Prospecting urban rooftop solar farm potential in Dublin, Ireland

2021 ◽  
Author(s):  
Ankit Verma ◽  
John Connolly ◽  
Noel O'Connor
Keyword(s):  
Renewable Energy ◽  
High Resolution ◽  
Solar Energy ◽  
Urban Areas ◽  
Renewable Energy Sources ◽  
Solar Irradiation ◽  
Industrial Building ◽  
Surface Model ◽  
Very High ◽  
Rooftop Solar

<p>The development of a sustainable and renewable energy system is a significant challenge for Ireland. In line with UN and EU policies, Ireland aims to transition to a competitive, low carbon, climate-resilient and environmentally sustainable economy by 2050 (Project Ireland 2040 National Planning Framework). Ireland is committed to an aggregate reduction in CO<sub>2</sub> emissions of at least 80% (compared to 1990 levels) by 2050 across the electricity generation, built environment and transport sectors. Renewable energy can help Ireland reduce GHG emissions and carbon footprint as energy demands grow. It also reduces dependencies on fossil fuels as well as increases energy supply security.</p><p>According to the Sustainable Energy Authority of Ireland’s “Energy in Ireland 2020” report, 36.5% of electricity demand was met by renewable energy sources in 2019. Wind energy contributes 32% while solar energy contributes to <1%. Significant investment has been made in Ireland’s wind sector; however, the solar energy sector is relatively new. Ireland has the second-lowest total installed and cumulated solar photovoltaic (PV) capacity in the EU with just 36 MW or 7.3 W per inhabitant. (EurObserv'ER 2019).</p><p>Solar prospecting is necessary to identify optimum locations where solar farms can be established. Commercial and industrial building rooftops in urban areas offer a suitable location for establishing rooftop solar farms due to good connectivity with the electricity grid and proximity to users. Here we present an urban solar prospecting study in Dublin, Ireland.</p><p>A very high-resolution geospatial dataset was acquired for 47 industrial areas covering 53.3 km<sup>2</sup>. The data comprises of very high-resolution aerial images (12.5 cm/pixel) and digital surface model (DSM) (25 cm/pixel).</p><p>The high-resolution DSMs were used to model solar irradiation on building rooftops in ArcGIS Pro using the area solar analyst tool. These models were optimised for Irish conditions using Met Éireann solar radiation data for Dublin. The maximum solar insolation received in Dublin is 1000-1050 kWh/m<sup>2</sup>. The results demonstrate that there is potentially a large amount of commercial and industrial rooftop surface area available for PV installation in Dublin. These rooftops can generate a significant amount of electricity and help to offset CO<sub>2</sub> emissions.</p><p> </p>

scholarly journals GEOSPATIAL ASSESSMENT FOR PLANNING A SMART ENERGY CITY USING ROOFTOP SOLAR PHOTOVOLTAIC IN BANDUNG CITY, INDONESIA

2021 ◽  
Vol XLIV-M-3-2021 ◽  
pp. 83-87
Author(s):  
K. T. N. Ihsan ◽  
A. D. Sakti ◽  
K. Wikantika
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Urban Areas ◽  
Power Plants ◽  
Solar Power ◽  
Solar Pv ◽  
Energy Needs ◽  
The World ◽  
The City ◽  
Rooftop Solar

Abstract. Increasing the production of clean and environmentally friendly energy has become one of the world agendas as a strategic effort in dealing with long-term climate change. Seeing the potential of the energy produced, the ease in the installation process, with the small risk of harm generated, solar energy has received significant attention from many countries in the world. The potential for solar energy in Indonesia alone reaches 207 GWp, but only 145.81 MWp has been utilized. Currently, the Indonesian government has set a target to build a Solar Power Plant capacity in 2025 of 6.5 GWh. Urban areas are areas with higher energy demand than rural areas, but the availability of vacant land in urban areas is very minimal for installing solar power plants. Therefore, rooftop solar PV(Photovoltaic) can be a solution in dense areas such as cities. Good planning by looking at the potential resources and energy needs in spatial is needed to manage and utilize energy optimally and sustainably in urban areas. This study aims to develop a geospatial assessment for plan smart energy city that uses rooftop solar PV's potential energy in every building that is effective and efficient. The novelty in the analysis of the distribution of the potential for rooftop solar PV development in urban areas integrates meteorological and spatial aspects and socio-economic aspects. Integration of multi-dynamic spatial data uses in determining the rooftop solar PV construction location, such as meteorological data for solar energy potential, increasing energy needs of each building, and socio-economy data. The data source used comes from statistical data and remote sensing data. The analysis will be carried out temporally (2008, 2013, and 2018) to see the pattern of changes in aspects used in a certain period so that the development plan can be carried out more optimally. This research's output is the formation of a priority analysis of solar PV rooftop construction in urban areas, especially the city of Bandung. The result of energy can also produce by the construction of rooftop solar PV in a potential area. This research is expected to be utilized by policymakers to develop renewable energy in the city of Bandung and increase community participation in switching to renewable energy.

