Abstract:
Lebanon struggles to meet its domestic energy demands amidst one of the most severe globally ranked economic collapses and drastic environmental degradation. On top of this, Lebanon has a major dependence on imports for fuel to be utilized for energy generation and transportation. Turning challenges into opportunities, Lebanon has the potential to lead the transition toward a sustainable green economy by investing in ammonia for its application in the fuel production industry. The objective of this study is to determine the most efficient, competitive, and environmentally friendly ammonia synthesis process to be used as a long-term clean energy source – as a direct fuel and for hydrogen storage, and for industrial fertilizers production in Lebanon.
As a grounding step to contribute to making this a reality, this research study offers a comprehensive approach to assess the efficiency, competitiveness, and environmental friendliness of four ammonia synthesis configurations using a scenario analysis of Grey, Blue, Enhanced Blue, and Green ammonia processes. This is done through a techno-economic analysis and a life-cycle assessment using openLCA software performed for the four chosen ammonia production routes. Sensitivity analyses are developed to evaluate the effect of fluctuating prices of natural gas, ammonia, urea, and carbon dioxide credits on the economic feasibility of each configuration. The results of this study endorse the crucial sequential transition to green ammonia starting off from grey and blue production processes.
Abstract:
Higher education (HE) institutes are regarded, at a global scale, as a main driving force toward the establishment of a sustainable development-based awareness and mindset among the present and future generations, deeming their role towards the United Nations Sustainable Development Goals (UN SDGs) achievement a primary one despite several barriers.
In this paper, a model is developed using MATLAB software by integrating quantitative data on the sustainable development efforts implemented in 24 universities, including 4 Lebanese universities, in 12 countries located in 5 continents. This model outputs a decision-making tree on the sustainability of universities and a sensitivity analysis to compute sustainability scores for each university. With the aim of enhancing HEs crucial role in achieving the UN SDG 2030 agenda, this paper reveals and proves theories and trends depicted in the literature, and worldwide primarily by the Times Higher Education Impact Ranking.
Abstract:
In this paper we study the use of PV (photovoltaic) solar panels for marine vessels (mega-yachts) roofs. We consider three different PV materials- polycrystalline silicone, Gallium arsenide (GaAs) and Cadmium Telluride (CdTe). We simulate using ANSYS thermal modelling, PV panel for each of these materials, during the months of May, August, December with solar radiation heat flux of 399.25 W/m2, 286.67W/m2 and 186.23W/m2. The loads are applied on a PV panel with 5 layers consisting of glass, semi-conductor, tedlar, and two layers of encapsulant surrounded by an aluminium frame, to house all the components. Steady state thermal analysis is conducted. Contour plots are produced for total heat flux and temperature distribution. Bar charts are produced for comparing thermal performance. It is found that Gallium arsenide is the most thermally efficient material with the highest retention of total heat flux. It works more efficiently than the other options in particular when a coating of hydrophobic surface film is used in yacht applications in marine engineering.
Abstract:
Renewable energy has been regarded, on a global scale, as a feasible solution, a long- term growth and sustainable measure to encounter global warming and climate change. Countries worldwide are experiencing, at various levels, the negative impacts of global warming besides the volatility of oil prices as well as the awareness about the depletion of fossil fuels. The deployment of various renewable energy resources is gaining momentum as most countries have adopted the UN 2030 target of having at least 30% of the electric power generated from renewable resources. Also, clean technologies provide significant benefits in terms of economic growth, financial benefits, and environmental improvement, in addition to energy sector security. The Power authorities in Lebanon, a country currently with crucially unstable financial and economic conditions, are developing the National Renewable Energy Action Plan (NREAP) to meet the 2030 target taking into consideration three scenarios that reflect the economic recovery process by 2030, the Full Recovery, the Partial Recovery, and the lack of recovery (stagnation) scenario.
The objective of this paper is to assess the impact of each of the three scenarios in reaching the 2030 target, and the corresponding drop in CO2 emissions, that will have a positive environmental impact. A thorough assessment is made to estimate the impact of various economic recovery scenarios on the deployment of each of the renewable energy resources. Renewable energy resources are recognized as the primary component for mitigating the detrimental effects of the country’s power sector crisis and the overall economic as well as social welfare of the people.
