Renewable Energy Growth Research Articles

Model predictive control of multilevel inverter used in a wind energy conversion system application

The rapid growth of renewable energy, particularly wind energy, has significantly contributed to global electricity generation, with global renewable energy capacity reaching an all-time high of 3870 gigawatts (GW) in 2023. However, ensuring high power quality for grid integration remains crucial for wind energy's role as a leading source in the energy transition. This necessitates the development of advanced Wind Energy Conversion Systems (WECS) capable of regulating current, voltage, and frequency to ensure power quality. This work proposes a novel predictive control strategy for multilevel inverters in WECS to achieve a total harmonic distortion (THD) below 5% in the generated electrical power. The proposed predictive control algorithm is presented and implemented in a WECS simulation with a multilevel inverter. The performance of the proposed system is evaluated through simulations using MATLAB/SIMULINK. Our results demonstrate that the predictive control approach outperforms traditional controllers for multilevel inverters in terms of output voltage, harmonic reduction, execution time, and overall WECS control.

RENEWABLE ENERGY CONSUMPTION, FINANCIAL DEVELOPMENT AND ECONOMIC GROWTH A COMPARATIVE ANALYSIS OF BRICS AND MINT

This study examined the relationship between renewable energy, financial development and economic growth in BRICS and MINT nations. The data used for the study was obtained from the World Bank development indicators from 1990-2022. The data was analysed using panel regression analysis(Pooled OLS) and Fixed Effects as well as the Dumitrescu-Hullin (2012) test for causality the result of the analysis showed that broad money per GDP had a positive impact on economic growth in MINT countries while it had a negative impact on economic growth BRICS nations. Market capitalisation per GDP was found to have a positive and significant impact on economic growth in BRIC nations Renewable energy on the other hand had a negative impact on economic growth in MINT countries while it had a negative impact on economic growth in BRICS nations. Renewable energy also had a unidirectional causality relationship with economic growth. KEYWORDS: Renewable Energy, Financial Development, Economic Growth, Sustainable Development

Relationship among micro-pollutants, economic growth, renewable energy, nanotechnology and ecological foot prints of China: evidence from panel data analysis.

An important concern is the availability of clean drinking water, which is an essential need for human survival. This issue arises due to the existence of hazardous micropollutants originating from various emission sources. Nanotechnology aids in the mitigation of micropollutants by assimilating and counteracting their effects, hence diminishing their influence on water and other ecosystems. The study investigates the relationship between nanotechnological progress, the adoption of renewable energy, environmental consequences, and economic growth in China, using the Environmental Kuznets Curve theory as a conceptual framework. The study employs panel cointegration tests to analyze structural breaks from 2000 to 2020. Nanotechnology is expected to reduce environmental degradation and the presence of micro-pollutants by increasing the use of renewable energy and promoting energy conservation. Nanotechnology is crucial for mitigating micro-pollutants and advancing sustainable development in this specific context. However, the literature also highlights the harmful consequences of nanoparticle emissions caused by nanotechnology on human and environmental health for a long duration, requiring more examination. This research is the first empirical inquiry into the relationship between improvements in nanotechnology, the use of renewable energy, economic growth, and ecological effect, all within the context of the Environmental Kuznets Curve theory. The results confirm the successful incorporation of all components with a focus on long-term outcomes. The findings suggest that the EKC hypothesis is relevant in China. In China, advancements in nanotechnology have a moderating effect on environmental degradation. The use of renewable energy sources in China enhances environmental circumstances. Given the offered empirical evidence, it is advisable for the government to have a leading role in the development of innovative nanotechnologies that have low emissions of nanoparticles. By using this approach, it will be possible to encourage the conservation of energy and the use of renewable sources in a more secure way, hence improving the effectiveness of sustainable development initiatives.

Financing Management and Social Information

China's robust renewable energy sector expansion has spurred academic inquiry into the underlying driving forces. Recent studies have highlighted the correlation between the growth of renewable energy and project financing and the pivotal role of information management in financing. Based on this, we use business data from Chinese listed companies from 2007 to 2021 to investigate the relationship between renewable energy business development and financing. Furthermore, we introduce social and enterprise information to explore their impact on this relationship. Our findings reveal that: (1) Expansion of renewable energy businesses enhances fund availability mainly through endogenous financing. (2) “Anti-dumping and countervailing” (“Double-anti”) investigations significantly hinder financing for expanding renewable energy businesses, while industrial policies mitigate these effects. (3) Complex international backgrounds combined with domestic market-government interactions promote renewable energy enterprises to apply information management technology for financing.

