Renewable Energy Growth Research Articles

Asymmetric role of energy sources on economic growth of Nigeria: Evidence from nonlinear approaches

AbstractNigeria has plentiful sources of renewable energies that are yet to be efficiently utilised, despite the country committing to net‐zero emissions by 2060, declared at the 26th United Nations Climate Change Conference in 2021, which necessitates lower consumption of fossil fuels. However, this commitment may divert the country from ending poverty as the main goal of sustainable development. This study seeks to identify the asymmetric effects of renewable and non‐renewable sources of energy used in electricity generation, along with CO2 emissions on the economic growth of Nigeria through asymmetric approaches. The findings indicate that Nigeria should mainly pursue policies concentrating on increased consumption of non‐renewable energies in the short run and more renewable energy in the long run to achieve higher economic growth. Furthermore, the long run causality results approving the only feedback relationship existing between renewable energy and economic growth, paves the way for Nigeria so that over the time the country will be able to significantly increase the share of renewable energy through which it can achieve a higher level of economic growth and approach its target of net‐zero emissions by 2060, both of which are the main goals of sustainable development.

Examining the nexus between carbon dioxide emissions, economic growth, fossil fuel energy use, urbanization and renewable energy towards achieving environmental sustainability in India

Purpose Global urbanization has accelerated due to the persistent trend of rural-to-urban migration in search of better prospects and livelihoods, which has had serious negative effects on the environment, especially in rapidly developing economies. Hence, the purpose of the study is to analyse the relationship between urbanization, economic growth, consumption of renewable energy and carbon emissions with careful examination, particularly in the context of India, where urban population growth has skyrocketed. Design/methodology/approach This study uses econometric methods like Granger causality analysis and the ARDL bound tests, to analyse the intricate relationships between the selected time series variables for India from 1970 to 2022. Findings This research highlights the difficult task of striking a balance between economic development and environmental preservation by emphasizing the crucial role that urbanization and economic expansion play in causing carbon emissions. India’s urbanization trajectory presents a significant policy problem that calls for a move towards renewable energy sources to successfully decrease carbon emissions. Moreover, this research indicates a two-way causal relationship between economic growth, urbanization and carbon emissions, pointing to the intricate interactions between these variables during the developmental stage. Research limitations/implications Despite India’s per capita emissions remaining below the global average, this study highlights the mounting policy challenge of balancing economic development with environmental sustainability as urbanization persists. The paper emphasizes the need for India to invest in renewable energy capacity to replace non-renewable sources and mitigate the carbon footprint of its growing energy demands. Collaborative efforts between India and the developed world to facilitate access to clean energy technologies are crucial for India to achieve sustainable growth in the long run. Originality/value To the best of the authors’ knowledge, existing literature predominantly focuses on investigating the relationship between renewable energy and economic growth, with only a limited number of studies exploring the impact on sustainable development to attain carbon neutrality. Furthermore, these studies have not considered the role of urbanization and non-renewable energy in addressing the challenge of sustainability issues in an emerging country like India. Hence, this study is a comprehensive study that addresses the research gap in these directions.

Exploring the Relationship Between Technological Progress, Human Capital, Political Uncertain, Energy Consumption, and Economic Growth: Evidence from a Panel Data Analysis

AbstractThis study examines the determinants of economic growth by integrating technological progress, human capital, energy consumption, and monetary policy uncertainty in an extended theoretical model. The empirical investigation covers 18 economies from 2009 to 2019 and applies the Bias-Corrected Estimation (BC) and Generalized Method of Moments (GMM) techniques. The findings reveal that while gross capital formation is a significant growth driver, financial development has no meaningful impact. Notably, intermediate education contributes positively to growth, whereas advanced education surprisingly shows a negative effect. Additionally, the results indicate a direct relationship between renewable energy consumption and growth, with oil consumption having a negative impact. Political instability, measured by the Global Economic Policy Uncertainty (GEPU) index, also hinders growth.