According to the Partial Recovery scenario, Lebanon will reduce 0.92 tons of CO2/capita by 2030 compared to year 2020. By 2030, Lebanon will be performing better than some developing countries (Sudan, Egypt, Jamaica, Kenya) when it comes to the reduction of CO2 emissions/capita. In general, developed countries have higher values of reduction of CO2 emissions/capita than developing countries.
Abstract:
Lebanese residents have been increasingly shifting to photovoltaic (PV) power systems in an attempt to offset the ongoing electricity shortage that has been occurring for multiple years, due to the global rise in fuel prices, as well as the local financial crisis, leading to low fuel purchasing power from both the government and the private generators’ owners. This study aims to assess the life-cycle impacts of the transition to PV systems, for centralized (PV farms) and decentralized (distributed residential units) systems, focusing on two pillars related to this shift: environmental and economic. To address the environmental pillar, a Life-Cycle Assessment (LCA) for both centralized and decentralized PV systems was conducted. Regarding the economic pillar, the cost of a PV system throughout its lifespan was investigated, using the Life-Cycle Costing (LCC) framework, for both centralized and decentralized systems. To tackle these two pillars, the authors studied the literature, solved the location selection problem to determine the optimal location of the centralized PV farm, estimated the demand for capacity planning and sizing, and conducted an LCA and an LCC to understand the environmental impact of a PV system and its total cost from cradle to grave, respectively. The results demonstrated that the centralized system exhibits lower emissions than the decentralized system and is associated with lower lifetime costs, as per the LCA and LCC conducted. To expand on this study, the robustness and replicability of the proposed framework may be tested.
Abstract:
Ocean wave energy is being increasingly studied and deployed globally in the 21st century. It is a clean and sustainable natural energy resource. Motivated by simulating a floating wave energy converter, here we describe ANSYS FLUENT simulations (CFD) of a 2-D model of such a system. ANSYS Fluent defines a “phase” as an identifiable class of material that has a particular inertial response to and interaction with the flow and the potential field in which it is immersed. The present simulations consider a case of a floating on a surface of water buoy, which can be also defined as an interaction of a solid body with the fluid, at the border of a mixture of two phases. The modelling is conducted with the Euler-Euler approach, in which different phases are treated mathematically as inter-penetrating continua. Since both phases are treated separately and cannot be occupied by other phases the concept of phasic volume fraction is introduced. These fractions are assumed to be continuous functions of space and time and their sum is equal to one. In this analysis the Volume of Fluid (VOF) multiphase model is adapted. The propagation of waves is simulated as an upstream boundary condition applied to the velocity inlet of the VOF model. The software allows the user to simulate the propagation of regular or irregular waves with the aid either wave theories or wave spectrum. First order gravity water waves (Airy wave theory) i.e. small amplitude waves in shallow to deep liquid depth ranges have been explored. Extensive visualization of velocity and volume fraction fields is included. The computations have shown that the shorter the wavelength, the lower the response of the force. Due to the shortening of the wavelength the distance between the peaks of the waves is shorter; therefore, there is a lack of fully developed trough. This results in lower height of the oscillatory motion. Consequently, when the wavelength was increased, there was enough time to generate the fully developed wave hence, a higher oscillatory motion. This transpires in the higher force and in turn higher potential energy that the point absorber can operate at.
Abstract:
This literature review investigates the crucial role of the Thermal Management System (TMS) in optimizing safety, efficiency, and longevity in Stationary Battery Energy Storage (BESS), with a focus on Lithium-ion batteries (LIBs). The paper delves into the modeling of battery thermal dynamics, stressing the importance of heat generation and dissipation. The advantages and disadvantages of various TMS technologies such as air cooling, liquid cooling, and Phase Change Materials (PCMs) are studied for efficiency and environmental impact. TMS design principles, considering uniform temperature distribution and cost-effectiveness, are explored. Adequate assessment in the early design stage, structural optimization design techniques, and internal adjustments of the BESS layout are effective methods to achieve high-performance levels with straightforward procedures. Operational strategies, including control operation methods, predictive control, and meta-heuristic models, are examined for their impact on battery efficiency and life cycle. The paper concludes with a discussion of the future work needed in TMS, emphasizing environmental considerations and exploring the combined impact of different technologies. This research contributes to advancing the understanding of thermal management in BESS, promoting safety, sustainability, and efficiency in the growing field of renewable energy integration.