Renewable Electricity and Green Hydrogen Integration for Decarbonization of “Hard-to-Abate” Industrial Sectors

This paper investigates hydrogen’s potential to accelerate the energy transition in hard-to-abate sectors, such as steel, petrochemicals, glass, cement, and paper. The goal is to assess how hydrogen, produced from renewable sources, can foster both industrial decarbonization and the expansion of renewable energy installations, especially solar and wind. Hydrogen’s dual role as a fuel and a chemical agent for process innovation is explored, with a focus on its ability to enhance energy efficiency and reduce CO2 emissions. Integrating hydrogen with continuous industrial processes minimizes the need for energy storage, making it a more efficient solution. Advances in electrolysis, achieving efficiencies up to 60%, and storage methods, consuming about 10% of stored energy for compression, are discussed. Specifically, in the steel sector, hydrogen can replace carbon as a reductant in the direct reduced iron (DRI) process, which accounts for around 7% of global steel production. A next-generation DRI plant producing one million tons of steel annually would require approximately 3200 MW of photovoltaic capacity to integrate hydrogen effectively. This study also discusses hydrogen’s role as a co-fuel in steel furnaces. Quantitative analyses show that to support typical industrial plants, hydrogen facilities of several hundred to a few thousand MW are necessary. “Virtual” power plants integrating with both the electrical grid and energy-intensive systems are proposed highlighting hydrogen’s critical role in industrial decarbonization and renewable energy growth.

Multi-Stage Coordinated Planning for Transmission and Energy Storage Considering Large-Scale Renewable Energy Integration

Due to the large-scale integration of renewable energy and the rapid growth of peak load demand, it is necessary to comprehensively consider the construction of various resources to increase the acceptance capacity of renewable energy and meet power balance conditions. However, traditional grid planning methods can only plan transmission lines, often resulting in low utilization rates of newly constructed lines. Additionally, static planning methods can only address single-target scenarios and cannot cope with dynamic growth in load and renewable energy. To address these issues, this paper proposes a multi-stage collaborative planning method for transmission networks and energy storage. This method considers the non-line substitution effect of energy storage resources and their characterization methods. It establishes the coupling relationship between resources across different planning stages to achieve coordinated multi-stage planning for transmission networks and energy storage. Based on the IEEE-24 node system and a case study in a northern province of China, the results show that the proposed method reduces investment costs by approximately 30% compared to static planning methods and by about 7.79% compared to conventional grid planning methods. Furthermore, this method can accommodate more renewable energy.

Elimination of power and frequency oscillations for AC microgrid with parallel virtual synchronous generator and synchronous generator

The integration of conventional synchronous generators (SGs) and virtual synchronous generators (VSGs) in microgrids (MGs) is increasingly common due to the growth of renewable energies. However, demand fluctuations and grid faults can pose significant challenges to the stability of the MG, causing system frequency and active power oscillations. This study proposes control approaches for an isolated/islanded AC MG that consists of an VSG and an SG to mitigate power and frequency oscillations. The proposed methods utilize the VSG’s adjustable damping coefficient, which is determined by intelligent controls. The proposed strategies significantly reduce power fluctuations by 53% and frequency deviations by 75%, thereby improving system stability and reliability. The suggested controllers use short-term large damping to effectively amplify the system’s AC frequency dynamic response and enhance power delivery across different power-sharing modes. The controllers do not require additional communication infrastructure and rely solely on the local AC frequency for feedback. Furthermore, a novel synchronization mechanism with positive effects on system stability is presented.

