Development Of Renewable Energy Technologies Research Articles

Research Review on Multi-Port Energy Routers Adapted to Renewable Energy Access

With the continuous development of renewable energy technologies, both domestically and internationally, the focus of energy research has gradually shifted towards renewable energy directions such as distributed photovoltaics and wind power. The penetration rate of renewable energy generation is constantly increasing, at the same time, the elements in the grid are becoming increasingly complex, and large-scale energy storage, as well as a variety of electricity loads such as electric vehicle charging piles and data centers are gradually appearing. Therefore, traditional distribution methods of the power grid are difficult to ensure the stable operation of the power system and cannot achieve efficient integration of renewable energy. Consequently, some scholars have proposed the concept of an energy internet. Compared to traditional power grids, the energy internet employs more comprehensive power electronics and communication technologies, enabling the interconnection of various new and traditional energy sources, and effectively integrating renewable energy. As the core device in the energy internet, the energy router plays a role in energy transformation and distribution, facilitating multi-information interconnection and multi-energy exchange within the energy internet. At the level of distribution network, the energy router can realize the efficient access of various forms of energy and the flexible control and management, which is of great significance for the optimal operation of distribution network. Against this backdrop, this paper reviews the development and current research status of energy routers, systematically analyzes the typical topologies and related control technologies of multi-port energy routers and summarizes and forecasts key issues and future development trends, aiming to provide thoughts and reference for subsequent related research.

Integrated management of abatement technology investment and resource extraction

As the need for increased renewable energy generation to meet climate goals grows, so does the demand for critical minerals in the industrial sector. This raises concerns about the availability of supply and the reliability of investment in critical minerals. Based on this, the study proposes an analytical framework for the integrated management of mineral extraction and renewable energy investments. Different from the previous strategy of separate management, this study has established an integrated model that utilizes new energy technology as the downstream application of emission reduction technology. It also utilizes copper, zinc, aluminum, rare earth elements, and other materials as the upstream raw material supply. In terms of minimizing costs, the entire supply chain process is optimized to achieve an empirical case. In addition, considering the significant uncertainty in the process of reducing emissions from new energy technologies, this study also incorporated a forward control stochastic programming method to model and solve it. We obtained confidence intervals for optimal technological investment paths and metal mining paths under various scenarios. Our findings indicate that: (1) Biomass, as a renewable energy technology with the lowest resource demand, should be prioritized for development. However, there is significant uncertainty surrounding the installed capacity of photovoltaics. (2) Copper ore reserves have little impact on the development of renewable energy technologies, while zinc ore and aluminum ore have a greater impact on wind energy and photovoltaics, respectively. (3) By optimizing the cut-off ratio of raw ore under a specific amount of ore storage, we can ensure the availability of materials needed for downstream energy technology.

Hydrophilic or Hydrophobic? Optimizing the Catalyst Microenvironment for Gas‐Involving Electrocatalysis

AbstractElectrocatalysis plays a key role in the development of renewable energy technologies. Along with the design of electrocatalysts, the microenvironment around catalytic sites has received increasing attention because it affects the distribution and mass transport of reaction species and impacts the reaction kinetics. In this Concept article, we highlight some mechanistic insights into the effect of microenvironment on gas‐involving electrocatalytic reactions, including CO2 reduction, 2‐electron oxygen reduction, and hydrazine oxidation, demonstrating their sensitivity to the wetting properties of microenvironment. For reactions with a gaseous reactant, a moderately hydrophobic microenvironment can greatly enhance the mass transport of gaseous species to accelerate the reaction kinetics while improving the stability of gas‐diffusion electrodes. In contrast, for reactions with a liquid reactant and gaseous product, a hydrophilic microenvironment improves the exposure of catalytic sites to the reactant, while a hydrophobic microenvironment benefits the reaction on the other end by accelerating the diffusion and detachment of generated gas bubbles, which would otherwise block the catalytic sites from the reactant. These understandings and insights can provide important guidelines on the control and optimization of catalyst microenvironment for the development of efficient electrolyzers.

