Renewable Energy Research Articles

The Impact of Renewable Energy Consumption on Unemployment in Developed Countries

The utilization of renewable energy resources has been increasing in alignment with sustainable development goals, generating significant effects on economic indicators. In this context, examining the impact of renewable energy consumption on unemployment is of considerable importance for both economic policymakers and academic researchers. The primary objective of this study is to determine whether renewable energy consumption has a reducing effect on the unemployment rate. While investments in the renewable energy sector are generally believed to enhance employment, the direction and magnitude of this relationship may vary across countries. Therefore, this study investigates the relationship between renewable energy consumption and unemployment in a sample of developed countries. To conduct the analysis, fixed effects and random effects models were applied using a panel data set. The findings indicate that renewable energy consumption contributes to a reduction in the unemployment rate. Additionally, GDP and trade openness, included in the model as control variables, exhibit statistically significant negative effects on unemployment. However, the effect of inflation on the unemployment rate is found to be insignificant. The results of this study are expected to contribute to a deeper understanding of the impact of renewable energy policies on employment. Furthermore, these findings provide valuable insights for assessing the role of energy policies in economic growth and labor market dynamics.

The Role of Research and Development in Renewable Energy Consumption - Sustainable Human Development Nexus: Evidence from EAC Member Countries

The pressing challenges of climate change and energy access in the East African Community (EAC) necessitate a strategic focus on research and development (R&D) to enhance renewable energy consumption and support sustainable human development. This study investigates the critical role of research and development (R&D) in promoting renewable energy consumption and its impact on sustainable human development within the East African Community (EAC). As global climate change intensifies, the transition from conventional energy sources to renewable alternatives is essential for fostering economic growth and improving human development indicators. Despite the recognized potential of renewable energy, EAC nations face challenges, including inadequate funding for R&D, limited technological capabilities, and ineffective policy frameworks. This paper analyzes the intricate relationship between R&D investments and renewable energy adoption, utilizing a comprehensive econometric approach with data spanning from 1996 to 2021. The study employs advanced econometric estimators, including Feasible Generalized Least Squares (FGLS) and Panel-Corrected Standard Errors (PCSE), alongside robustness tests such as Driscoll-Kraay standard errors and Fully Modified Ordinary Least Squares (FMOLS). The findings reveal that enhancing R&D is vital for overcoming barriers to renewable energy implementation, ultimately contributing to sustainable development goals. The study underscores the necessity for targeted policy interventions that leverage R&D to facilitate technological advancements, improve energy efficiency, and promote equitable access to renewable energy resources in the EAC region.

Islamic Financing Mechanisms for Renewable Energy Projects: Mapping Research Trends and Future Directions

This paper discusses the emergent trends in Islamic financing mechanisms for renewable energy projects, highlights their role in promoting economic growth, and discusses sustainability. By applying bibliometric analysis, cluster analysis (VOSviewer), and co-citation analysis, this study explores literature between 2008 and 2024 on the impact of Islamic finance on renewable energy projects. Data is collected from two major databases; Scopus and Web of Science Core Collection; key trends; influential publications; and future research directions. Findings show that Islamic financing mechanisms; including green sukuk and impact investing; are essential in supporting renewable energy investments. The study identifies key contributors such as Saudi Arabia; Malaysia; UAE; and Malaysia; with research focusing on the relationship between Islamic finance; ESG performance; renewable energy; and climate change mitigation. Future research may explore the integration of digital technologies; green innovation; and technological advancements in Islamic financing for renewable energy projects. The limitations include the reliance on Scopus and Web of Science databases, with further suggestions for incorporating additional databases and expanding keyword searches. This paper contributes to a better understanding of the intersection between Islamic finance and renewable energy, hence providing a good foundation for further research and practical applications in the field.