Toward Environmental Sustainability: The Nexus between Agriculture, Renewable Energy, and Economic Growth in Mitigating CO2 Emissions in Somalia

This research investigates the intricate relationships between agriculture, renewable energy, economic growth, and carbon dioxide (CO2) emissions in Somalia from 1991 to 2022. This study uses the Autoregressive Distributed Lag (ARDL) model and Granger causality tests to understand their impact on environmental sustainability. ARDL results reveal a negative role of agriculture and renewable energy on CO2 in the short and long term. The country's reliance on fossil fuels and biomass further intensifies CO2 emissions. While economic growth is essential for improving living standards, it positively correlates with CO2 emissions in the short and long term, emphasizing the challenge of decoupling economic development from environmental degradation. Domestic investment has a short-run relation only to CO2 emissions. In Granger causality tests, the results indicated that Agriculture and domestic investment have bidirectional causality to carbon dioxide emissions. On the other hand, renewable energy, economic growth, and domestic investment have unidirectional causality to Agriculture in Somalia, while domestic investment has bidirectional causality to renewable energy and economic growth. The study recommends implementing comprehensive and integrated approaches to prioritize sustainable development strategies, clean energy alternatives, and efficient agricultural practices. Promoting economic growth while also focusing on capacity-building and awareness campaigns is essential. Collaborating with the international community on climate change mitigation and sustainable development initiatives can further support Somalia's journey toward environmental sustainability.

Impact of greenhouse gas emission, renewable energy, and economic growth on health expenditure in Southeast Asia: A comparative analysis of econometric models

Purpose — The study explores the effects of greenhouse gas emissions, renewable energy, and economic growth on health expenditures across Southeast Asia while comparing the performance of different econometric models for accuracy in analysis.Method — To analyze the relationships among variables, the study employs three econometric models, the Autoregressive Distributed Lag Model, the co-integration Model, and the Quantile Regression Model, using annual data from 2000 to 2020.Findings — The results reveal that greenhouse gas emissions and GDP significantly influence health expenditure in all three models. However, the significance of renewable energy consumption varies, with only the quantile regression model indicating a significant relationship with health expenditure. Model comparison based on Mean Squared Error (MSE) suggests that the autoregressive distributed lag (ARDL) model provides the most accurate predictions. Also, it found that there is a short-run and long-run causal effect of GHG and GDP on health expenditure, as well as health spending on GDP.Implication — This study helps to understand how economic growth, environmental factors, and healthcare spending interact to develop sustainable policies to address health and environmental problems in Southeast Asia.Originality — This research contributes to the body of knowledge examining the impact of economic and environmental factors on health expenditures in Southeast Asia through a comparative analysis of different econometric models.

Trend Prediction of Vibration Signals for Pumped-Storage Units Based on BA-VMD and LSTM

Under “dual-carbon” goals and rapid renewable energy growth, increasing start-stop frequency poses new challenges to safe operations of pumped-storage power plant equipment. Ensuring equipment safety and predictive maintenance under complex conditions urgently requires vibration warnings and trend forecasting for pumped-storage units. In this study, the measured vibration-signal characteristics of pumped-storage units in a strong background-noise environment are obtained using a noise-reduction method that integrates BA-VMD and wavelet thresholding. We monitored the vibration-signal data of hydroelectric units over a long period of time, and the measured vibration-signal characteristics of pumped-storage units in a strong background-noise environment are accurately obtained using a noise-reduction method that integrates BA-VMD and wavelet thresholding. In this paper, a BP neural network prediction model, a support vector machine (SVM) prediction model, a convolutional neural network (CNN) prediction model, and a long short-term memory network (LSTM) prediction model are used to predict the trend of vibration signals of the pumped-storage unit under different operating conditions. The model prediction effect is analyzed by using the different error evaluation functions, and the prediction results are compared with the predicted results of the four different methods. By comparing the prediction effects of the four different methods, it is concluded that LSTM has higher prediction accuracy and can predict the vibration trends of hydropower units more accurately.

Electricity arbitrage for mobile energy storage in marginal pricing mechanism via bi-level programming

The rapid growth of renewable energy is integrated into the distribution system. The creation of both new market mechanisms and investment models has critical effects on the economics and security of the distribution market. Mobile energy storage has been used to increase the resilience of distribution grids due to their advantages in mobility and flexibility, which offer electricity arbitrage options for merchant investments. This paper presents a bi-level optimization framework based on location marginal pricing settlement of mobile energy storage financial rights revenue in active distribution systems. In the developed framework, the upper-level problem determines the optimal capacity, routing, and dispatching of mobile energy storage to maximize revenue in the liberalized electricity market. The lower-level problem performs the joint optimization of energy and reserve market clearing as well as renewable energy capacity optimization based on the alternating current optimal power flow model. The non-convexity of the line flow and location marginal pricing is linearized via second-order cone relaxation and Karush-Kuhn-Tucker. The bi-level programming is reformatted as mathematical programming with equilibrium constraints. Further, the revenue risk due to renewable energy uncertainty is measured via conditional value-at-risk. Finally, the effectiveness of the optimization framework and solution method is verified using the modified IEEE-33 test system. The results show that mobile energy storage promotes renewable energy and reduces distribution network costs by 2.3%.