A Comparative Analysis of Renewable Energy Policies and its Impact on Economic Growth: A Review

Renewable energy has been identified as a critical component of global efforts to address climate change, enhance energy security, and foster sustainable economic growth. As a result, many countries have implemented renewable energy policies to promote the development and deployment of renewable energy technologies. However, the impact of these policies on economic growth remains a subject of debate. This article provides a comparative analysis of renewable energy policies and their impact on economic growth. The study employs a systematic review of the literature and utilizes qualitative and quantitative methods to compare renewable energy policies and their economic impacts across different countries. The findings suggest that the impact of renewable energy policies on economic growth varies across countries and is influenced by factors such as policy design, institutional context, and economic structure. This research article finally, examined the challenges associated with implementing renewable energy policies, analyzed the implications of the findings for policymakers and further gave some potential solutions that will help the policymakers and future researchers.

China’s Road towards Decarbonization: Unrealistic Promise or a Credible Commitment?

This article argues that in low- and middle-income countries, market forces alone are structurally inadequate to spark the rapid development of renewable energy resources and initiate the replacement of obsolete technologies with cleaner technologies. Using the theoretical perspective of new structural economics as a point of departure, the examination of system-level constraints to the transformation of renewable energy reveals that active state participation in the energy sector can, on the one hand, play a key role in limiting fossil fuel consumption and, on the other, accelerate the development of renewable energy technologies. Analysis of the structural characteristics that underlie the gradual deceleration of fossil fuel extraction and the acceleration of renewable energy deployment suggests that China has laid the necessary prerequisites to reconcile policy objectives of promoting energy transformation and ensuring long-term economic growth.

Technology Diffusion and Climate Action: A Leader–Follower Model

Can a small technology-developing country increase technology diffusion to developing countries in climate action? We argue that when a country takes into account all direct and indirect benefits from pushing forward the transnational diffusion of national green technology, a free transfer may give the country a net benefit. This result is driven by the idea that technology transfer partnerships enable the countries to tailor technology development to best fit the special circumstances of receiving countries. Such decentralised cooperation can pave the way for scalable technology diffusion. The focus is on one country’s renewable energy technology development and how this can affect climate action in major developing countries such as China and India. We propose a leader–follower model between the technology-developing country and the developing country that allows complex payoffs and focuses on a situation in which one country makes a cooperative move to solve the inherent collective action problem. This effective shared learning platform has an upscaling potential, and international organisations, such as the European External Action Service, could further facilitate technology diffusion to developing countries.

Direct regeneration of spent lithium-ion batteries: A mini-review

Recycling spent lithium-ion batteries (LIB) has emerged as a pressing necessity for addressing resource shortages and mitigating environmental pollution. This article reviews the most advanced spent LIBs recycling technology, namely direct regeneration. Traditional recycling methods have problems with high energy consumption and secondary pollution. In contrast, direct regeneration extends battery life by repairing degraded cathode materials and retains battery energy to the maximum extent. This method includes technologies such as chemical lithiation and recycling of waste graphite. These innovative technologies improve battery cycle life, reduce energy consumption, production costs, and promote sustainable resource management. Direct regeneration technology provides new opportunities to reduce resource waste and reduce environmental pollution. It will promote the sustainable management of spent LIBs and support the development of future renewable energy technologies.

Analisis Efek Rumah Kaca serta Teknologi Penanggulangan Efek Rumah Kaca yang Terbarukan

Global warming is an increase in global temperature at the Earth's surface (within several thousand kilometers) compared to the normal/average value recorded over a standard period (World Meteorological Organization/WMO measurements: at least 30 years). Global warming is one of the impacts caused by the greenhouse effect. The greenhouse effect is a condition where the surface temperature of a celestial body, such as a planet or star, increases rapidly. This increase in temperature is caused by changes in the composition and conditions of the atmosphere around the object. The greenhouse effect can be caused by human activities and can occur naturally due to natural events such as forest burning due to a prolonged dry season. Basically, the greenhouse effect is very difficult to overcome, but we can reduce the greenhouse effect by using environmentally friendly energy such as renewable energy. With the rapid development of technology in this modern era, there are many renewable technologies that can be developed and utilized. This analysis aims to determine the process, causes and consequences of the greenhouse effect as well as the development and use of renewable energy technology to overcome the greenhouse effect.