scholarly journals A Study on the Application of Solar Panel Technology in Low-Income Residential Housing in Deli Serdang Regency

2021 ◽  
Vol 5 (3) ◽  
pp. 398-411
Author(s):  
Dicky Andrea Sembiring ◽  
Ahmad Mansuri ◽  
Ferry Rahmat Astianta Bukit ◽  
Malinda Sari Sembiring
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Low Income ◽  
Energy Requirement ◽  
Renewable Energy Sources ◽  
Electrical Energy ◽  
Subsidized Housing ◽  
Solar Irradiation ◽  
Total Energy Consumption ◽  
Fossil Energy

The need for energy use, especially electrical energy continues to increase from year to year. One of the sectors that consume the largest electrical energy is the household sector which consumes about 27% of the total energy consumption of all sectors. The main energy source in Indonesia at this time still comes from fossil energy, although the government has tried to develop various renewable energy sources for the future. Solar energy is one of the renewable energies that is quite potential for Indonesia considering the level of solar radiation in Indonesia is quite high throughout the year. The selection of subsidized housing as the object of research is due to the existence of clear regulations and the number which also continues to increase every year. Through the collection of physical data on the research location, such as analysis of shadows, roof structure, solar irradiation data, average electric power usage, the average solar energy requirement of the subsidized housing will be obtained. Furthermore, by calculating the economic value, it will be obtained how the description of the possibility of applying solar energy to subsidized housing will be obtained. If possible, the application of solar energy in subsidized housing can help government programs to use renewable energy and reduce the use of fossil energy

scholarly journals 3D-information fusion from very high resolution satellite sensors

2015 ◽  
Vol XL-7/W3 ◽  
pp. 651-656 ◽  
Author(s):  
T. Krauss ◽  
P. d'Angelo ◽  
G. Kuschk ◽  
J. Tian ◽  
T. Partovi
Keyword(s):  
High Resolution ◽  
Change Detection ◽  
Information Fusion ◽  
Renewable Energy Sources ◽  
Open Pit ◽  
Open Pit Mining ◽  
Surface Model ◽  
Digital Terrain ◽  
3D Information ◽  
Very High

In this paper we show the pre-processing and potential for environmental applications of very high resolution (VHR) satellite stereo imagery like these from WorldView-2 or Pl´eiades with ground sampling distances (GSD) of half a metre to a metre. To process such data first a dense digital surface model (DSM) has to be generated. Afterwards from this a digital terrain model (DTM) representing the ground and a so called normalized digital elevation model (nDEM) representing off-ground objects are derived. Combining these elevation based data with a spectral classification allows detection and extraction of objects from the satellite scenes. Beside the object extraction also the DSM and DTM can directly be used for simulation and monitoring of environmental issues. Examples are the simulation of floodings, building-volume and people estimation, simulation of noise from roads, wave-propagation for cellphones, wind and light for estimating renewable energy sources, 3D change detection, earthquake preparedness and crisis relief, urban development and sprawl of informal settlements and much more. Also outside of urban areas volume information brings literally a new dimension to earth oberservation tasks like the volume estimations of forests and illegal logging, volume of (illegal) open pit mining activities, estimation of flooding or tsunami risks, dike planning, etc. In this paper we present the preprocessing from the original level-1 satellite data to digital surface models (DSMs), corresponding VHR ortho images and derived digital terrain models (DTMs). From these components we present how a monitoring and decision fusion based 3D change detection can be realized by using different acquisitions. The results are analyzed and assessed to derive quality parameters for the presented method. Finally the usability of 3D information fusion from VHR satellite imagery is discussed and evaluated.