Abstract:
During the past decades, environmental concerns have become a global issue, mainly in the middle eastern region. Many actions are taken to help reduce pollution like using renewable energy, recycling or even replacing plastics with biodegradable products. If truth be told, the continuous piling up of industrial waste products is becoming a serious global environmental challenge that threats the ecosystem. All of this has significantly shaped queries on natural fibers in recent years. Fibers can be classified as synthetic and natural; synthetic fibers are manmade such as nylon, polyester, and acrylic while natural fibers are obtained from natural sources like plants and animals for example cotton, linen, coir, wool, and silk. Natural fibers have many advantages compared to synthetic fibers, especially in composite applications. Thus, these properties make natural fibers attractive in different applications. Hemp fibers, derived from the Cannabis Sativa L. plant, are among the most important industrial sources of fibers and they are considered the strongest of the family. Hemp fiber applications are numerous and distinctive including fishing nets, cloth, hats, papers, fabrics. Throughout this study, we evaluated and compared three different set of hemp fibers extraction methods for the purpose to establish the highest recovery by looking over the effect of different alkali percentages. Moreover, we measured the fiber properties such as density, pH, electrical conductivity, water absorbance coefficient and chemical stability in order to promote the use of hemp fibers as a multipurpose. Our results showed that the extraction using 7% NaOH and 0.5% Na2SO3 for 60 min at 100°C, has an optimal rate of 50% in mass. Moreover, this alkali treatment improves hemp fibers quality and properties. In fact, our measured density is found to be 0.514 g/cm3 significantly lower compared to the industrial fibers as carbon and glass, affecting the materials costs, handling and transportation. The electrical conductivity is measured and has a low value of 25μS/cm proposing to be stable and semi-conductor; thus, it could be used in different electrical composites applications such as micro-chips. The pH is found to be slightly acidic with a value of 6.5 giving an idea about the swelling, defined as a dimensional change due to water or moisture absorption. The capacity of water absorption exhibits a remarkable value around 336% after 1 h of immersion, indicating a better water resistance of treated fibrous biomaterial. The chemical stability was measured by immersing in a solution of 10% NaOH for 20 days with a mass loss of 19%, suggesting to have a better resistance of chemical degradation, encouraging to be used in alkaline environment such as cement. Our findings conclude that hemp fibers derived from the Cannabis Sativa L. compete with synthetic and industrial ones in many applications such as composites reinforcement, textiles and construction materials.
Abstract:
Since the turn of the 21st century, higher education in the Gulf Cooperation Council (GCC) region has witnessed significant progress, with the establishment of numerous universities aimed at delivering quality education. Dhofar University (DU) in Oman stands as a prime example of these efforts. This paper extends a reflective article published in 2014 on DU, aiming to evaluate the long-term impacts of initial strategic decisions, collaborations, accreditation processes, and sustainability of education on DU’s development, covering the period up to the present. The objective is to capture the evolution of DU’s academic, administrative, and strategic frameworks, providing a comprehensive overview of the university’s progress and current standing. By extending the reflection period to the present, this paper aims to offer a valuable understanding of the sustainability of DU’s early educational initiatives and provide actionable recommendations for future strategic planning, accreditation processes, and quality assurance practices.
Abstract:
In this paper, we examine the feasibility of harnessing abundant solar energy resources in North Africa to export it to Europe, via a high voltage direct current (HVDC) submarine cable (SC), where it will be used to produce green hydrogen for the European market. The main subsystems used to model green hydrogen production are water desalination by reverse osmosis, water electrolysis using a polymer-electrolyte membrane (PEM), solar PV panels, batteries, and submarine cables to transmit electric energy from Africa to Europe. These models were integrated using an energy management system to simulate the operation of generating renewable electric energy from PV panels and transmitting it to Europe to produce hydrogen. A search space of designs is identified and sampled and then examined to identify the best among these in an ordinal optimization (OO) framework to determine their cost of operation in $/kg of hydrogen. The likely optimal design had an average production rate of around 50 t/ day, which consisted of a PV plant of 810 MW, a battery of 1350MWh, a PEM of 86 t/ day, a RO size of 56 m3/h, a SC size of 2000mm2 at 320 kV DC, and a buffer hydrogen storage of 32 tons. This resulted in a hydrogen cost of $4.43/ kg, with the Tunis-Italy route being investigated for power delivery. This is deduced based on projected technology costs for the year 2035, which are likely to drop further.