Design Guidelines for Building and Infrastructure Integrated Photovoltaic Modules

The demand for renewable energy is increasing as efforts to decarbonize energy sources continue. Photovoltaic (PV) generation systems are the main contributor to the growth of renewable energy, but limited land availability in countries such as Belgium and Netherlands poses a challenge to their deployment. Integrated PV (IPV) can be a promising solution, but requires special consideration regarding electrical and fire safety, efficiency, durability, cost, and environmental impact in the design process. This study seeks to assist designers of IPV products by guiding the selection of materials, technologies, mechanical designs, and production methods for PV semifabricates (SF). It provides a comprehensive list of general design criteria, each offering various options in terms of bill of materials and production technologies. These options come with their own set of advantages and disadvantages, which are enumerated and quantified wherever feasible. The general design guidelines are validated based on the building‐integrated PV and infrastructure‐integrated PV demonstrators (in this case a noise barrier) being developed in the Solar Energy Made Regional (SolarEMR) project.

From Potential to Power: Advancing Nigeria’s Energy Sector through Renewable Integration and Policy Reform

Nigeria is a nation endowed with both abundant renewable and non-renewable energy resources. Despite its vast potential, Nigeria struggles with a consistent power supply due to various systemic issues, such as inadequate funding, infrastructural decay, corruption, technical skill shortages, and macroeconomic instability. These challenges hinder the effective harnessing and distribution of energy resources, particularly renewable ones like wind, solar, biomass, and hydropower. This study assesses the existing energy policies and their efficacy in promoting sustainable energy development towards achieving universal electricity access by 2030. It highlights the necessity for a just energy transition that integrates a substantial proportion of renewable energy into the national grid, aiming to meet up to 60% of the country’s energy demands with clean sources by 2050. This transition is critical not only for energy security and reducing the environmental impact but also for fostering socioeconomic equity. Recommendations include overhauling the legal and regulatory frameworks to support renewable energy growth, particularly in off-grid areas, to ensure clean, affordable, and secure energy access. Strategic investments, enhanced infrastructure, and robust public–private partnerships are essential to overcome the current barriers and realize Nigeria’s energy potential. This paper calls for a comprehensive approach that addresses both the technical and socioeconomic dimensions of the energy crisis, laying the groundwork for a sustainable and prosperous energy future for Nigeria.

Real-time risk assessment of distribution systems based on Unscented Kalman Filter

The continuous growth of renewable energy and the load level has posed increasingly severe operational risks to distribution systems. In view of this, this paper combines state estimation with risk assessment, and uses the results of distribution system state estimation based on Unscented Kalman Filter as the input of risk assessment. With the combination, the sampling based on probability distributions in traditional risk assessment methods is no longer needed, thus avoiding the difficulty of updating probability distributions timely according to the latest information in real-time operation. By applying the proposed risk assessment method, the real-time assessment of operational risks in perspectives of bus voltage, branch power, and renewable energy utilization is achieved. Meanwhile, the weight of each risk index is properly determined according to both subjective and objective knowledge by using Analytic Hierarchy Process method and entropy weight method. Case studies show that the proposed method achieves effective assessment of comprehensive risks in the operation of distribution system.

THE ROLE OF THE GREEN ECONOMY IN SHAPING ECONOMIC GROWTH IN POLAND

The aim of this paper is to examine and understand the impact of various green economy indicators on economic growth in Poland from 2010 to 2021. The study focused on a select number of indicators, including the final energy intensity of the economy, expenditures on environmental fixed assets in relation to gross domestic product (GDP), the share of renewable electricity in gross final electricity consumption, primary energy intensity of GDP, and the percentage of urban green areas. The relationship between green economy indicators and economic growth, expressed as gross domestic product per capita, was examined using regression analysis, time series analysis and correlation analysis. Data for the analysis were taken from the Central Statistical Office. Time trend analysis showed that the economy’s final energy intensity and the share of renewable energy improved steadily over the period under review, with a positive impact on GDP per capita. Correlation analysis demonstrated a robust inverse correlation between energy intensity and GDP per capita, along with a positive association between the share of renewable energy and economic growth. In linear and multiple regressions, the economy’s final energy intensity, expenditures on environmental fixed assets, and the share of renewable energy exhibited a significant impact on GDP per capita. The study’s conclusions underscore the necessity of sustained and intensified efforts towards a green economy in Poland, which is pivotal for ensuring long-term economic growth and sustainable development.