A Comparative Analysis of Life Cycle Costs and Emissions in Mae Sariang’s Microgrid Energy Scenarios

This study evaluates the life cycle costs, net present value (NPV), and greenhouse gas (GHG) emissions of three energy scenarios for the Mae Sariang microgrid system to assess the economic and environmental impacts of different energy sources. The reliance on renewable energy has become increasingly vital in addressing energy sustainability and reducing carbon footprints. The analysis reveals that Scenario I, primarily utilizing solar energy, achieved the lowest life cycle cost per kilowatt-hour (kWh) at 6.18 and the highest NPV of 226,583,036 baht, while also producing the fewest GHG emissions at 21,239 kgCO₂e/year. In contrast, Scenario II, dependent on grid electricity, incurred the highest costs and emissions at 25,180 kgCO₂e/year, reflecting its reliance on higher-carbon sources. Scenario III, which incorporates diesel generation, demonstrated moderate emissions at 22,240 kgCO₂e/year but resulted in a negative NPV of -2,690,330 baht due to high fuel expenses. The findings highlight that prioritizing renewable energy sources not only enhances financial viability but also minimizes environmental impact. Therefore, the study concludes that adopting a renewable-focused approach in microgrid systems offers substantial economic and ecological benefits. Policy recommendations include incentivizing renewable energy integration, promoting energy efficiency measures, and developing supportive frameworks to reduce reliance on high-carbon electricity, ultimately enhancing the feasibility and sustainability of energy systems.

Native Lignin Migration and Clustering in Wood: Superhydrophobic, Antimold, and Tribonegative Layers for Rain‐Driven Electrification

AbstractThe development of wood‐based materials for energy harvesting, particularly triboelectric nanogenerators (TENGs), has recently attracted significant attention. Traditional strategies for wood‐based TENG primarily rely on delignification to enhance tribo‐positivity, overlooking the intrinsic potential of lignin and necessitating the use of fluoropolymers to maintain performance. In this study, the native lignin within the wood matrix is used to create a superhydrophobic, fully wood‐based tribonegative material (referred to as Lig‐wood), functioning as a liquid–solid triboelectric nanogenerator (L–S TENG) upon contact with water. Through a process of pretreatment and in‐situ regeneration, lignin undergoes migration, assembly, and redistribution within the wood's hierarchical architecture. This results in enhanced hydrophobicity (water contact angle 148°) and efficient surface charge transfer. The morphological and chemical changes significantly boost Lig‐wood's tribonegative performance, achieving a 7.5‐fold increase in voltage and a 6‐fold increase in current compared to unmodified wood. The Lig‐wood powers LEDs and digital timers under simulated rainfall, demonstrating its functionality as green energy harvesting material. Importantly, the surface‐localized lignin imparts self‐cleaning and antimold properties, supporting the potential for long‐term, outdoor use. By leveraging the inherent functionalities of lignin, this approach presents a sustainable strategy for rain‐driven energy harvesting, representing a significant advancement in green and renewable energy technologies.

How ICT Investment and Human Development Accelerate Renewable Energy and Environmental Progress?

Addressing environmental challenges relies on fostering pro-environmental behavior within society. Human development and ICT investment are crucial to comprehend their roles in promoting environmentally conscious actions. In this context, the present research investigates the relationship between human development, ICT investment, and pro-environmental behavior in the context of China. Employing a classy nonlinear NARDL model, the study explores the asymmetric impact of human development and ICT investment on pro-environmental behavior indicators. The results show that positive changes in human development and ICT investment promote renewable energy consumption and reduce CO2 emissions. In contrast, the negative change in the human development index does not significantly impact Renewable energy consumption, while it increases CO2 emissions. On the other hand, the negative change in ICT investment reduces renewable energy consumption and increases CO2 emissions. Policymakers should prioritize enhancing human development and encouraging sustainable ICT investment in China.