Innovating for sustainability: exploring the synergy between international digital trade, appeal mechanisms, renewable energy, and economic growth on ecological footprint in BRICST economies

Innovating for sustainability: exploring the synergy between international digital trade, appeal mechanisms, renewable energy, and economic growth on ecological footprint in BRICST economies

Prediction of short circuit current of wind turbines based on artificial neural network model

The growth of renewable energy on a global scale is making significant strides in power plants. This is due to the increasing concern about climate change, the rising demand for electricity, and the necessity to reduce reliance on fossil fuels. Ensuring the successful integration of new energy resources into the existing network is just as crucial as it requires the system to be reliable and adaptable. For instance, wind energy, which is one of the renewable sources, has an intermittent nature that necessitates the ability to synchronize its actions to achieve the desired system performance. The objective of this study is to utilize a new neural network system to calculate the short circuit current of power plants. Specifically, the focus is on identifying and categorizing the short circuit faults that occur between the stator coils of the squirrel cage induction generator used in wind power generation. To achieve this, a system was developed to simulate turbine data. Subsequently, four feature extraction techniques and machine learning algorithms were employed to enable early detection of short circuit faults. The numerical results obtained from the simulation demonstrated the high efficiency and accuracy of the proposed model.

Assessing the Relationship between CO2 Emissions, Renewable Energy, Trade Openness and Economic Growth: MENA Countries Analysis

Assessing the Relationship between CO2 Emissions, Renewable Energy, Trade Openness and Economic Growth: MENA Countries Analysis

Renewable Energy and Economic Growth in Saudi Arabia: Evidence from ARDL model

Renewable Energy and Economic Growth in Saudi Arabia: Evidence from ARDL model

Forecasting synergistic pathways between rare earth elements, renewable energy, and product and economic complexities in achieving a low-carbon future

Recent decades have witnessed an unprecedented transformation in the global energy landscape, driven by environmental concerns and the quest for sustainable economic growth. As the world grapples with the urgent need for decarbonization, the utilization of renewable energy technologies with the instrumental role of rare earth elements (REEs) has come to the forefront. However, empirical investigations into their synergistic pathways for product and economic complexities concerning achieving a low-carbon future remain scarce. Therefore, we forecast synergistic pathways between the REE supply, renewable energy, economic and product complexities, and GDP growth using a panel dataset of 11 REE-producing countries from 1990 to 2023. We used Common Correlated Effects and Temporal Causal Models as primary methods to estimate panel long-run elasticities and subsequently forecast mutual causal synergies between the variables. The results indicated that REE supply led to renewable energy and economic growth that further elevated the countries’ product and economic complexities rankings. GDP growth increased REE production, economic complexity, and renewable energy directly, and consequently, product complexity and REE production through them. This underscores the positive role of REE production coupled with renewable energy technologies in achieving a low-carbon future based on economic diversification, enhanced industrial capabilities, and technological sophistication.

Green finance and renewable energy growth in developing nations: A GMM analysis

This research aims to examine the interrelationship between green finance and its influence on the renewable energy industry in a sample of 30 developing nations from 1990 to 2018. The main aim of this study is to investigate the interconnected effects between green bonds, investments in renewable energy, and carbon markets, with a specific emphasis on the influence of the banking system in shaping these interrelationships. To accomplish this objective, the Generalized Method of Moments (GMM) is utilized to examine the data and comprehend the intricate interrelationships among the variables. The emergence of green finance offers a favourable prospect for tackling environmental issues while concurrently fostering sustainable economic development. Nevertheless, the degree to which it impacts the adoption of renewable energy and carbon markets has yet to be thoroughly investigated, especially in developing nations. This study seeks to provide insights into the factors that influence the development of green finance and its implications for investments in renewable energy by examining a diverse group of 30 emerging countries. The findings of this research provide compelling revelations regarding the interdependence between green finance and its influence on the renewable energy industry. The results underscore the notable contribution of the banking sector in enabling the transfer of capital into sustainable energy initiatives via the utilization of green bonds. Furthermore, we have discovered dynamic spillover effects between green bonds, renewable energy investments, and carbon markets. These financial mechanisms have the potential to influence each other within the framework of sustainable development. A comprehensive comprehension of the complex interconnections among green finance, renewable energy, and carbon markets is imperative for policymakers, investors, and financial institutions seeking to promote sustainable practices and efficiently allocate resources. This research adds to the expanding corpus of literature on green finance and offers significant implications for advancing a more environmentally friendly and sustainable future in developing nations.