Abstract:
Nanofluids are a subset of nanomaterials. They are doped fluids with suspensions of nanoparticles. Conventional heat transfer fluids have inherently poor thermal conductivity compared to solids. Conventional fluids that contain mm- or micro-m-sized particles do not work with the emerging “miniaturized” technologies since they can clog the tiny channels of these devices. Modern nanotechnology provides opportunities to produce nanoparticles that can be exploited in hybrid fuel cells e.g. magnetohydrodynamic fuel cell systems. Argonne National Lab developed the concept of nanofluids (1995). Nanofluids are a new class of advanced heat-transfer fluids engineered by dispersing nanoparticles smaller than 100 nm (nanometer) in diameter in conventional heat transfer fluids. Motivated by emerging hybrid magnetic nanofluid fuel cells, we present a numerical study of free convection MHD flow of hybrid magnetic nanofluid (Titania/Cu-water) in a 2-D differentially heated square closed space containing a non-Darcy porous medium. The non-dimensional governing equations for mass, momentum and energy are solved with associated boundary conditions by using the D2Q9-based Lattice Boltzmann Method. Extensive contour plots are included for streamlines and isotherms in the fuel cell enclosure. RSM-based sensitivity analysis is performed for hybrid nanofluid Titania-Cu/Water in a novel nano-magnetic fuel cell enclosure. The current investigation has been done considering the variation in Rayleigh number (1000 ≤ Ra ≤ 1,000,000), Darcy number (0.0001 ≤ Da ≤ 0.1) and Hartmann (magnetic) number (0 ≤ Ha ≤ 50). It has been discovered that the diagonal length of an eddy (internal vortex) boosts as the Rayleigh number increases. Furthermore, the magnitude of the Nusselt number is found to be linearly related to the Rayleigh number. In addition, it has been shown that the Nusselt number tends to drop as Hartmann (magnetic) number Ha values rise indicating that stronger magnetic field reduces the heat flux to the boundaries which can assist in thermal corrosion control in fuel cell design.
Abstract:
In this paper we will develop a methodology and computational tool to help us design power systems that are more secure and reliable. Our study investigates both traditional networks and micro-grids that may incorporate renewable energy sources like solar panels and batteries. The methodology is based on using a DC optimal power flow (DC-OPF) at the time of peak demand to carry out a contingency analysis. Fictitious generators are installed at load nodes to represent load-sheds that may be needed in case lines are at their limits or if existing generators do not have enough capacity to supply the load. When fictitious generators are used, this is either due to a shortage of generation or to a transmission line limitation. If generation is less than demand plus spinning reserve, then the system needs generation reinforcement, which are made available at candidate nodes, and sequentially added at nodes with the highest local marginal price (LMP). However, when the system has enough generators, and fictitious generation is used, then line reinforcements are probably needed, and the line selected for reinforcement is the one that is observed to be most often at its limits during the outage study. Once the network is deemed adequate, we analyze it using an AC-OPF to assess its reactive power capacity to supply the load and add static-var-compensation (SVC) systems if needed. Our methodology is applicable for micro-grids with renewable energy sources (e.g. PV panels) and storage units (e.g. batteries). However, the analysis of micro-grids with renewable energy sources requires identifying the critical hour when lines are most heavily loaded. The developed computational tool uses MATPOWER to carry out DC-OPF and AC-OPF and was tested on the IEEE 5, 30, 118 bus, and other systems.
