45 research outputs found

    Oil Spill Detection Analyzing “Sentinel 2“ Satellite Images: A Persian Gulf Case Study

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    Oil spills near exploitation areas and oil loading ports are often related to the ambitions of governments to get more oil market share and the negligence at the time of the loading in large tankers or ships. The present study investigates one oil spill event using multi sensor satellite images in the Al Khafji (between Kuwait and Saudi Arabia) zone. Oil slicks have been characterized with multi sensor satellite images over the Persian Gulf and then analyzed in order to detect and classify oil spills in this zone. In particular this paper discusses oil pollution detection in the Persian Gulf by using multi sensor satellite images data. Oil spill images have been selected by using Sentinel 2 images pinpointing oil spill zones. ENVI software for analysing satellite images and ADIOS (Automated Data Inquiry for Oil Spills) for oil weathering modelling have been used. The obtained results in Al Khafji zone show that the oil spill moves towards the coastline firstly increasing its surface and then decreasing it until reaching the coastline

    Marine energy digitalization digital twin's approaches

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    Digital twins (DTs) promise innovation for the marine renewable energy sector using modern technological advances and the existing maritime knowledge frameworks. The DT is a digital equivalent of a real object that reflects and predicts its behaviours and states in a virtual space over its lifetime. DTs collect data from multiple sources in pilots and leverage newly introduced low-cost sensor systems. They synchronize, homogenize, and transmit the data to a central hub and integrate it with predictive and learning models to optimize plant performance and operations. This research presents critical aspects of DT implementation challenges in marine energy digitalization DT approaches that use and combine data systems. Firstly, the DT and the existing framework for marine knowledge provided by systems are presented, and the DT's main development steps are discussed. Secondly, the DT implementing main stages, measurement systems, data harmonization and preprocessing, modelling, comprehensive data analysis, and learning and optimization tools, are identified. Finally, the ILIAD (Integrated Digital Framework for Comprehensive Maritime Data and Information Services) project has been reviewed as a best EU funding practice to understand better how marine energy digitalization DT's approaches are being used, designed, developed, and launched

    Hourly energy profile determination technique from monthly energy bills

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    Hourly energy consumption profiles are of primary interest for measures to apply to the dynamics of the energy system. Indeed, during the planning phase, the required data availability and their quality is essential for a successful scenarios’ projection. As a matter of fact, the resolution of available data is not the requested one, especially in the field of their hourly distribution when the objective function is the production-demand matching for effective renewables integration. To fill this gap, there are several data analysis techniques but most of them require strong statistical skills and proper size of the original database. Referring to the built environment data, the monthly energy bills are the most common and easy to find source of data. This is why the authors in this paper propose, test and validate an expeditious mathematical method to extract the building energy demand on an hourly basis. A benchmark hourly profile is considered for a specific type of building, in this case an office one. The benchmark profile is used to normalize the consumption extracted from the 3 tariffs the bill is divided into, accounting for weekdays, Saturdays and Sundays. The calibration is carried out together with a sensitivity analysis of on-site solar electricity production. The method gives a predicted result with an average 25% MAPE and a 32% cvRMSE during one year of hourly profile reconstruction when compared with the measured data given by the Distributor System Operator (DSO)

    Methodology framework for prioritisation of renewable energy sources in port areas

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    Ports play a crucial role in increasing the decarbonisation of urban environments to mitigate the environmental impacts of maritime transport and promote sustainable intermodal mobility. Various efforts have been made to increase energy self-sufficiency using renewable energy sources (RESs) in different ports worldwide. However, the ports played an essential role in the pollution process of the nearest cities due to the short distance and merging with urban areas. In this case, solar and wind were measured using the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data of four Lazio province ports. Each RES was evaluated using 10 years of monthly data for mapping and 1 year of hourly data for potential assessment and energy converters installation. Furthermore, the time series method has been considered to design and develop better management of RESs for decision making monitoring the energy needs of ports. This time series method has been applied to the generated energy source based on various parameters of the RESs used in port

    Offshore wind farm layouts designer software's

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    Offshore wind energy can be considered one of the renewable energy sources with high force potential installed in marine areas. Consequently, the best wind farm layouts identified for constructing combined offshore renewable energy farms are crucial. To this aim, offshore wind potential analysis is essential to highlight the best offshore wind layouts for farm installation and development. Furthermore, the offshore wind farm layouts must be designed and developed based on the offshore wind accurate assessment to identify previously untapped marine regions. In this case, the wind speed distribution and correlation, wind direction, gust speed and gust direction for three sites have been analyzed, and then two offshore wind farm layout scenarios have been designed and analyzed based on two offshore wind turbine types in the Northwest Persian Gulf. In this case, offshore wind farm layouts software and tools have been reviewed as ubiquitous software tools. The results show Beacon M28 and Sea Island buoys location that the highest correlation between wind and gust speeds is between 87% and 98% in Beacon M28 and Sea Island Buoy, respectively. Considerably, the correlation between wind direction and wind speed is negligible. The Maximum likelihood algorithm, the WAsP algorithm, and the Least Squares algorithm have been used to analyze the wind energy potential in offshore buoy locations of the Northwest Persian Gulf. In addition, the wind energy generation potential has been evaluated in different case studies. For example, the Umm Al-Maradim buoy area has excellent potential for offshore wind energy generation based on the Maximum likelihood algorithm, WAsP algorithm, and Least Squares algorithm

