Determination of temperature profile inside a PV module operating under specific conditions using a model coupling internal heating to optical absorption
In this study, the complex dynamics behind heat transfer within photovoltaic (PV) solar modules under spectral solar illumination are investigated. A new model coupling internal heating to optical absorption is derived from equations governing ...
Assessing the potential of green hydrogen production from wind power: case of microgrid
In the context of a microgrid, green hydrogen production from wind power was assessed in this paper. A Wind-Hydrogen Integrated Power Grid Model was employed to address the intermittent nature of wind energy resources. Wind power generation was ...
A Brief Review of Energy Consumption Forecasting Using Machine Learning Models
Energy consumption forecasting plays a pivotal role in modern resource management and sustainable development. This paper presents a concise overview of state-of-the-art techniques and methodologies employed in the field of energy consumption ...
Sustainability-Driven Hourly Energy Demand Forecasting in Bangladesh Using Bi-LSTMs
This research presents a comprehensive study on developing and evaluating a deep learning-based forecasting model for hourly energy demand prediction in Bangladesh. Leveraging a novel dataset obtained from the Power Grid Company of Bangladesh (...
Electrocoagulation-based AZO DYE (P4R) Removal Rate Prediction Model using Deep Learning
- Meryem Akoulih,
- Smail Tigani,
- Fouzia Byoud,
- Meryem El Rharib,
- Rachid Saadane,
- Samuel Pierre,
- Abdellah Chehri,
- Sanae El Ghachtouli
This article presents a study on the effectiveness of electrocoagulation (EC) for the removal of azo dyes from wastewater. The analysis was performed using a combination of statistical methods, including density estimation, correlation analysis, ...
Towards Sustainable Buildings: Predictive Modeling of Energy Consumption with Machine Learning
The building sector's energy consumption remains a significant problem, requiring the development of powerful energy management systems to improve energy efficiency. The main aim of this research is to forecast energy use through indoor ...
Nexus between economy, renewable energy, population and ecological footprint: empirical evidence using STIRPAT model in Morocco
The present study aims to examine the long run impacts of per capita income, renewable energy consumption, urbanization, trade openness on ecological footprint in Morocco over the period 1980-2021. It also attempts to explore the validity of the ...
Prediction of energy production in a building-integrated photovoltaic system using machine learning algorithms
Globally, the building sector is a significant consumer of energy. Implementing effective energy management system (EMS) strategies is crucial for reducing energy consumption and optimizing energy usage across all building elements. Moreover, ...
Challenges and Limitations of Artificial Intelligence Implementation in Modern Power Grid
Ongoing global decarbonization and energy transition have led to significant changes in the traditional power grid, resulting in new challenges for grid operators. These challenges, which are exacerbated by the increased penetration of distributed ...
Review of the Integration of Photovoltaic and Electric Vehicles on Distribution Network: Impacts and Enhancement Approaches
The development of electricity generation from renewable sources, particularly photovoltaic energy (PV), as well as the significant growth of electric mobility with electric vehicles (EVs), leads us to contemplate the potential impacts of these ...
Proactive Environmental Management's Drive for Green Technology Adoption in MENA Firms: Regulatory Mediation and Financial Moderation
This empirical study explores the determinants of Green Technologies and Practices (GTP) adoption within Middle East and North Africa (MENA) firms, focusing on Proactive Environmental Management (PEM), Environmental Regulation (ER), and Financial ...
Design optimization of a multi-source renewable energy system using a novel method based on selective ensemble learning
This study conducts a comparative assessment to optimize the design of a Hybrid Renewable Energy System (HRES) consisting of PV panels, wind turbines (WTs), and hydrogen storage (PV/WT/FC). The study focuses on Dakhla City, leveraging its ...
Solar To Hydrogen Production Barriers and Opportunities in Oman: A Case Study in The Dhofar Region
The energy demand has increased rapidly worldwide due to the depletion of fossil fuels. Recently, the rate of energy consumption has become unsustainable, providing a strong incentive for many countries to pursue renewable energy sources. By 2030, ...
Review on Biodiesel Generations: Energy Demand, Costs, and Emissions
- Houda Amdi,
- Imane Hajjout,
- Reda Errais,
- Mohammed Jmili,
- Khalid Guissi,
- El Mostapha Boudi,
- El Houssain Baali
Faced with the growing demand for energy worldwide, fossil fuels, like any other resource available in finite quantities, are in the process of disappearing since their production cannot increase indefinitely. On the other hand, Russia's war with ...
Deep Learning and Econometric Analysis of CO2 Emissions in Bangladesh: A Transition Towards Renewable Energy and Sustainable Practice
- Tamanna Siddiqua Ratna,
- Tanzin Akhter,
- Md. Ashraful Babu,
- Md. Mortuza Ahmmed,
- M. Mostafizur Rahman,
- Mufti Mahmud
Environmental sustainability achievement is an increasingly significant issue in current society. Globally, unimpeded greenhouse gas emissions threaten environmental sustainability. As a developing economy, Bangladesh is extremely reliant on ...
Analysis of land use and land cover transpose using remote sensing and GIS approach: a case of Hamirpur, India
The process of urbanization is inevitable and its higher rates have been observed in the less developed nations. It has impacted the socio-economic as well as environmental condition of the urban system. The present study intends to demonstrate a ...
Integrated Thermodynamic Analysis and Channel Variation Effects on Solid Oxide Electrolysis for Efficient Hydrogen Generation
This study delves into the intricate dynamics of Solid Oxide Electrolysis Cells (SOECs) using comprehensive simulation and analysis. By exploring the effects of temperature, pressure, and geometrical variations, we reveal valuable insights into ...
Modeling and Analysis of a Horizontal Axis Current Turbine
In recent times, various research studies have proven that the marine currents turbine (MCT) resource has enormous potential for electric power. For the proper exploitation of this resource, it is necessary to understand the hydrodynamics of the ...
Federated Learning Communications Optimization Using Sparse Single-Layer Updates
Federated learning has emerged as a robust framework for distributed machine learning, enabling model training across decentralized data sources while preserving data privacy. Despite its advantages, a persistent challenge remains: the high ...
Kolmogorov-Smirnov based method for detecting black hole attack in vehicular ad-hoc networks
- Badreddine Cherkaoui,
- Mohammed-Alamine El Houssaini,
- Mohammed Kasri,
- Abderrahim Beni-Hssane,
- Mohammed Erritali
The security of ad hoc networks continues to pose a major challenge in today's digital age. Threatened by unscrupulous users, especially in decentralized and open architectures, ad-hoc vehicular networks make protection against malicious attacks a ...
Impact of Renewable Energy Resources on the Performance of DTN Networks in the Context of Hierarchical Routing Tree Topology (HRTT)
Delay-Tolerant Networks (DTN) are mobile networks specifically designed to operate in challenging wireless environments where connectivity is not guaranteed, and various issues such as frequent disconnections, long delivery delays, low delivery ...
Smart Waste Collection Based on Vehicle Routing Optimization: Case of Casablanca City
Morocco has implemented circular economy principles in their waste management program to close or rehabilitate all existing landfills. However, the waste collection and transportation process remain highly inefficient and costly, contributing to a ...
Deep learning and Vegetation indices based approach for leaf diseases classification in RGB images
Foliar diseases are one of the factors that impact corn crop productivity. Automatic detection of corn diseases can play an important role in addressing the issue of diseases management and productivity enhancement. In this regard, an experimental ...