MPPT Performance Analysis for PV Energy Harvesting Using Grey Wolf Optimization (GWO) Algorithm

Renewable energy is a key solution to meeting the growing demand for electricity while reducing reliance on non-renewable sources. Among various renewable technologies, photovoltaic (PV) systems are widely used in solar power plants (PLTS) to harness solar energy. However, PV efficiency is affected by environmental factors such as fluctuating solar irradiance and temperature, which cause instability in output voltage and power. To address these issues, Maximum Power Point Tracking (MPPT) techniques are applied to optimize power extraction. This study proposes the Grey Wolf Optimization (GWO) algorithm for MPPT and evaluates its performance through MATLAB/SIMULINK simulations under varying irradiance and temperature conditions. Inspired by the hunting behavior and social hierarchy of grey wolves, GWO dynamically adjusts the converter's duty cycle based on real-time voltage and current measurements to maximize output power. The study focuses on PV systems in Malang, Indonesia, and compares GWO with the Particle Swarm Optimization (PSO) method in terms of accuracy and stability. The results indicate that increased solar irradiance substantially enhances PV power output, while rising temperatures tend to reduce efficiency. The GWO algorithm achieves an average tracking accuracy of 94.5632%, slightly lower than the 96.9851% achieved by PSO. However, GWO demonstrates superior performance in terms of stability, with faster convergence and reduced oscillations during the tracking process. A comparison of system performance before and after applying the GWO method shows notable improvements in tracking consistency and power extraction efficiency, especially under dynamic environmental changes. The novelty of this study lies in its use of real-world environmental data collected over a 30-day period in a tropical setting, which is rarely addressed in previous GWO-based MPPT research. These findings highlight the potential of the GWO-based MPPT strategy to enhance PV system reliability and efficiency in real-time renewable energy applications.

An In-Depth Analysis of Sustainable Sourcing Practices and Their Environmental Impact in the Cosmetics Industry: A Case Study of L’Oréal USA and Unilever USA

The pursuit of enhanced appearance has driven the evolution of beauty practices from natural ingredients to processed and packaged products. However, this progression has significantly impacted the environment through pollution and waste. The cosmetics business has a significant environmental impact because it relies on natural resources, energy consumption, and packaging waste. An increasing number of consumers are demanding sustainable products. Thus, significant cosmetics businesses like Unilever and L’Oréal have committed to more sustainable sourcing procedures. This study looks at Unilever and L’Oréal’s sustainability activities and ambitions for sourcing cosmetic ingredients in the U.S. between 2019 and 2023. It concludes that both businesses have made significant strides. Unilever has committed to sourcing all of its agricultural raw materials sustainably by 2025 and to using plastic packaging that is fully recyclable or compostable by 2030, while L’Oréal wants to source all of its palm oil sustainably by 2025 and reduce emissions by 25% per finished product by 2030. The study highlights that both companies have implemented various strategies, including partnerships with sustainable suppliers, renewable energy use, reduced packaging waste, and deforestation-free certifications. Despite these developments, problems with waste management, transparency, inefficient corporate social responsibility (CSR), increasing the price of sustainable components, and satisfying consumer demand still exist. The study highlights that despite notable advancements and industry acclaim for their sustainability initiatives, Unilever and L’Oréal still encounter challenges in pursuing more sustainably sourced cosmetic ingredients. Their progress is a benchmark and inspiration for the broader cosmetics industry, demonstrating a commitment to a sustainable future.

IOT Based Automatic Plant Irrigation System

The IoT-based automatic plant irrigation system is a sustainable solution that combines solar energy and smart technology to optimize water usage and reduce manual intervention. IoT sensors monitor soil moisture levels, automating irrigation based on real-time data. Solar panels provide renewable energy, while Amazon Alexa integration enables voice-controlled operation and system monitoring. This innovative approach enhances agricultural productivity, conserves resources, and promotes eco-friendly farming practices. Keywords: IoT, automatic irrigation, solar panels, Amazon Alexa, smart agriculture, sustainable farming, automation, renewable energy.

Low-Carbon Energy Risk and Renewable Energy Development: Insigths from Method of Moments Quantile Regression

The current work investigates the effect of low-carbon energy risk on renewable energy development for the first time in the literature. The annual data used in the work contains the sample of 137 countries. For the empirical estimations, Method of Moments Quantile Regression (MMQR) is applied, considering the heteroscedastic nature of the data and energy markets as well. The results provide valuable findings that a decrease in low- carbon energy risk leads to a rise in renewable energy across all the quantiles. Moreover, the results remain robust when the sample is divided into developed and developing countries, further validating theoretical linkage. Policymakers should consider the components of low-carbon energy risk in the decision-making process to enhance renewable energy development.