Insectivorous bats alter their flight and feeding behaviour at ground‐mounted solar farms

Abstract Efforts to mitigate the climate crisis result in a green‐green dilemma: the development of renewable energy technology is required worldwide to reduce greenhouse gas emissions but can have negative impacts on biodiversity. Impacts are being documented for wind farms, but effects of solar farms (photovoltaic power stations) on habitat use of vertebrates remain extremely poorly known. Using insectivorous bats as a biological model for high trophic levels, we tested whether the presence of ground‐mounted solar farms affected flight and feeding behaviour. We assessed behaviour using three‐dimensional flight path reconstruction systems from echolocation calls, via standardised paired sampling of 16 control and 16 solar farm (treatment) sites. We quantified bat flight and feeding behaviour as flight speed, sinuosity of flight trajectories, and the probability of emission of feeding buzzes (acoustic signatures of prey capture attempts), and demonstrated that feeding was characterised by slow, sinuous flight with feeding buzzes. We recorded 15,273 three‐dimensional bat positions, resulting in 1317 flight trajectories. We found strong behavioural responses to ground‐mounted solar farms in two of three bat guilds and five of seven taxa. Specifically, bats shifted their flight towards faster (+10 to +44%) and straighter trajectories (+33%) with lower probability of prey capture attempts (−18 to −39%) at solar farms. Since these changes in flight features are explicit indicators of a decrease in bat feeding behaviour, the implementation of ground‐mounted solar farms is likely to result in reduced feeding habitat quality for bats. Synthesis and applications: The negative effects of solar farms on bat flight and feeding behaviour should be considered when solar energy projects are planned. Research is needed to understand the mechanisms underlying the effects; for example, shading underneath solar panels may reduce plant biomass and therefore insect prey availability. Until exact mechanisms are identified, efforts should be made, first to avoid building solar farms on sites with great feeding potential for bats, and second to offset residual effects by improving the surrounding land and/or solar farms to provide better foraging opportunities. In this way, populations of bats can be supported alongside the generation of renewable energy.

A new hybrid model for photovoltaic output power prediction.

Recently, with the development of renewable energy technologies, photovoltaic (PV) power generation is widely used in the grid. However, as PV power generation is influenced by external factors, such as solar radiation fluctuation, PV output power is intermittent and volatile, and thus the accurate PV output power prediction is imperative for the grid stability. To address this issue, based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), improved artificial rabbits optimization (IARO) and convolutional bidirectional long short-term memory (CBiLSTM), a new hybrid model denoted by CEEMDAN-IARO-CBiLSTM is proposed. In addition, inputs of the proposed model are optimized by analyzing influential factors of PV output power with Pearson correlation coefficient method. In order to verify the prediction accuracy, CEEMDAN-IARO-CBiLSTM is compared with other well-known methods under different weather conditions and different seasons. Specifically, for different weather conditions, MAE and RMSE of the proposed model decrease by at least 0.329 and 0.411, 0.086 and 0.021, and 0.140 and 0.220, respectively. With respect to different seasons, MAE and RMSE of the proposed model decrease by at least 0.270 and 0.378, 0.158 and 0.209, 0.210 and 0.292, and 1.096 and 1.148, respectively. Moreover, two statistical tests are conducted, and the corresponding results show that the prediction performance of CEEMDAN-IARO-CBiLSTM is superior to other well-known methods.

Integrating data mining and fuzzy decision-making techniques for analyzing the key minimizing factors of carbon emissions

The purpose of this study is to identify the key factors to minimize carbon emission problem. Within this framework, an examination has been made by considering both data mining and fuzzy decision-making techniques. In the analysis process, N-gram methodology is implemented to the abstracts of 1711 studies in the “Sciencedirect” platform and five different indicators are selected. In the proposed decision-making model, firstly, selected criteria are weighted by Spherical fuzzy CRITIC. Secondly, E7 economies are ranked with RATGOS. Thirdly, a sensitivity analysis is performed, and a comparative evaluation is conducted by MAIRCA technique. The most important originality of this proposed model is generating a new technique named RATGOS. In the literature, there are various decision-making models to rank the alternatives. However, lots of researchers criticized these approaches due to some reasons, such as using Euclidean distance by calculating the distances to the negative ideal solutions. Thus, it is seen that there is a need for a new technique that considers geometric mean in proportional concepts. To reach this objective, the RATGOS technique is introduced so that it can be possible to reach more accurate results. The findings indicate that renewable energy usage is the most critical item to overcome carbon emission problem. Therefore, some measures should be taken to increase renewable energy investments. First, governments can offer incentives for renewable energy investments. These incentives may include various incentives such as tax exemptions and low interest loans. Moreover, more research and development works are required for the development of renewable energy technologies. In this way, it can make renewable energy technologies more effective and efficient. For future research directions, an evaluation can be carried out for developed countries because carbon emissions problem also plays a crucial role for the social and economic improvements of these economies.

