Using Machine Learning (ML) algorithms for classification of the existing residential neighbourhoods and their spatial characteristics (e.g. density) so as to provide plausible scenarios for designing future sustainable housing is a novel application. Here ...

IOP PUBLISHING LTD2021

Big data mining for the estimation of hourly rooftop photovoltaic potential and its uncertainty

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Alina Ursula Rosa Walch, Roberto Castello

The large-scale deployment of photovoltaics (PV) on building rooftops can play a significant role in the transition to a low-carbon energy system. To date, the lack of high-resolution building and environmental data and the large uncertainties related to e ...

2020

Quantifying the technical geothermal potential from shallow borehole heat exchangers at regional scale

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Alina Ursula Rosa Walch

The extraction of shallow geothermal energy using borehole heat exchangers (BHEs) is a promising approach for decarbonisation of the heating sector. However, a dense deployment of BHEs may lead to thermal interference between neighboring boreholes and ther ...

Pergamon-Elsevier Science Ltd2020

A solar-based sustainable urban design: The effects of city-scale street-canyon geometry on solar access in Geneva, Switzerland

Jean-Louis Scartezzini, Jérôme Henri Kämpf, Nahid Mohajeri Pour Rayeni, Dan Assouline

Buildings commonly have the largest share in the energy demand of a country, but they also offer sites for the generation of solar energy. Here we develop a methodology to analyse the effects of street-canyon geometries on the solar access of street surfac ...

2019

Machine learning and geographic information systems for large-scale wind energy potential estimation in rural areas

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Dasaraden Mauree, Dan Assouline

Clean, safe, affordable and available in the long-term, wind is one of the most promising sources of renewable energy. Its optimized and profitable use, however, requires an estimation of the potential in locations of interest, given its very volatile beha ...

IOP2019

A critical comparison of methods to estimate solar rooftop photovoltaic potential in Switzerland

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Alina Ursula Rosa Walch

To understand the opportunities and challenges of large shares of solar photovoltaics (PV) in our electricity mix, various large-scale studies of PV potential on building roofs have been conducted in recent years. The use of different datasets, methods and ...

2019

Integrating urban form and distributed energy systems: Assessment of sustainable development scenarios for a Swiss village to 2050

Jean-Louis Scartezzini, Silvia Coccolo, Amarasinghage Tharindu Dasun Perera, Lucas Mosca, Nahid Mohajeri Pour Rayeni, Morgane Le Guen

The integration of renewable energy in the built environment, improving the energy efficiency of buildings, and optimizing distributed energy systems are three interconnected activities that are central for the transition to sustainable cities. Here, a met ...

Pergamon-Elsevier Science Ltd2019

Spatio-temporal modelling and uncertainty estimation of hourly global solar irradiance using Extreme Learning Machines

Jean-Louis Scartezzini, Fabian Guignard, Nahid Mohajeri Pour Rayeni, Alina Ursula Rosa Walch, Roberto Castello

2019

A machine learning approach for mapping the very shallow theoretical geothermal potential

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Dan Assouline

The very shallow geothermal potential (vSGP) is increasingly recognized as a viable resource for providing clean thermal energy in urban and rural areas. This is primarily due to its reliability, low-cost installation, easy maintenance, and little constrai ...

2019

Urban greening archetypes at the European scale

Jean-Louis Scartezzini, Silvia Coccolo, Amarasinghage Tharindu Dasun Perera, Nahid Mohajeri Pour Rayeni, Dasaraden Mauree, Ismaël Krafess, Cynthia Houmani

Urban greening has great ecological, social and economic benefits for the built environment. It also has significant impacts on the microclimate and urban energy balance. In this study, we quantify the impacts of urban greening on the ground surface temper ...

IOP Science2019

Large-scale rooftop solar photovoltaic technical potential estimation using Random Forests

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Dan Assouline

2018

A city-scale roof shape classification using machine learning for solar energy applications

Jean-Louis Scartezzini, Bérénice Guiboud, Andreas Bill, Nahid Mohajeri Pour Rayeni, Dan Assouline

Solar energy deployment through PV installations in urban areas depends strongly on the shape, size, and orientation of available roofs. Here we use a machine learning approach, Support Vector Machine (SVM) classification, to classify 10,085 building roofs ...

Pergamon-Elsevier Science Ltd2018

Combining Fourier Analysis And Machine Learning To Estimate The Shallow-Ground Thermal Diffusivity In Switzerland

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Dan Assouline

We propose a methodology combining physical modelling and machine learning (ML) to estimate the apparent ground thermal diffusivity at the scale of a country. Based on ground temperature time series at different depths, we estimate the diffusivity at 49 Sw ...

IEEE2018

Improving the energy sustainability of a Swiss village through building renovation and renewable energy integration

Jean-Louis Scartezzini, Silvia Coccolo, Amarasinghage Tharindu Dasun Perera, Lucas Mosca, Nahid Mohajeri Pour Rayeni, Morgane Le Guen

The integration of renewable energy technologies and building renovation are the two main procedures for improving energy sustainability of buildings at neighborhood scale. It is difficult, however, to optimize these procedures simultaneously. This study f ...

Elsevier2018

Quantifying rooftop photovoltaic solar energy potential: A machine learning approach

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Dan Assouline

The need for reduction in CO2 emissions to mitigate global warming has resulted in increasing use of renewable energy sources. In urban areas, solar photovoltaic (PV) deployment on existing rooftops is one of the most viable sustainable energy resources. T ...

Pergamon-Elsevier Science Ltd2017

Extending building integrated photovoltaics (BiPV) using distributed energy hubs. A case study in Cartigny, Switzerland

Jean-Louis Scartezzini, Silvia Coccolo, Nour Mdeihli, Amarasinghage Tharindu Dasun Perera, Nahid Mohajeri Pour Rayeni

The integration of renewable energy technologies in the existing energy infrastructure plays a key role in improving the sustainability of cities. Due to the stochastic nature of some renewable energy sources, primarily wind and solar energy, direct integr ...

Elsevier2017

Achieving energy sustainability in future neighborhoods through building refurbishment and energy hub concept: a case study in Hemberg-Switzerland

Jean-Louis Scartezzini, Silvia Coccolo, Amarasinghage Tharindu Dasun Perera, Lucas Mosca, Nahid Mohajeri Pour Rayeni, Morgane Le Guen

This study aims to investigate the role of distributed generation through the energy hub concept and refurbishment of existing buildings. More specifically, a computational platform combining (i) the urban energy modelling tool CitySimPro and (ii) the micr ...

Elsevier2017

Effects of city size on the large-scale decentralised solar energy potential

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Dan Assouline

To assess the PV-potential on rooftops for decentralized electricity supply in Switzerland, the potential is compared with the following urban-size parameters: (a) urban population, (b) number of buildings, (c) the cumulative building ground-floor area, an ...

Elsevier2017

3D Model for Solar Energy Potential on Buildings from Urban LiDAR Data

Jean-Louis Scartezzini, Andreas Bill, Nahid Mohajeri Pour Rayeni

One of the most promising sustainable energy that can be considered in urban environment is solar energy. A 3D model for solar energy potential on building envelope based on urban LiDAR data was developed in this study. The developed algorithm can be used ...

The Eurographics Association 20162016