Issues in Business Development and how to Develop Business in Qatar

The growth of business in Qatar is the country's rapidly expanding infrastructure. The government's massive investments in transportation, telecommunications, and energy infrastructure have not only improved the country's connectivity but also created opportunities for businesses to leverage these assets for growth. This has led to the emergence of new industries and sectors, such as logistics, technology, and renewable energy, which are poised to play a significant role in Qatar's economic development. As a result, the country has been keen on diversifying its economy and reducing its dependency on oil and gas revenues. One of the key strategies to achieve this goal has been business development, with an emphasis on attracting foreign investments, fostering entrepreneurship, and creating a conducive environment for businesses to thrive. However, despite the government's efforts in promoting business development in Qatar, there are still several challenges and obstacles that need to be addressed to realize its full potential. On this premise, the paper aims to examine the issues related to business development and how businesses can be developed in Qatar. The paper shows that Qatar's commitment to leveraging technology and innovation in key sectors of its economy has positioned the country as a leader in the region and a hub for technological advancement. By embracing technology and innovation, Qatar is driving growth, enhancing competitiveness, and building a sustainable economy for the future. Also, while Qatar has enjoyed relative stability in recent years, geopolitical tensions in the region and fluctuations in oil prices can impact the country's economy and business environment. This can create uncertainty for businesses and investors, making it difficult to plan for the future. The paper concludes that Qatar presents a wealth of opportunities for businesses looking to expand into the Middle East market. The country's stable political environment, strong economy, and strategic location make it an attractive destination for foreign investors. By implementing the listed recommendations (Consider setting up a local presence; Attending industry events and trade shows; Adapt to local customs and traditions) and strategies, businesses can develop a strong presence in Qatar's market and capitalize on the country's lucrative business opportunities. With careful planning, cultural sensitivity, and a commitment to quality, companies can achieve sustainable success and growth in the region.

Exploring the Relationship between Economic Growth, Renewable Energy and Carbon Emissions: A Case of Cuba

In the modern era, balancing economic growth and environmental sustainability has become one of the greatest challenges, especially for the emerging nations. As a case of examining the decoupling of economic growth from carbon emissions, Cuba’s historical reliance on fossil fuels, especially during the U.S. embargo, is quite interesting. In this article we have examined the impact of economic growth upon the carbon emissions of Cuba. We extracted annual time series data for the dependent variable (Carbon Emissions) and explanatory variables (Economic Growth and Renewable Energy Consumption) for the period spanning from 1990 to 2020. To determine the long run relationship between the variables, we used Auto regressive distributed lags (ARDL) bounds test of co-integration. The empirical findings revealed the existence of a long-run relationship among the variables of the model. We found that economic growth has a significant positive impact upon carbon emissions; furthermore, there is also a bi-directional causality between the economic growth and the carbon emissions. This research could help the policymakers to establish novel and efficient policies to tackle the environmental issues and move closer to the attainment of sustainable development goals.

Regulatory Impacts on the Development of Solar Industry in China: A Policy Analysis

Traditionally, China's energy structure has been dominated by coal, but China is trying to make transition towards renewable energy sources such as solar, wind, and hydroelectric power. Among these energy, solar energy plays a crucial role due to its scalability and reduction of cost. This study explains the impact of government policies on the development of solar industry and how China become a global leader in this sector, and strategies employed to fix the problem of overcapacity. By employing a mixed-method approach, including current status of the solar industry, case studies, and policy analysis, this paper examines the impact of policy frameworks, both historical and contemporary policies. It aims to provide insights for policymakers and industry stakeholders through evidence-based recommendations designed to optimize policy frameworks, support industrial growth, and promote sustainable development. Lastly, this research seeks to give a broader understanding of how government policies can nurture a resilient and competitive solar industry, thereby promote the development of renewable energy technologies and environmental management.