Social impact of decarbonization objectives through smart homes: Survey and analysis

The technological development and economic growth of renewable energy are the key solution for almost full decarbonization of the energy systems. The sustainability and energy efficiency, artificial intelligence and connectivity will be the determining elements towards reaching this ambitious goal. Household appliances and tools for controlling energy consumption, temperature, lighting, etc. In the smart home will play a key role to increase awareness of families' energy consumption. IoT (Internet of Things) devices for the smart home allow us to monitor consumption and pay attention to efficiently energy use. However, savings are not the only important element of the smart home. Together with the digital control of the home these are elements that include a fundamental dimension: decarbonization, which is the cornerstone of the energy transition, which must involve an epochal change of mentality to our society where digitalization and people's well-being meet. The paper deals with social analysis of large cities population perception on integrating renewable energy sources and necessary devices to transform existing houses in smart homes towards economic wellbeing and decarbonization of the energy sector. Different classes of respondents were interviewed – owned and rented fome, rural and urban inhabitants, different segments of age, various number of inhabitants in urban areas and the capital, women and men, high-income and low-income, different levels of education – to support or disregard smart home technological development and reveal the different perception towards further usage of smart devices for daily benefits.

Certification of MPC-based zonal controller security properties using accuracy-aware machine learning proxies

The fast growth of renewable energies increases the power congestion risk. To address this issue, the French Transmission System Operator (RTE) has developed closed-loop controllers to handle congestion. RTE wishes to estimate the probability that the controllers ensure the equipment’s safety to guarantee their proper functioning. The naive approach to estimating this probability relies on simulating many randomly drawn scenarios and then using all the outcomes to build a confidence interval around the probability. Although theory ensures convergence, the computational cost of power system simulations makes such a process intractable.The present paper aims to propose a faster process using machine-learning-based proxies. The amount of required simulations is significantly reduced thanks to an accuracy-aware proxy built with Multivariate Gaussian Processes. However, using a proxy instead of the simulator adds uncertainty to the outcomes. An adaptation of the Central Limit Theorem is thus proposed to include the uncertainty of the outcomes predicted with the proxy into the confidence interval. As a case study, we designed a simple simulator that was tested on a small network. Results show that the proxy learns to approximate the simulator’s answer accurately, allowing a significant time gain for the machine-learning-based process.

Comparative analysis of environmental sustainability indicators: Insights from Japan, Bangladesh, and Thailand

This study analyses environmental sustainability indicators (ESIs) and explores their governance challenges in developing countries (Bangladesh and Thailand) and advances possible remedies in light of the practices of a developed country (Japan). A comparative analysis of countries' performance based on the ESIs could help identify useful practices from countries with high ESI to improve the poor ESI countries. While it is broadly understood that renewable energy and effective governance support environmental sustainability, our findings extend this knowledge by detailing how these factors interact specifically within the contexts of developed and developing nations. The analysis delineates the complex relationship between GDP growth, fossil fuel reliance, and sustainability efforts, offering a detailed examination of the variance in ESI performance across these countries. Beyond established notions, this study empirically validates the relationships between environmental sustainability (ES) and its influencing factors, providing a country-specific analysis that emphasizes the differential impact of renewable energy adoption, governance quality, and economic policies on environmental sustainability in Japan, Bangladesh, and Thailand. The results also revealed that Bangladesh's performance in terms of majority ESIs ranges from bad to worse, while Japan exhibits good performance in all its ESI indicators except for emissions. Thailand's ESI performance indicates its vulnerability to climate disasters and slow growth of renewable energy. The ESI measures of Thailand have shown its susceptibility to climate-related calamities and a slowdown in the rate of renewable energy implementation. A noticeable discrepancy in the execution of regulatory frameworks was noted between developing countries, such as Bangladesh, and industrialized ones, such as Japan. The outstanding results of Japan's ESI may be credited to the successful practices of its citizens and their strong devotion to the rule of law.

Carbon reduction through renewable energy and digitalization in emerging economies: Moderating role of public debt.