Abstract:
Turbine blade failure is a large contributing factor to the overall failure of wind turbines across the world; every year 0.54% of the 700,000 wind turbines in operation fail each year due to the blades. This consequently costs billions each year in maintenance, down time, and environmental factors and therefore this needs to be investigated and resolved immediately. VINDSTAT database found that 8% of the downtime for a wind turbine is due to turbine blades, the CREW database discovered that on 34 occasions of downtime in the first 5 years due to the blades and finally, the NREL database showed that 1-3% of all turbines require replacement within the first 5 years. Fluid-structure interaction (FSI) creates fatigue effects in wind turbines, and this is a major contributor to structural failure. Turbine blades in wind turbine systems exhibit the highest number of failure events per year of any component and averaged at 1 hour of downtime per event. Considering that this occurs over 30 times in the first 5 years, the downtime is considerable. In this paper we simulate 3-D FSI in a curved HAWT (horizontal axis wind turbine) blade. We examine different free stream velocity cases and compute the streamlines, pressure, total deformation, Von Mises stress and strain. The flow domain is created around the blade with the inlet being assigned a length of 750 mm and the outlet assigned twice the length of 1500 mm. We investigate the modifications in response for a composite material blade. A non-linear region between the applied velocity of 3 m/s and 9 m/s is computed. The relationship morphs to a linear (elastic) one as the wind speed is increased from 9 m/s to 12 m/s. A mesh convergence study was done to determine the number of elements needed in the model to gain accurate results whilst keeping the processing time down. It could be seen from the graphs shown in section 3.1 that convergence took place at using a total of 18696 elements. Thus, an element size of 3 mm was ideal to use. There was very little difference seen in the data obtained after further decreasing the element size. The tip of the blade also experiences high pressures at high velocities, and this results in the total deformation, stress and strain increasing on the blade. The tip speed ratio of a wind turbine blade influences the power generated by the wind turbine blade. If the speed of the rotor is too slow, the blades will rotate slowly, and all the wind will pass through the gaps between the blades resulting in no power production. However, if the rotor is spinning to fast the blades will act as a solid wall and repel the wind. The noise levels emitted by increasing the tip speed ratio can prove to be a problem for turbines found on land. The maximum total deflection value was obtained for a wind speed of 12 m/s (1.0527 mm). The structural results obtained from ANSYS are dependent on the pressure loads imported from the fluent analysis. The maximum pressure exerted on the blade for a wind speed of 12 m/s was 5.132×102 Pa. This contributes to the maximum total deflection value being obtained.
Abstract:
In the twenty-first century, global challenges stem from population growth, technological advancement, and economic growth, resulting in an increase in energy demands. Various energy combustion processes are leading to persistent increase in GHG emissions, in addition to energy resources depletion. Renewable energy systems, in the wake of the UN Sustainable Development Goals set in 2015 for year 2030, have emerged as a key aspect of maintaining global sustainability, and they are also beneficial to an economy that integrates them into economic regeneration and ensures energy security. Renewable technologies in Lebanon offer a long-term solution to the short- handed electricity sector by providing off-grid energy access to the peripheral regions, making the adoption of clean energy a vital solution to meet the SDGs in a profitable and economically viable way.
This paper examines the assessment of three energy scenarios outlined in Lebanon’s National Renewable Energy Action Plan (NREAP) aimed to align with the UN 2030 SDGs through renewable energy adoption. The evaluation includes assessing the efficiency and economic feasibility of solar, wind, and hydropower technologies to define a sustainable energy mix, considering capital and operational costs alongside energy production, and aiming to achieve a 30% overall share of renewable energy within the total energy resource portfolio. Through the application of an optimization method, our analysis reveals that the optimal renewable energy share with the minimum cost for the year 2025 stands at 20%, totaling $6,557. This underscores the strategic significance of efficiently allocating renewable energy resources to simultaneously attain cost-effectiveness and meet sustainability objectives.
Abstract:
Achieving sustainability is a global priority requiring efforts and cooperation from all nations. A key factor for sustainability is to conserve resources and protect the environment from harmful emissions. For this purpose and in order to improve efficiency, reduce costs and minimize environmental impact, it is essential for the industries to work on power factor correction implementations. Hence, this paper explores different methods of improving power factor and compares between adopting a synchronous motor or an induction motor and capacitors in an industrial complex. First, power factor is a measure of the energy being wasted without giving any actual work or output (Reactive Power). Therefore, having a low power factor will contribute to having low efficiency and more emissions. This study compares the economic feasibility, loss reduction, payback period, and emissions reduction between the two different methods of power factor correction (PFC) stated above. The analysis shows that using an induction motor and capacitors will create not just an effective loss reduction solution but also a much friendlier cost. Moreover, this paper proves that by choosing the right method of PFC industries can benefit a lot in terms of savings and consumption while also having a short payback period. In a nutshell, power factor correction is a legitimate engineering practice for enhancing the performance parameters of industrial power systems.