Comprehensive Investigation of Cooling, Heating, and Power Generation Performance in Adsorption Systems Using Compound Adsorbents: Experimental and Computational Analysis

The extensive utilization of petrochemical energy sources has led to greenhouse gas emissions, the greenhouse effect, the frequent occurrence of extreme weather events, and the severe degradation of Earth’s ecosystems. The development of renewable energy technologies has become an inevitable trend. This paper investigates an adsorption-based cooling/heating/power generation technology driven by low-grade solar thermal energy. The research results demonstrate that the adsorption performance of vermiculite compound adsorbents impregnated with LiCl solution is superior to those impregnated with CaCl2 solution, with the former exhibiting adsorption at lower p/po partial pressure ratios. Furthermore, at an adsorption bed temperature of 25 °C and a p/po partial pressure of 0.8, the adsorption cooling performance of Comp. 2 compound adsorbent impregnated with LiCl solution reaches 5760.7 kJ/kg, with a coefficient of performance (COP) of 0.75, heating performance of 9920.8 kJ/kg, COPh of 1.51, and power generation capacity of 10.6 kJ/kg. This research contributes to the advancement of sustainable energy technologies and the mitigation of environmental impacts associated with petrochemical energy sources.

Trifunctional electrocatalysts of single transition metal atom doped g-C4N3 with high performance for OER, ORR and HER

With the rapid development of renewable energy technologies, the quest for efficient and cost-effective trifunctional catalysts capable of simultaneously driving the Hydrogen Evolution Reaction (HER), Oxygen Reduction Reaction (ORR), and Oxygen Evolution Reactions (OER) has become a focal point of research. In this study, we employed first-principles calculations to investigate the catalytic activities of the synthetic material g-C4N3 as an electrocatalyst for HER, OER, and ORR by incorporating various transition metal atoms into the numerous 3 N vacancies (TM@g-C4N3) naturally occurring in its primitive structure. Our calculations reveal that Cu@g-C4N3 holds promise as a trifunctional electrocatalyst, exhibiting low OER/ORR overpotentials (ηOER = ηORR = 0.44 V) and a |ΔG∗H| value of only 0.08 eV. Furthermore, Ni@g-C4N3_S1N2 exhibits a lower OER overpotential (ηOER = 0.34 V). Bader charge analysis, charge density difference calculations, and D-band center investigations confirm that the catalytic performance is fundamentally rooted in the electronic properties of these materials. Thus, g-C4N3 embedded with transition metal atoms shows promise as an efficient electrocatalyst for OER/ORR/HER, with implications for the development of high-efficiency trifunctional electrocatalysts.

State-of-the-art review of MPPT techniques for hybrid PV-TEG systems: Modeling, methodologies, and perspectives

The development of alternative renewable energy technologies is crucial for alleviating climate change and promoting energy transformation. Of the currently available technologies, solar energy has promising application prospects owing to its merits of being clean, safe, and sustainable. Solar energy is converted into electricity through photovoltaic (PV) cells; however, the overall conversion efficiency of PV modules is relatively low, and most of the captured solar energy is dissipated in the form of heat. This not only reduces the power generation efficiency of solar cells but may also have a negative impact on the electrical parameters of PV modules and the service life of PV cells. To overcome the shortcomings, an efficient approach involves combining a PV cell with a thermoelectric generator (TEG) to form hybrid PV-TEG systems, which simultaneously improve the energy conversion efficiency of the PV system by reducing the operating temperature of the PV modules and increasing the power output by utilizing the waste heat generated from the PV system to generate electricity via the TEGs. Based on a thorough examination of the literature, this study comprehensively reviews 14 maximum power point tracking (MPPT) algorithms currently applied to hybrid PV-TEG systems and classifies them into five major categories for further discussion, namely conventional, mathematics-based, metaheuristic, artificial intelligence, and other algorithms. This review aims to inspire advanced ideas and research on MPPT algorithms for hybrid PV-TEG systems.