Performance Investigation of Renewable Energy Integration in Energy Management Systems with Quantum-Inspired Multiverse Optimization

The study introduces a novel standalone hybrid Energy Management System that combines solar PV, wind energy conversion systems, battery storage, and microturbines in order to provide reliable and efficient power under various operating conditions. The developed Quantum-Inspired Multiverse Optimization (QI-MVO) algorithm has thus far allowed for a remarkable efficiency of 99.9% and a 40% reduction in power losses when compared to conventional approaches. A rather speedy convergence to best solutions is exhibited by the methods, which take about 0.07 s for calculation, hence ensuring accurate optimization in complex energy systems. The QI-MVO-based EMS brings in improved reliability and optimal utilization of the system through balanced energy distribution and by maintaining system operational stability. In conclusion, the present work showcases QI-MVO as a sustainable and scalable energy management solution, which sets the stage for optimization strategies wherein hybrid energy management assumes a very important role.

Decoding the Online Reputation of China's Energy Storage Products in the Cross-Border E-Commerce B2B Market

As a core technological solution for balancing the intermittency of renewable energy, energy storage products play a pivotal role in global energy transition and carbon neutrality initiatives. China, leveraging its competitive advantages in lithium battery technology and integrated supply chains, has established dominance in the global energy storage market. However, escalating trade barriers and diminishing cost advantages are compelling enterprises to seek breakthroughs through cross-border e-commerce. This study focuses on deciphering the online reviews for Chinese energy storage products in B2B cross-border e-commerce markets, addressing three research questions: (1) Sentiment distribution characteristics of B2B users on Alibaba International and Amazon Business platforms; (2) Demand disparities between Regional Comprehensive Economic Partnership(RCEP) and non-RCEP procurement entities; (3) Common pain points reflected in platform user reviews. Employing TextBlob sentiment analysis and Biterm Topic Model (BTM) text mining techniques, the author analyzed 34,073 user reviews from Alibaba International and Amazon Business spanning 20182024. Key findings reveal that Median sentiment scores of 0.457 for Alibaba International and 0.229 for Amazon Business. Non-RCEP buyers prioritize brand reputation and transactional efficiency, while RCEP counterparts emphasize technical specifications and long-term partnerships. Logistics efficiency and product performance emerge as universal concerns globally, with heightened severity in emerging markets due to infrastructure limitations. The study proposes actionable strategies, including differentiated branding frameworks, logistics optimization protocols, and localised innovation pathways, to empower Chinese energy storage enterprises in overcoming trade barriers and enhancing global competitiveness. These insights provide theoretical foundations and practical benchmarks for policymakers and industry stakeholders navigating the evolving B2B cross-border e-commerce landscape.

Analysis of Wind Energy Potential On Nusa Penida Island Using The Weibull Distribution: Evaluation of Power Density and Intermittency

Nusa Penida Island faces increasing energy demands driven by tourism and development, highlighting the need for sustainable energy solutions. While previous wind studies in Indonesia have primarily focused on larger islands, this research evaluates Nusa Penida’s wind energy potential using the Weibull distribution method for power density and intermittency analysis. Unlike prior studies, this research incorporates seasonal variations and probabilistic modeling to provide a more accurate assessment of wind intermittency. Statistical analysis of 2019–2020 wind speed data from NASA Power reveals stable wind conditions, with an average power density of 104 W/m², making it suitable for medium scale wind energy projects. Peak wind speeds occur mid year, optimizing conditions for energy harvesting, while intermittency analysis indicates that wind speeds fall below 3 m/s approximately 30% of the time, emphasizing the need for energy storage or hybrid systems. This research quantifies the impact of intermittency on energy planning, offering a data driven approach to support Indonesia’s renewable energy diversification and reduce reliance on fossil fuels. The findings establish Nusa Penida’s feasibility for wind energy deployment, contributing to enhanced energy resilience in remote island communities.