Abstract:
Lebanon, especially Beirut, continues to face significant solid waste disposal challenges due to limited land, resources aggravated by a continued breakdown of central authority. The small overpopulated country, predominantly mountainous with only a narrow coastal strip and the Beqaa Valley as its main agricultural area, treats only 23% of its waste, with 8% undergoing material recovery and 15% composted. The remaining 77% is unsustainably dumped. Additionally, Lebanon suffers from a longstanding major grid electricity shortage, with no broad solution in sight. Apart from solar energy solutions, this paper re-thinks a possibly symbiotic solution involving a gas turbine plant designed to consume conventional fossil fuel and/or refuse-derived fuel, thus addressing to some extent both electricity and waste disposal issues. Results show that For a nominal 100 MW power output, it is possible to burn 1040 T/d RDF which constitutes about 65% of the daily produced RDF or 17.3% of daily generated MSW in Beirut, beefed up with only 1.98 T/d of premium fuel. Alternatively, if RDF becomes in shortage for some reason, 100 MW nominal power can be maintained if 467 T/d of premium fuel is combusted while combusting only 86 T/d of RDF which is 5% of daily RDF. Trade-off scenarios such a 50 % RDF-50% Fuel Oil case have also been presented.
Abstract:
This paper is based on a real-life project that evaluates the potential of a microgrid for a Lebanese village. The majority of the microgrid’s power will come from already-existing synchronous generators and solar power systems. This study finds methods to guarantee appropriate voltage quality by examining the micro grid voltage profiles at each bus at various times of the year. The steady-state behavior of the voltage profile is studied over time using ETAP power flow analysis module in four different seasons of the year. The main objective of this paper is to study the effectiveness of using droop control applied to synchronous generators or shunt capacitor banks and a comparison of both for improving the voltage profile at the different buses of the microgrid. Based on the obtained results for this case study and because of the system’s limited generation, droop control would be used for large loads, whereas simply using shunt capacitors could be efficient for low loads.
Abstract:
In the dynamic landscape of Electric Vehicles (EVs), this paper unfolds a detailed exploration of the indispensable Battery Management System (BMS) and its pivotal functions in optimizing battery performance, ensuring safety, and prolonging the lifespan of EVs. The analysis encompasses a thorough examination of both wired and wireless communication protocols employed by BMS, illuminating the advantages and disadvantages. Systematically comparing these protocols across performance, efficiency, cost, installation, and maintenance,the paper shows critical considerations influencing the selection of communication methods in BMS. Furthermore, it stares into the future, spotlighting emerging trends and technological advancements set to drive the automotive industry forward. Notable topics include the switchable 2x400V/800V architectures for long-range capabilities and rapid charging, as well as Electrochemical Impedance Spectroscopy (EIS) with Power Line Communication (PLC) for smart cell sensing without extensive wiring. The paper also explores the integration of Battery Digital Twin for predictive analysis, the perfect shifts toward Software-Defined Vehicles (SDV) enabling continuous improvement, and the adoption of Cloud-Based Wireless Solutions for over-the-air updates and remote capabilities. In conclusion, this paper stands as a comprehensive guide to the current and future landscape of BMS in EVs. In conclusion, the paper emphasizes the interconnected trajectory of EV trajectory, BMS, and communication protocols. The journey towards cleaner and more efficient mobility is accelerated by innovations in communication protocols and next-generation BMS technologies. The journey has just begun, directing toward a future marked by progress and transformative possibilities.