    A parametric study of wave energy converter layouts in real wave models

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    Ocean wave energy is a broadly accessible renewable energy source; however, it is not fully developed. Further studies on wave energy converter (WEC) technologies are required in order to achieve more commercial developments. In this study, four CETO6 spherical WEC arrangements have been investigated, in which a fully submerged spherical converter is modelled. The numerical model is applied using linear potential theory, frequency-domain analysis, and irregular wave scenario. We investigate a parametric study of the distance influence between WECs and the effect of rotation regarding significant wave direction in each arrangement compared to the pre-defined layout. Moreover, we perform a numerical landscape analysis using a grid search technique to validate the best-found power output of the layout in real wave models of four locations on the southern Australian coast. The results specify the prominent role of the distance between WECs, along with the relative angle of the layout to dominant wave direction, in harnessing more power from the waves. Furthermore, it is observed that a rise in the number of WECs contributed to an increase in the optimum distance between converters. Consequently, the maximum exploited power from each buoy array has been found, indicating the optimum values of the distance between buoys in different real wave scenarios and the relative angle of the designed layout with respect to the dominant in-site wave direction

    A primary offshore wind farm site assessment using reanalysis data: a case study for Samothraki island

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    The correct strategy for monitoring and assessing marine Renewable Energy Sources (RESs) is of great importance for local/national sustainable development. To achieve this goal, it is necessary to measure in the most precise possible manner the local/regional RESs potential. This is especially true for Offshore Wind (OW) energy potential, since the most precise techniques are long and expensive, and are not able to assess the RESs potential of large areas. Today, Remote Sensing (RS) satellites can be considered the most important land and marine observation tools. The RS tools can be used to identify the interested areas for future OW energy converters installations in large and small-scale areas. In this study, the OW energy potential has been analysed by means of a 40 years wind speed data from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset of the Samothraki island surrounding area in the Mediterranean Sea. The OW speed potential has been analysed by means of monthly data from ECMWF Interim reanalysis (ERA-Interim) datasets using the Network Common Data Form (NetCDF) format. Automatically, analyses have been carried out using the Region Of Interest (ROI) tool and Geographical Information System (GIS) software in order to extract information about the OW speed assessment of the Samothraki island area. The primary results of this study show that the southwest area of Samothraki island has good potential for future OW farms installation (bottom fixed and floating version) in near and offshore areas. This study shows the OW energy potential per location, as well as the trend of OW speed, which has changed over the past 40 years in the Mediterranean Sea

    Investigating Smart City Development Based on Green Buildings, Electrical Vehicles and Feasible Indicators

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    With a goal of achieving net-zero emissions by developing Smart Cities (SCs) and industrial decarbonization, there is a growing desire to decarbonize the renewable energy sector by accelerating green buildings (GBs) construction, electric vehicles (EVs), and ensuring long-term stability, with the expectation that emissions will need to be reduced by at least two thirds by 2035 and by at least 90% by 2050. Implementing GBs in urban areas and encouraging the use of EVs are cornerstones of transition towards SCs, and practical actions that governments can consider to help with improving the environment and develop SCs. This paper investigates different aspects of smart cities development and introduces new feasible indicators related to GBs and EVs in designing SCs, presenting existing barriers to smart cities development, and solutions to overcome them. The results demonstrate that feasible and achievable policies such as the development of the zero-energy, attention to design parameters, implementation of effective indicators for GBs and EVs, implementing strategies to reduce the cost of production of EVs whilst maintaining good quality standards, load management, and integrating EVs successfully into the electricity system, are important in smart cities development. Therefore, strategies to governments should consider the full dynamics and potential of socio-economic and climate change by implementing new energy policies on increasing investment in EVs, and GBs development by considering energy, energy, techno-economic, and environmental benefits

    Gis and remote sensing for renewable energy assessment and maps

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    Geographic Information Systems (GIS) and Remote Sensing (RS) techniques are of great interest for the renewable energy field. The assessment and monitoring of Renewable Energy Sources (RESs) potential is critical in planning their high-penetration in the energy systems. To this aim, several different measurements tools such as in-situ measurements (cup anemometers and buoys), on-site RS tools (e.g., LIDAR and SODAR), satellite image data and reanalysis datasets (e.g., ECMWF and MERRA) can be used. This Special Issue aims to provide the state-of-the-art tools mentioned earlier in different energy applications and at different scales, i.e., urban, regional, national and even continental, for planning and policymaking of renewable scenarios. For this purpose, the Special Issue “GIS and Remote Sensing for Renewable Energy Assessment and Maps” has been designed and launched, intended for renewable energy engineers, GIS and platform users, as well as planners. Among a very high number of submissions, 13 articles were selected for acceptance and publication

    Nearshore wave energy assessment of Iranian coastlines

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    In this study, the measured wave data for year 2010 at 3 hour time step for six sites in the Caspian sea, Persian Gulf and Oman Sea of Iran have been statistically analysed to determine the wave power potential of Iranian coastlines. The statistical attitudes allows to estimate the significant weight height (Hs), peak wave energy period (Tp), and the wave energy flux for unit of crest length. This preliminary research aims to assess the nearshore wave energy potential and ultimately identify the best Wave Energy Converters (WECs) technology for the peculiar wave climate of the studied areas. Results show that wave power in Qeshm, Chabahar and Anzali presents the best potential and thus are the most indicated to be studied further the installation of Wave Energy Converters
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