Application of Artificial Intelligence in Wind Power New Energy Grid Integration Planning and Scheduling

Wind power integration into existing energy grids presents significant challenges in managing variable energy generation, grid stability, and scheduling optimization. Factors such as fluctuating wind power output, conventional grid generation, battery storage capacity, and varying load demands influence system performance in achieving effective energy distribution and integration. A novel bio-inspired resilient manta ray foraging (Res-MRF) optimization algorithm is applied to address these challenges in the actual-time planning and scheduling of power generation, storage, and load management in a wind-powered new energy grid. Initially, data were collected that comprise power generated by wind turbines. Then preprocessing using Z-score normalization is performed to standardize data effectively. Further, a maximum power point tracking algorithm based on the wind speed values from the dataset is implemented to predict the maximum power output. The suggested method is implemented using Python software. Finally, the proposed Res-MRF-based approach intelligently allocates resources, balances grid load, and reduces operational costs while ensuring sustainable energy delivery and user demand satisfaction. Extensive simulations validate the efficacy of the Res-MRF technique, demonstrating efficient reduction in total energy costs and improved grid efficiency, while ensuring that renewable energy resources are effectively utilized. These results highlight the potential of artificial intelligence-driven optimization in enhancing the integration of wind power into new energy grids.

Analysis of Photovoltaic Panel Performance Integrated with the Grid in a Load-Sharing Scheme

This paper examines the performance of photovoltaic panels integrated into the electrical grid in a load-sharing scheme at Darool Ehsan Muhammadiyah Senior High School, Sragen. The study is part of Universitas Muhammadiyah Surakarta's community service program focused on renewable energy development in educational environments. Unlike previous studies relying on simulated data, this research uses real-time primary data from direct measurements of photovoltaic power production and grid electricity consumption over a specific period. The study’s innovation lies in analyzing the photovoltaic system within a tropical climate-based load-sharing scheme and comparing energy usage when connected to photovoltaic panels versus when disconnected. It also evaluates the impact of reducing solar energy consumption from the grid. The collected data reveal an estimated daily load of 49.89 kWh, with PLN-supplied energy consistently exceeding inverter-supplied energy. Integration of photovoltaic panels into the grid reduces PLN electricity consumption by up to 30% during optimal sunlight periods, achieving an average system efficiency of 15%. This research offers valuable insights into the potential and challenges of implementing photovoltaic panels in educational settings, emphasizing the importance of climate considerations in system design and optimization. Future studies will focus on techno-economic evaluations of solar power installations and harmonic distortion (THD) analysis for larger-scale implementations.

Economic Analysis, Innovative Educational Models and Pragmatic Sustainability: The Case Study of a Photovoltaic System on a Public Building

The development of renewable energy has changed the utility sector, leading to a change in the interests of companies operating in the sector. The prosumer is a new emerging figure that can enable citizens and businesses to be an integral part of this change. In this context public administrations can play a key role and this study aims to assess the profitability of a photovoltaic (PV) system located in a public building (secondary school) in Italy. This analysis is integrated within an innovative teaching model that aims to stimulate the problem-solving competence of university students. The results show that the implementation of the PV system is characterised by important economic results with profits ranging from 2866 to 5670 €/kW in a 97 kW plant and from 2065 to 4012 €/kW in a 168 kW plant with a fundamental role played by the percentage of self-consumption and the avoided cost in the bill. The emission reduction in the 1st-year ranges from 56.6 to 98 tCO2eq. Pragmatic sustainability can support the decarbonisation of our energy system by involving young people in the choices and favouring social models that reward their skills.

Examining the Environmental Impact of High-Powered Computing

In recent years, the popularity of high-performance computing (HPC) has made its environmental impact increasingly prominent. The operation of HPC equipment generates ecological problems such as air pollution, water wastage, and solid waste pollution, posing a serious threat to ecosystems and human health. This study aims to develop a broad model to assess the environmental impacts of carbon emissions, cooling water resources required, and e-waste generated during HPC operation. The ecological effects of HPC in terms of atmosphere, water resources, and solid waste were assessed through the model. We suggest technical and policy solutions designed to enhance energy efficiency, boost the share of renewable energy sources, refine the placement of data centers, encourage sustainable supply chains, and strengthen e-waste recycling programs. It highlights the criticality of the environmental impact of HPC and presents our research insights and recommendations to support global efforts to achieve sustainable development.