Greenenergy Awards

  1. Introduction The rapid growth of renewable energy integration into smart microgrids has introduced both opportunities and operational complexities. Renewable energy sources such as solar and wind are inherently intermittent, leading to uncertainty in generation forecasting and grid balancing. Simultaneously, demand response programs enable flexible load management, creating new dimensions for optimizing energy distribution. This research investigates advanced energy management strategies that integrate uncertainty modeling and consumer participation mechanisms to ensure economic efficiency, grid stability, and sustainability. The study establishes a comprehensive analytical framework combining stochastic optimization, predictive modeling, and real-time control systems to improve microgrid performance under uncertain conditions. 2. Modeling Renewable Energy Uncertainty Renewable energy sources introduce variability due to weather-dependent generation patterns. This research...

  1. Introduction Renewable energy deployment in Africa presents both significant opportunities and complex challenges driven by climate variability, infrastructure gaps, and energy access demands. A weather-aware optimization framework integrates meteorological intelligence with renewable energy planning to improve system resilience and operational efficiency. By combining forecasting analytics, smart grid technologies, and data-driven optimization, researchers aim to enhance stability, reduce intermittency risks, and support sustainable energy transitions across diverse African regions. 2. Climate-Integrated Energy Forecasting Models Advanced climate-integrated forecasting models enhance renewable energy reliability by incorporating real-time weather data into solar and wind power prediction systems. These models reduce uncertainty, improve grid balancing strategies, and optimize power generation scheduling under dynamic climatic conditions. 3. Optimization Algorithms for Ren...

  1. Introduction Digital-driven new quality productivity represents a transformative shift in economic systems where digital technologies, data integration, and intelligent platforms redefine production efficiency and structural coordination. In the context of global supply chain disruptions, resilience has become a strategic priority. This study integrates complex network theory with the Hadamard Product to analyze how digital innovation strengthens interconnected production networks, enhances adaptive capacity, and improves systemic robustness. By examining multi-layer economic linkages, the research provides a novel methodological contribution to understanding digital transformation and supply chain sustainability. 2. Digital-Driven Productivity Transformation Digital-driven productivity extends beyond traditional efficiency metrics by incorporating data analytics, artificial intelligence, cloud platforms, and interconnected systems into production ecosystems. This research ...

  1. Introduction The transcritical CO₂ cycle represents a significant advancement in sustainable energy and refrigeration research due to its minimal environmental impact and compatibility with climate goals. Unlike conventional refrigerants, CO₂ operates above its critical point, enabling unique thermodynamic behavior that offers both opportunities and challenges. Current research focuses on improving system efficiency, understanding supercritical heat transfer, and optimizing operating conditions. As global regulations phase out high-GWP refrigerants, the transcritical CO₂ cycle has become a central topic in energy, mechanical, and environmental engineering research. 2. Thermodynamic Principles and System Modeling Research on the transcritical CO₂ cycle emphasizes advanced thermodynamic modeling to understand supercritical fluid behavior and heat exchange mechanisms. Scholars investigate pressure optimization, gas cooler performance, and entropy generation to enhance system e...

1. Introduction The green trade transition represents a critical shift in how countries align international trade with environmental sustainability goals. In OECD economies, this transition is driven by a combination of regulatory pressure, technological advancement, and global climate commitments. This research introduces the concept of green trade, highlights its relevance in contemporary economic discourse, and establishes the importance of empirically identifying its key determinants using dynamic panel modeling techniques. 2. Conceptual Framework of Green Trade in OECD Economies This topic examines the theoretical foundations of green trade, focusing on how environmental standards, trade liberalization, and sustainable production interact within OECD countries. It discusses the evolution of green trade policies and their role in promoting environmentally responsible exports and imports while maintaining economic competitiveness. 3. Methodological Approach Using Dynamic Panel Model...

  1. Introduction The integration of Computational Fluid Dynamics (CFD) with Artificial Neural Networks (ANN) represents a transformative approach in modern engineering research. Traditional CFD methods, while accurate, are computationally intensive, especially for complex blade deformation and aerodynamic response analysis. By coupling CFD with ANN models, researchers can achieve faster predictions without compromising accuracy, enabling efficient optimization of blade design in renewable energy and turbomachinery applications. 2. CFD-Based Aerodynamic Modeling CFD plays a critical role in capturing complex airflow behavior around rotating blades, including turbulence, pressure distribution, and wake interactions. In this research context, CFD simulations provide high-fidelity datasets that describe aerodynamic loads and deformation patterns under varying operating conditions. These simulations form the foundational knowledge base for training intelligent predictive models. 3....