A GIS tool for the calculation of solar irradiation on buildings at the urban scale, based on Italian standards

Pili, Stefano; Desogus, Giuseppe; Melis, Davide

doi:10.1016/j.enbuild.2017.10.027

Cited by 18 publications

(7 citation statements)

References 40 publications

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“…This calculation is essential to identify the urban heat island (UHI) effects [121], to assess building heating and cooling energy needs and to estimate techno-economic photovoltaic (PV) potential [122]. In addition, GIS based techniques can be used to examine the spatial variability of solar energy radiation [112,123,124]. The solar radiation analysis methods using GIS can be categorised according to the kind of data employed.…”

Section: Estimating Solar Radiation Using Gismentioning

confidence: 99%

Energy Consumption and Spatial Assessment of Renewable Energy Penetration and Building Energy Efficiency in Malaysia: A Review

et al. 2021

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The development of sustainable energy systems is very important to addressing the economic, environmental, and social pressures of the energy sector. Globally, buildings consume up to 40% of the world’s total energy. By 2030, it is expected to increase to 50%. Therefore, the world is facing a great challenge to overcome these problems related to global energy production. Malaysia is one of the top consumers of primary energy in Asia. In 2018, primary energy consumption for Malaysia was 3.79 quadrillion btu at an average annual rate of 4.58%. In this paper, we have carried out a detailed literature review on several previous studies of energy consumption in the world, especially in Malaysia, and how geographical information system (GIS) methods have been used for the spatial assessment of energy efficiency. Indeed, strategies of energy efficiency are essential in energy policy that could be created using various approaches used for energy savings in buildings. The findings of this review reveal that, for estimating energy consumption, exploring renewable energy sources, and investigating solar radiation, several geographic information system techniques such as multiple criteria decision analysis (MCDA), machine learning (ML), and deep learning (DL) are mainly utilized. The result indicates that the fuzzy DS method can more reliably determine the optimal PV farm locations. The 3D models are also regarded as an effective tool for estimating solar radiation, since this method generates a 3D model exportable to software tools. In addition, GIS and 3D can contribute to several purposes, such as sunlight access to buildings in urban areas, city growth prediction models and analysis of the habitability of public places.

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Section: Estimating Solar Radiation Using Gismentioning

confidence: 99%

Energy Consumption and Spatial Assessment of Renewable Energy Penetration and Building Energy Efficiency in Malaysia: A Review

et al. 2021

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“…Others have investigated the use of LiDAR data combined with aerial imagery to automatically generate building models; Secord explored the use of LiDAR data and the use of DEMs obtained from LiDAR data and their corresponding image information for feature extraction. Pili S investigated a multiscale theory for extracting buildings from LiDAR and image data [7][8][9]. Mutani G proposed a feature classi cation method for the fusion of LiDAR and aerial optical images [10,11].…”

Section: Introductionmentioning

confidence: 99%

Urban Llandscape Design and Maintenance Management Based on Multisource Big Data Fusion

Zhang

2022

Mathematical Problems in Engineering

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Data modeling based on the fusion of data from multiple sources can improve modeling accuracy compared to a single data source. A new modular information fusion model based on genetic neural networks is designed for the urban landscape design process. A digital elevation model is created using an ordered sequence of numbers based on preprocessed sensor images. A 3D orthophoto is then obtained to generate a 3D landscape using an artificial parallax-assisted mechanism. The scale and resources of the regional landscape are described by the three-dimensional geometric dimension after data processing, and a modular landscape model with a clear subject is constructed. Finally, a genetic algorithm based on real number coding optimizes the initial weights of the neural network and selects suitable learning factors to train the neural network to complete the data fusion task and error analysis. The maintenance situation is analyzed by introducing a multifactor landscape maintenance evaluation method. The simulation results show that the fusion process of the above model is stable and the energy consumption of information fusion is low, which can promote the efficient construction of the landscape and has important application value for improving the landscape design and maintenance management.

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“…Segundo Lopes (2013), a existência de fontes de sombreamento, como árvores e edifícios, pode provocar uma redução na produção de energia e, com isso, elevar o custo financeiro e retardar o retorno do investimento da unidade de microgeração. Diversos trabalhos já avaliaram o potencial da energia solar na malha urbana sob diferentes óticas, desde indicadores morfológicos (MOHAJERI et al, 2016;MORGANTI et al, 2017) à verificação do potencial pela integração com modelos 3D (KANTERS et al, 2012;MACHETE et al, 2018;PILI et al, 2018). A análise da energia solar na escala urbana pode ser realizada por ferramentas especializadas, como, por exemplo, os softwares Radiance, DIVA, CitySim, SUNtool (MORGANTI et al, 2017), ou mesmo extensões que podem ser utilizadas em conjunto a outros softwares, como as extensões Solar Energy Analysis, disponível para o SketchUp, e Insight Solar Analysis, disponível para o Revit, da Autodesk.…”

Section: Introductionunclassified

Análise do potencial da utilização de energia solar em Cuiabá/MT

Magalhães

Santos

Luz

et al. 2019

RICA

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A capital de Mato Grosso, Cuiabá, assim como o restante do estado, apresenta condições climáticas intensas ao longo do ano. Cidade de clima quente e com céu predominantemente ensolarado durante todo o ano, Cuiabá possui grande potencial para a implantação de energia solar fotovoltaica, apesar de não estar localizada na área do Brasil que recebe maior radiação. Este estudo tem como objetivo analisar este potencial, tendo em vista a importância do aproveitamento de energias renováveis no cenário atual e do aumento da demanda por energia elétrica no Brasil. A análise foi feita por meio dos dados de irradiação provenientes do software SunData, tanto no plano horizontal, quanto no plano inclinado ideal para a geração de energia, e a partir deles foi calculado o fator de capacidade de duas placas solares para a irradiação incidente na área urbana de Cuiabá/MT. Além disso, foi realizada uma análise do potencial na escala local a partir de modelagem 3D gerada pelo software Autodesk Revit em conjunto com o plugin Insight Analysis.

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A GIS tool for the calculation of solar irradiation on buildings at the urban scale, based on Italian standards

Cited by 18 publications

References 40 publications

Energy Consumption and Spatial Assessment of Renewable Energy Penetration and Building Energy Efficiency in Malaysia: A Review

Energy Consumption and Spatial Assessment of Renewable Energy Penetration and Building Energy Efficiency in Malaysia: A Review

Urban Llandscape Design and Maintenance Management Based on Multisource Big Data Fusion

Análise do potencial da utilização de energia solar em Cuiabá/MT

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