Utilizing renewable energy (RE) and embracing the digital economy (DIG) can significantly contribute to achieving economic, energy, and climate goals by promoting carbon reduction. In this regard, public debt (DEB) is particularly important since it provides the funds required to achieve these goals by investing in renewable energy and digital economy projects. Thisstudy examines the impact of public debt on the link between renewable energy and carbon emissions (CE), as well as the association between the digital economy and carbon emissions in emerging economies from 2003 to 2022. The study employed cross-sectional augmented autoregressive distributed lag (CS-ARDL) estimation to check the relationship between the variables. The findings of our study suggest that the integration of renewable energy sources and the growth of the digital economy have a positive impact on reducing carbon emissions. On the other hand, public debt has a positive effect on carbon emissions. In addition, the findings support the notion that interaction terms (RE × DEB) and (DIG × DEB) have a diminishing effect on carbon emissions. It can be concluded that the reduction of carbon emissions is contingent upon the utilization of public debt to promote the growth of renewable energy and the digital economy. Based on our study, it is recommended that emerging economies' needs focus on boosting renewable energy usage and digital economy initiatives. Additionally, it is necessary for these economies to maintain a sustainable level of debt.

Analysis of renewable energy and economic growth of Germany

The study aims to investigate the effect of energy use, renewable energy consumption, nuclear energy consumption and air transport freight on CO2 emissions in Germany. Auto-regressive distributed lag (ARDL) technique was used to establish the short and long-term correlations between the dependent (CO2) and independent variables (Energy use, nuclear consumption, renewable consumption, air transport freight) on a time series data from 1970 to 2021. The results demonstrated the dependence of energy use on non-renewable energy sources by revealing a significant and positive relationship between short and long-term energy use and CO2 emissions. Similar to energy use, nuclear energy use and air transport freight was also found to be positively correlated with CO2 emissions. On the other hand, despite the fact that there is a strong negative connection between carbon dioxide emissions and renewable energy, the results reveal that the correlation between the two is not statistically significant. The study aims to investigate the effect of important economic factors on Germany’s CO2 emissions in order to move further in a sustainable manner. The data reveals an astonishing increase in the usage of nuclear energy for power generation between 1965 and 1985, which was followed by a fall in 2012 as a result of the Fukushima tragedy and growing social unease in Germany, which ultimately led to the phase-out of nuclear power. Nonetheless, BAU projections revealed that even with 200 nuclear power plants, CO2 emissions would still be reduced to 278 by 2070, in part because of the additional power produced by other energy sources.

Convergence Analysis and Testing of Regional Effects of Green Finance on The Growth of Renewable Energy

ABSTRACT A paradigm shift in energy production and use is essential in the pursuit of carbon peaking and neutrality, and the expansion of renewable energy is a cornerstone of such a shift. This article first proposes an index that comprehensively measures renewable energy development in 30 provinces in China from 2010 to 2022. Then, the σ and β convergence models are applied to investigate the uniformity of renewable energy development. Furthermore, a spatial Durbin model is estimated to examine the spatial impact of green finance on renewable energy development. The results show that from 2010 to 2020, China has witnessed a significant increase in renewable energy use in its eastern, central and western regions, with the western region accelerating faster than its counterparts. During the same period, a remarkable trend of high convergence in renewable energy development has been observed, despite a slowdown in the spatial convergence rates between the central, eastern, western and national levels. The positive spatial spillover effect of renewable energy has increased significantly. The growth of renewable energy in the region and its surrounding areas is positively influenced by the growth of green finance.

The Impact of Renewable Energy; Financial Development and Economic Growth on Carbon Emission: Empirical Evidence from Pakistan

This research investigates the impact of renewable energy; financial development, economic growth, nonrenewable energy and natural resource rents on carbon emissions in Pakistan. An annual data series ranging from 1990 to 2022 is used; while Pesaran’s et al. (2001) cointegration test is utilized and empirical results confirm that renewable energy, financial development, nonrenewable energy and economic growth have long run cointegrating relation with carbon emissions. The results further provide evidence that utilization of clean energy combats carbon emission while financial development, economic growth and unclean energy promote carbon emission. Natural resource rents also help in combating carbon emission but only in long run. These results are reliable as guided by diagnostics used in this research. This research suggests that both clean energy and natural resources must be promoted to combat carbon emissions while financial development; economic growth and nonrenewable energy may be escalated carefully because these are promoting environmental pollution in Pakistan.