Greenenergy Awards

  1. Introduction The Research Excellence Award represents a benchmark of scholarly distinction, recognizing individuals who contribute significantly to advancing knowledge and innovation. In a rapidly evolving global research ecosystem, excellence is defined not only by publication output but also by impact, collaboration, and transformative discoveries. This award fosters a culture of intellectual rigor, interdisciplinary engagement, and evidence-based progress that shapes the future of science and society. 2. Measuring Research Impact and Scholarly Contribution Research impact extends beyond publication counts to include citation influence, collaborative networks, and societal relevance. This topic explores quantitative and qualitative metrics used to evaluate scholarly performance, emphasizing responsible research assessment and knowledge dissemination across global academic platforms. 3. The Role of Peer-Reviewed Publications in Advancing Knowledge Peer-reviewed research ...

1. Introduction Decentralized renewable energy systems are transforming the global energy landscape, yet surplus generation from solar mini-grids often remains underutilized. Integrating green finance mechanisms and vertically coordinated economic structures can unlock this excess capacity to produce low-carbon hydrogen and support electric mobility ecosystems. This research introduces a systemic framework that connects renewable surplus utilization, hydrogen value chain development, and sustainable transport electrification to enhance carbon mitigation and economic resilience. 2. Solar Mini-Grid Surplus Optimization and Energy Storage This topic investigates technical strategies for capturing and optimizing surplus electricity generated by solar mini-grids. It evaluates storage technologies, demand-side management, and power-to-hydrogen conversion systems to ensure efficient utilization of excess renewable energy while minimizing curtailment losses. 3. Green Finance Mechanisms for Hyd...

  1. Introduction Fluoride contamination in groundwater poses significant risks to human health, including dental and skeletal fluorosis. Developing cost-effective and environmentally sustainable removal techniques is therefore essential. This research introduces the application of Chara vulgaris biomass as a biosorbent for fluoride ion adsorption. By integrating kinetic and thermodynamic evaluations, the study provides a scientific foundation for understanding adsorption mechanisms, efficiency, and feasibility under different environmental conditions. 2. Characterization of Chara vulgaris Biomass as a Biosorbent This topic focuses on the physicochemical properties of Chara vulgaris biomass that influence fluoride adsorption performance. Surface morphology, functional groups, porosity, and active binding sites are examined using analytical techniques. The findings explain how natural biomass structure enhances adsorption capacity and supports its application in low-cost water...

  1. Introduction The transition toward renewable energy systems requires sustainable and resilient biomass supply chain networks capable of operating under uncertainty and disruption risks. This research introduces an integrated multi-period, multi-objective mathematical modeling framework that simultaneously optimizes economic, environmental, and social objectives. By incorporating scenario-based uncertainty analysis, the model enhances decision-making robustness while addressing long-term sustainability challenges in biomass energy infrastructure planning. 2. Multi-Objective Mathematical Modeling Framework This topic explores the development of a comprehensive mathematical model that optimizes cost efficiency, carbon emissions, and social welfare simultaneously. Using multi-objective programming techniques, the study generates Pareto-optimal solutions that help decision-makers balance trade-offs between profitability, sustainability, and community development goals. 3. Scena...

  1. Introduction Forest biomass estimation plays a crucial role in understanding carbon sequestration potential, ecosystem productivity, and climate regulation. Nepal’s diverse topography and ecological gradients require spatially explicit modeling approaches to capture regional biomass variability. This research introduces a data-driven bioregionalisation framework combined with machine learning algorithms to enhance prediction accuracy across forest types. By integrating ecological zoning with predictive modeling, the study supports national climate commitments and sustainable forest governance strategies. 2. Data-Driven Bioregionalisation Framework This topic explores the methodological foundation of dividing Nepal into ecologically homogeneous bioregions using environmental variables such as elevation, precipitation, soil type, and vegetation indices. Bioregionalisation improves predictive consistency by reducing spatial heterogeneity and strengthening model generalization ...

  1. Introduction Geothermal energy exploration requires accurate subsurface characterization to reduce drilling risks and improve resource assessment. This research introduces an integrated methodology combining radon gas measurement and conventional electrical prospecting to enhance geothermal detection efficiency. By analyzing radon anomalies associated with subsurface fault zones and correlating them with resistivity data, the study demonstrates a multidisciplinary approach to identifying geothermal reservoirs. The Lantian Section case study provides a practical framework for sustainable geothermal exploration and contributes to advancing renewable energy resource mapping techniques. 2. Radon Measurement in Geothermal Prospecting Radon gas anomalies are closely linked to tectonic fractures and geothermal pathways. This topic examines radon concentration mapping techniques and their role in identifying permeable zones associated with geothermal reservoirs. The study highlight...