scholarly journals Three-dimensional urban solar potential maps: Case study of the i-Scope Project

2018 ◽  
Vol 22 (1 Part B) ◽  
pp. 663-673 ◽  
Author(s):  
Dragutin Protic ◽  
Milan Kilibarda ◽  
Marina Nenkovic-Riznic ◽  
Ivan Nestorov
Keyword(s):  
Solar Energy ◽  
Urban Areas ◽  
Three Dimensional ◽  
Urban Environments ◽  
Solar Irradiation ◽  
Surface Model ◽  
Digital Surface Model ◽  
Information Models ◽  
Scope Project

Solar maps as web cartographic products that provide information on solar potential of surfaces on the Earth have been exploited in decision making, awareness raising, and promoting the use of solar energy. Web based solar maps of cities have become popular services as the use of solar energy is especially attractive in urban environments. The article discusses the concept and aspects of urban solar potential maps on the example of the i-Scope project as a case study. The i-Scope roof solar potential service built on 3-D urban information models was piloted in eight European cities. To obtain precise data on solar irradiation, a good quality digital surface model is required. A cost efficient innovative method for generation of digital surface model from stereophotogrammetry for urban areas where no advanced source data (e. g. LiDAR) exist is developed. The method works for flat, shed and gable roofs and provides sufficient accuracy of digital surface model .

Model Statistika Prediksi Energi Surya Dengan Menggunakan Autoregresif Integrated Moving Average (ARIMA)

Jurnal MIPA ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 181
Author(s):  
Imriani Moroki ◽  
Alfrets Septy Wauran
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Moving Average ◽  
Arima Model ◽  
Solar Irradiation ◽  
Energy Sources ◽  
Energy Potential ◽  
Good Design ◽  
Potential Sources ◽  
The Common

Energi terbarukan adalah salah satu masalah energi paling terkenal saat ini. Ada beberapa sumber potensial energi terbarukan. Salah satu energi terbarukan yang umum dan sederhana adalah energi matahari. Masalah besar ketersediaan energi saat ini adalah terbatasnya sumber energi konvensional seperti bahan bakar. Ini semua sumber energi memiliki banyak masalah karena memiliki jumlah energi yang terbatas. Penting untuk membuat model dan analisis berdasarkan ketersediaan sumber energi. Energi matahari adalah energi terbarukan yang paling disukai di negara-negara khatulistiwa saat ini. Tergantung pada produksi energi surya di daerah tertentu untuk memiliki desain dan analisis energi matahari yang baik. Untuk memiliki analisis yang baik tentang itu, dalam makalah ini kami membuat model prediksi energi surya berdasarkan data iradiasi matahari. Kami membuat model energi surya dan angin dengan menggunakan Metode Autoregresif Integrated Moving Average (ARIMA). Model ini diimplementasikan oleh R Studio yang kuat dari statistik. Sebagai hasil akhir, kami mendapatkan model statistik solar yang dibandingkan dengan data aktualRenewable energy is one of the most fomous issues of energy today. There are some renewable energy potential sources. One of the common n simple renewable energy is solar energy. The big problem of the availability of energy today is the limeted sources of conventional enery like fuel. This all energy sources have a lot of problem because it has a limited number of energy. It is important to make a model and analysis based on the availability of the energy sources. Solar energy is the most prefered renewable energy in equator countries today. It depends on the production of solar energy in certain area to have a good design and analysis of  the solar energy. To have a good analysis of it, in this paper we make a prediction model of solar energy based on the data of solar irradiation. We make the solar and wind enery model by using Autoregresif Integrated Moving Average (ARIMA) Method. This model is implemented by R Studio that is a powerfull of statistical. As the final result, we got the statistical model of solar comparing with the actual data

scholarly journals Lighting System Modernization as a Source of Green Energy

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2771
Author(s):  
Leszek Kotulski ◽  
Artur Basiura ◽  
Igor Wojnicki ◽  
Sebastian Siuchta
Keyword(s):  
Renewable Energy ◽  
Urban Areas ◽  
Large Scale ◽  
Energy Savings ◽  
Renewable Energy Sources ◽  
Green Energy ◽  
Light Sources ◽  
Levelized Cost Of Electricity ◽  
Cost Of Electricity ◽  
Lighting Retrofit