ROLE OF HUMAN CAPITAL, INCOME INEQUALITY AND RENEWABLE ENERGY CONSUMPTION ON CO2 MITIGATION IN MALAYSIA

The present research endeavours to investigate the interconnection among human capital, income inequality, renewable energy consumption, economic growth, and pollution. The ultimate objective is to identify effective policy approaches by uncovering empirical findings. This study employs the innovative approach of dynamic ordinary least square (DOLS) to examine data spanning from 1980 to 2018. In order to evaluate the accuracy of the DOLS estimation, we utilise the fully modified ordinary least square (FMOLS) and canonical correlation regression (CCR) techniques. In order to comprehensively investigate the association between the chosen variables, a paired Granger causality analysis was employed. Findings of this study show that using renewable energy enhances Malaysia's environmental quality, while economic growth, income inequality, and human capital all cause environmental deterioration. Therefore, it is possible that Malaysia could achieve its goal of reducing CO2 emissions and meeting its obligations under the Paris Agreement if it were to successfully adopt policy initiatives to develop human capital, increase the use of renewable energy sources, achieve a low-carbon economy, and reduce the income disparity. The research presents several new findings. The authors show that economic growth is one of the drivers of renewable energy use because it provides inputs for the development of renewable energy technology and infrastructure. But if there is pollution as a result of rapid economic growth, it will also negatively impact worker productivity. As a result, the poor get poorer, and the income inequality gap widens. This will obstruct both economic advancement and government efforts to promote the creation of renewable energy sources.

How to lead on carbon neutrality through sustainable development: A perspective on renewable energy, Information and Communication Technology (ICT), and logistics networks.

In the face of intensifying climate change-induced environmental problems, understanding the causal relationship between carbon dioxide (CO2) emissions and socioeconomic factors is crucial for achieving sustainable development. This study investigates how the causal relationships between renewable energy, information and communication technology (ICT), logistics networks, economic growth, industrialization, and energy intensity impact sustainable development using a panel dataset drawn from 104 countries and covering 2006 to 2019. Methodologically, panel unit root, panel co-integration, and Granger causality tests are employed as robust econometric techniques. The results of the panel unit root and co-integration tests confirm the stationarity of the variables and reveal significant long-term relationships among them throughout the empirical analysis period. Notably, the panel FMOLS and DOLS estimates indicate a positive effect of RE and ICT on reducing CO2 emissions, whereas GDP and energy intensity have a negative impact on CO2 emissions reduction. Moreover, the pairwise Granger causality test findings indicate bidirectional causal relationships between RE and CO2, IND and CO2, ICT and RE, IND and RE, GDP and ICT, as well as IND and ICT. The study recommends providing policy support, including for technological development and innovation, towards establishing a system that fosters sustainable development.

Observation of Support-Dependent Water Oxidation Kinetics on Molecularly-Derived Heterogeneous Ir-Oxide Catalysts

Heterogeneous water oxidation catalysis is central to the development of renewable energy technologies. Understanding the material properties that determine water oxidation activity is critically important for the design of efficient and durable water oxidation catalysts. The electronic structure and surface chemistry of the catalyst influence the accumulation of oxidative charge (holes) on catalytically active sites. Hole distribution dynamics and molecular structure of the active sites are generally accepted to jointly determine activity. However, these properties are typically inherent to materials; it has been difficult to independently tune them on most heterogeneous catalysts, hindering the development of an understanding of their relative influence. Herein, heterogenized dinuclear Ir catalysts (Ir-DHC) supported on different oxides were employed to overcome this challenge. It was found that at low temperatures (288-298 K), the photocatalytic activities of Ir-DHC on indium tin oxide (ITO) and CeO2 supports are comparable within the studied range of fluences (62-151 mW/cm2). By contrast, at higher temperatures (310-323 K), Ir-DHC on ITO exhibits a ∼100% higher water oxidation activity than on CeO2. The divergent activities under these conditions were attributed to the distinct abilities of the supporting substrates to redistribute surface holes. Specifically, ITO is relatively efficient in distributing photogenerated holes between Ir-DHC active sites, whereas CeO2 exhibits sluggish hole redistribution because of its reducibility, thereby limiting hole accumulation at Ir-DHC active sites. The temperature dependence was explained by a temperature induced switch in the rate-determining step of the reaction. These findings highlight the critical role of the supporting substrate in determining the turnover at active sites of heterogeneous catalysts.