Abstract:
The increasing global demand for energy, coupled with mounting concerns over the environmental and economic impacts of conventional fuel sources, has underscored the urgent need for more sustainable alternatives, this study seeks to comprehensively examine various solar panel allocations taking into consideration the location and the sun’s trajectory. The research delves into the optimal deployment methods of solar panels across residential, commercial, and utility-scale applications, taking into meticulous account factors such as geographical location, climate patterns, space availability, estate cost, and energy consumption profiles. The research mainly focuses on East-West and South panels layouts, comparing their environmental and economic effects to fixed installations; Incorporating various tilt and azimuth angle settings further improves the study by illuminating how these modifications affect energy harvesting, cost-effectiveness, maintenance needs, and sustainability. Utilizing data gathered from solar atlases, accurate measurements of solar irradiance and other important parameters may be made, enabling a comprehensive analysis of the performance of every arrangement. The study’s conclusions are highly relevant to those involved in solar energy solutions since they provide a valuable comparative analysis of various allocation options. Through an analysis of the interactions between different types of panels, allocation algorithms, and sun trajectory modifications, this research seeks to improve decision-making regarding the most effective use of solar energy resources in a variety of contexts.
Abstract:
The transportation sector is a major contributor to global energy consumption and air pollution. In response, the automotive industry is actively engaged in addressing this dual challenge by pursuing advancements that enhance energy sustainability and minimize vehicle emissions. In this context, modern diesel engines are continually improving, driven by growing concerns about environmental impact and human health. In particular, Diesel Particulate Filters (DPFs) play a crucial role in reducing harmful particulate matter (PM) emissions from diesel engines. Maintaining optimal DPF performance is essential for both environmental and regulatory compliance. Modern legislations for diesel vehicles require the use of a soot sensor downstream the DPF to satisfy the new challenging OBD limits. In this work, the performance of a recent diagnostic technique based on 2D projection of the resistive soot sensor is assessed using Artemis driving cycle. A validated simulation platform is employed to evaluate DPF monitoring performance under realistic conditions that incorporate engine-out soot emission variations and sensor response dispersions. The obtained results are promising and show the relevance and robustness of the proposed approach for fast and effective DPF diagnostic. A statistical analysis is performed in order to derive a relevant detection threshold that satisfies a trade-off between false alarm and non-detection rates. The resulting diagnostic strategy has been validated for on-line DPF malfunction detection and can be easily implemented for real-time applications.
Abstract:
The significant increase in electricity demand, rapid depletion of fossil fuels, and environmental concerns around the world have led to the commissioning of large-scale solar Photo-Voltaic (PV) plants. The paper presents the theoretical and experimental analysis of a solar system floating over Qaraoun lake – Lebanon. The implementation of three interconnected 48 MW floating PV panels, covering 0.48 km², can generate 144 MW of power. The project will be supervised by several Closed-Circuit Television Televisions (CCTV) and a control room. Moreover, its output voltage needs to be raised to 66 kV, in order to be connected to the EDL network, using 360-500 kVA transformers, 9-20,000 kVA transformers and 69,300 m of 630 A cables. The economic feasibility showed that the turning point for the project to pay back is at 6 years returning almost $ 400,000,000 in the upcoming 25 years.
Abstract:
In recent years, the application of advanced machine vision technologies for fault detection in power transmission lines has gained substantial attention. Deep learning techniques have emerged as pivotal tools in developing robust vision-based solutions that enhance fault detection accuracy while reducing operational costs. However, the effectiveness of these techniques is often constrained by the availability of comprehensive datasets containing diverse and real-world fault scenarios in power transmission lines. This study addresses these challenges by proposing a framework for fault detection in power transmission lines using pre-trained deep learning models, specifically ResNet50 and EfficientB0 CNN architectures, for feature extraction. The Support Vector Machine (SVM) algorithm is employed for classification, leveraging its capability to handle multi-class fault detection tasks effectively. To evaluate the proposed framework, extensive tests are conducted on a merged dataset comprising images from publicly available datasets. The dataset encompasses a variety of fault types typically encountered in power transmission lines, enabling comprehensive performance evaluation based on accuracy and F1 scores. Comparative analyses are conducted with ten fine-tuned deep learning models to assess the efficacy of transfer learning techniques for fault detection and identification. The results demonstrate that the combined approach of deep feature extraction using CNNs and SVM classification outperforms transfer learning methods, particularly in terms of accuracy and reliability across various fault types.