  1. Introduction Geothermal energy exploration plays a crucial role in advancing sustainable and renewable energy systems. Accurate identification of geothermal reservoirs requires integrated geophysical and geochemical methods to reduce uncertainty and enhance exploration success rates. This study introduces the combined use of soil radon measurement and conventional electrical prospecting techniques to improve geothermal anomaly detection. By analyzing subsurface gas migration patterns alongside resistivity variations, researchers can better interpret fault structures and heat pathways, contributing to efficient geothermal resource assessment and sustainable energy planning. 2. Radon Measurement as a Geochemical Indicator This topic explores radon gas as a tracer for identifying geothermal activity. Elevated radon concentrations often correlate with fault zones and fracture systems that facilitate heat flow. The research evaluates radon anomaly mapping techniques and discusse...

  1. Introduction High-temperature and high-pressure (HTHP) drilling environments demand advanced fluid systems capable of maintaining structural integrity and operational efficiency under extreme thermal stress. Conventional drilling fluids often degrade at elevated temperatures, leading to reduced foam stability, viscosity loss, and compromised wellbore control. This research introduces a novel high-temperature-resistant foam drilling fluid system engineered to enhance thermal endurance, improve rheological stability, and ensure effective cuttings transport in deep and ultra-deep wells. 2. Thermal Stability and Rheological Performance Analysis This topic investigates the rheological behavior of foam drilling fluids under elevated temperature conditions. Laboratory testing evaluates viscosity retention, foam half-life, and shear resistance across various temperature ranges. The findings highlight the importance of polymer stabilizers and surfactant optimization in preserving fl...

  1. Introduction The rapid expansion of renewable energy systems has intensified focus on the energy quality trilemma: maintaining reliability, affordability, and environmental sustainability simultaneously. However, correlated climatic events—such as coincident wind and solar droughts—pose systemic risks to power systems with high renewable penetration. This research investigates how simultaneous low-generation periods challenge grid stability, increase dependency on backup generation, and influence long-term energy planning. By combining climate variability analysis with energy system modeling, the study provides a structured understanding of renewable generation risks in decarbonized electricity systems. 2. Statistical Modeling of Coincident Renewable Droughts This research topic explores probabilistic and time-series modeling techniques used to detect and predict simultaneous low wind and solar generation events. By analyzing long-term meteorological datasets, researchers quan...

  1. Introduction Energy insecurity remains a critical socio-economic challenge in the United States, disproportionately affecting low-income and marginalized communities. Households facing high energy burdens often engage in energy-limiting behaviors such as reducing heating or cooling, compromising health and well-being. Rooftop solar photovoltaic systems combined with residential energy storage present an innovative solution to improve affordability, reliability, and resilience. This research introduces the theoretical and empirical foundations for examining how distributed clean energy technologies can alleviate energy insecurity while supporting decarbonization and equitable energy transitions. 2. Measuring Energy Insecurity and Household Energy Burden This topic focuses on the quantitative assessment of energy insecurity using metrics such as energy burden ratios, payment arrears, service disconnections, and thermal discomfort indicators. The research evaluates socio-econo...

  1. Introduction Urban waste collection systems significantly contribute to transportation-related carbon emissions. Integrating environmental considerations into vehicle routing optimization represents a transformative step toward sustainable logistics. This research introduces emission-sensitive path optimization models that balance operational efficiency and environmental responsibility. By incorporating carbon cost functions into routing algorithms, municipalities can improve sustainability metrics while reducing fuel consumption and greenhouse gas emissions in municipal solid waste transportation systems. 2. Carbon Emission Modeling in Waste Transportation This topic examines quantitative emission modeling techniques used to measure fuel consumption and carbon output in municipal waste transport fleets. By integrating emission estimation formulas into routing algorithms, researchers can evaluate the environmental cost of each route. The study highlights how emission-based ...

  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....

  1. Introduction The integration of offshore wind power with hydrogen energy storage systems has emerged as a promising solution for addressing intermittency challenges and achieving long-term sustainability goals. Life Cycle Environmental Impact Assessment (LCA) provides a comprehensive framework to evaluate the environmental performance of such integrated energy systems across all life cycle stages. This research focuses on understanding how offshore wind–hydrogen systems contribute to emissions reduction, energy efficiency, and sustainable resource utilization within the broader context of global energy transition. 2. Life Cycle Assessment Framework for Offshore Wind Systems This topic examines the methodological framework used to conduct life cycle assessments of offshore wind power systems. It highlights key stages such as raw material extraction, turbine manufacturing, transportation, offshore installation, operation, maintenance, and end-of-life disposal or recycling. By...