The use of formal methods and artificial intelligence has made it possible to automatically design outdoor lighting. Quick design for large cities, in a matter of hours instead of weeks, and analysis of various optimization criteria enables to save energy and tune profit stream from lighting retrofit. Since outdoor lighting is of a large scale, having luminaires on every street in urban areas, and since it needs to be retrofitted every 10 to 15 years, choosing proper parameters and light sources leads to significant energy savings. This paper presents the concept and calculations of Levelized Cost of Electricity for outdoor lighting retrofit. It is understood as cost of energy savings, it is in the range from 23.06 to 54.64 EUR/MWh, based on real-world cases. This makes street and road lighting modernization process the best green “energy source” if compared with the 2018 Fraunhofer Institute cost of electricity renewable energy technologies ranking. This indicates that investment in lighting retrofit is more economically and ecologically viable than investment in new renewable energy sources.

scholarly journals Legitimating power: Solar energy rollout, sustainability metrics and transition politics

2021 ◽  
pp. 251484862110249
Author(s):  
Siddharth Sareen
Keyword(s):  
Solar Energy ◽  
Political Ecology ◽  
Global Climate ◽  
Renewable Energy Sources ◽  
Energy Transition ◽  
Analytical Framework ◽  
Solar Irradiation ◽  
Low Carbon ◽  
Sustainability Metrics ◽  
Energy Transitions

Increasing recognition of the irrefutable urgency to address the global climate challenge is driving mitigation efforts to decarbonise. Countries are setting targets, technological innovation is making renewable energy sources competitive and fossil fuel actors are leveraging their incumbent privilege and political reach to modulate energy transitions. As techno-economic competitiveness is rapidly reconfigured in favour of sources such as solar energy, governance puzzles dominate the research frontier. Who makes key decisions about decarbonisation based on what metrics, and how are consequent benefits and burdens allocated? This article takes its point of departure in ambitious sustainability metrics for solar rollout that Portugal embraced in the late 2010s. This southwestern European country leads on hydro and wind power, and recently emerged from austerity politics after the 2008–2015 recession. Despite Europe’s best solar irradiation, its big solar push only kicked off in late 2018. In explaining how this arose and unfolded until mid-2020 and why, the article investigates what key issues ambitious rapid decarbonisation plans must address to enhance social equity. It combines attention to accountability and legitimacy to offer an analytical framework geared at generating actionable knowledge to advance an accountable energy transition. Drawing on empirical study of the contingencies that determine the implementation of sustainability metrics, the article traces how discrete acts legitimate specific trajectories of territorialisation by solar photovoltaics through discursive, bureaucratic, technocratic and financial practices. Combining empirics and perspectives from political ecology and energy geographies, it probes the politics of just energy transitions to more low-carbon and equitable societal futures.

scholarly journals Characterizing the Spatial and Temporal Availability of Very High Resolution Satellite Imagery in Google Earth and Microsoft Bing Maps as a Source of Reference Data

Land ◽  
2018 ◽  
Vol 7 (4) ◽  
pp. 118 ◽  
Author(s):  
Myroslava Lesiv ◽  
Linda See ◽  
Juan Laso Bayas ◽  
Tobias Sturn ◽  
Dmitry Schepaschenko ◽  
...  
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Reference Data ◽  
Temporal Distribution ◽  
Google Earth ◽  
Training Data ◽  
Visual Interpretation ◽  
The Usa ◽  
Very High

Very high resolution (VHR) satellite imagery from Google Earth and Microsoft Bing Maps is increasingly being used in a variety of applications from computer sciences to arts and humanities. In the field of remote sensing, one use of this imagery is to create reference data sets through visual interpretation, e.g., to complement existing training data or to aid in the validation of land-cover products. Through new applications such as Collect Earth, this imagery is also being used for monitoring purposes in the form of statistical surveys obtained through visual interpretation. However, little is known about where VHR satellite imagery exists globally or the dates of the imagery. Here we present a global overview of the spatial and temporal distribution of VHR satellite imagery in Google Earth and Microsoft Bing Maps. The results show an uneven availability globally, with biases in certain areas such as the USA, Europe and India, and with clear discontinuities at political borders. We also show that the availability of VHR imagery is currently not adequate for monitoring protected areas and deforestation, but is better suited for monitoring changes in cropland or urban areas using visual interpretation.

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