Greenhouse gas (GHG) emissions reduction in the electricity sector: Implications of increasing renewable energy penetration in Ghana's electricity generation mix

The development and deployment of renewable energy technologies into the national electricity generation mix have high potential in the reduction of greenhouse gas (GHG) emissions in the sector, which contributes to about 40% of GHG emissions globally. Ghana through the Nationally Determined Contributions has pledged to reduce GHG emissions by 15% unconditionally, especially in the electricity sector which is one of the major contributors of GHG in the country. The study explores how the impact of increasing renewable energy penetration in the electricity generation mix will have on the greenhouse gas (GHG) emissions reduction from the sector. Four electricity supply scenarios were developed in the Low Emissions Analysis Platform (LEAP) using existing renewable energy targets identified in Ghana's Renewable Energy Master Plan. These, including, the Business as Usual (BAU), 10%, 20% and 30% renewable energy penetration scenarios were modelled to assess GHG emissions reduction up till 2030 by replacing the thermal generation sources in the electricity generation mix with equivalent amounts of renewable energy sources. Electricity demand projections for the various consumption sectors including residential, non-residential, special load as well as street lighting were made from 2016 to 2030 based on historical data. The model projected the demand for electricity to rise from 10,129.0 GWh in 2016 to 24,151.4 GWh in 2030. The cumulative demand of 237,570.5 GWh was met in all four scenarios with a total installed generation capacity of 3,794.6 MW. GHG emissions for the BAU scenario rose cumulatively to 52,545.2 thousand MtCO2eq in 2030 but reduced to 46,178.3 thousand MtCO2eq, 41,603.2 thousand MtCO2eq and 38,332.6 thousand MtCO2eq in the 10%, 20%, and 30% renewable energy penetration scenarios respectively. The result indicates that renewable energy deployment could lead to the attainment of GHG emission reduction substantially leading to minimising effects on climate change.

Meta-learning based voltage control strategy for emergency faults of active distribution networks

With the increase of energy demand and the continuous development of renewable energy technology, active distribution networks have become increasingly important. However, the introduction of a large amount of renewable energy has made the structure of ADN increasingly complex and fragile, and emergency fault caused by emergencies may often occur. Voltage control in the emergency fault event is particularly important. In this context, this paper presents a meta-learning based voltage control strategy for renewable energy integrated active distribution network. A general regression neural network is first applied to extract features from the operation data. Then, the local cross-channel interaction network is adopted to capture targeted information that is most related to emergency fault from the features and induce knowledge transfer to update the voltage control strategy. This allows the proposed strategy to make optimal decisions quickly when only limited data are available under an emergency fault that has never occurred. Comparison results based on a 69-bus distribution network validate the effectiveness and robustness of the proposed strategy.

Assessing Sustainable Impacts of Green Energy Projects for the Development of Renewable Energy Technologies: A Triple Bottom Line Approach

The escalating global concern for sustainable development necessitates an in-depth understanding of the role of renewable energy projects. Evaluating their impact on economic, environmental, and social sustainability is of significant importance. In this study, the impact of green energy projects on economic, environmental, and social sustainability across APEC countries from 2010 to 2021 is comprehensively assessed using machine learning models. The employed machine learning models revealed associations between key variables and sustainability implications of green energy projects. Renewable energy consumption emerged as a significant contributor to economic performance, scoring a compelling importance score of 0.34. Concurrently, fossil fuel energy consumption and urban population were identified as key influencers on environmental outcomes and social impacts, respectively, with importance scores of 0.36 and 0.42. The empirical evidence presented in this research underscores the pivotal role of renewable energy projects in driving economic development, counteracting environmental harm, and facilitating urban electricity access, while also noting the counteracting effect of fossil fuel consumption. The study’s outcomes are intended to guide future research directions and inform policy formulations, contributing significantly to global sustainability discourse.