Examining the contribution of globalization, renewable energy, and economic growth towards CO2 emissions in the G‐7 countries

AbstractMost of the world's developed countries have negative consequences of unbalanced economic growth and environmental sustainability. The current study contributes to the literature by investigating the impacts of sub‐indices of globalization, renewable energy, and economic growth on CO2 emissions in G‐7 countries of United Kingdom, United States, Japan, Canada, France, Italy, and Germany. The article demonstrates the correlation between numerous variables in the G‐7 countries between 1990 and 2020, including GDP per capita growth, CO2 emissions, globalization, and renewable and non‐renewable energy. The Pooled Mean Group (PMG) technique performs significant tests for cross‐sectional dependence, panel unit root, co‐integration, and descriptive statistics. The study results show that environmental pollution rises with economic growth and falls in the presence of renewable energy sources. Renewable energy use, political globalization, and economic globalization lower environmental harm. From the finding, we indicate that we reduce the environmental pollution in the given countries by lowering or raising the factor affecting the country. A globe map was used in the current study to assign the G‐7 nations. Based on the findings, we addressed several policy initiatives.

Seasonal forecasting of the European North-West shelf seas: limits of winter and summer sea surface temperature predictability

The European North-West shelf seas (NWS) support economic interests and provide environmental services to adjacent countries. Expansion of offshore activities, such as renewable energy infrastructure, aquaculture, and growth of international shipping, will place increasingly complex demands on the marine environment over the coming decades. Skilful forecasting of NWS properties on seasonal timescales will help to effectively manage these activities. Here we quantify the skill of an operational large-ensemble ocean-atmosphere coupled global forecasting system (GloSea), as well as benchmark persistence forecasts, for predictions of NWS sea surface temperature (SST) at 2–4 months lead time in winter and summer. We identify sources of and limits to SST predictability, considering what additional skill may be available in the future. We find that GloSea NWS SST skill is generally high in winter and low in summer. GloSea outperforms simple persistence forecasts by adding information about atmospheric variability, but only to a modest extent as persistence of anomalies in the initial conditions contributes substantially to predictability. Where persistence is low – for example in seasonally stratified regions – GloSea forecasts show lower skill. GloSea skill can be degraded by model deficiencies in the relatively coarse global ocean component, which lacks dynamic tides and subsequently fails to robustly represent local circulation and mixing. However, “atmospheric mode matched” tests show potential for improving prediction skill of currently low performing regions if atmospheric circulation forecasts can be improved. This underlines the importance of coupled atmosphere-ocean model development for NWS seasonal forecasting applications.

Mobileception-ResNet for transient stability prediction of novel power systems

Power system transient stability prediction (TSP) is particularly important as power systems change and evolve, including the rapid growth of renewable energy, the proliferation of electric vehicles, and the construction of smart grids. Traditional time-domain simulation methods are time-consuming and cannot achieve online prediction. Direct methods are poorly adapted and cannot be applied to complex power systems. Existing machine learning algorithms only classify the transient stability without providing the degree of transient stability of the system. Therefore, a fast and accurate power system TSP method is needed to assist operators in implementing timely measures to improve the stability of the power system running. This study proposes a Mobileception-ResNet network, Mobileception-ResNet is formed by Inception-ResNet-v2, MobileNet-v2, and a fully connected layer. In this study, Mobileception-ResNet and nine comparison models are experimented on two node systems, i.e., the IEEE 10–39 and 69–300 systems. In the IEEE 10–39 system, the root mean square error, mean absolute error, and mean absolute percentage error of Mobileception-ResNet are 44.13 %, 36.74 %, and 39.96 % lower, and the coefficient of determination is 0.04 % higher, respectively, when compared to the comparative model with the best evaluation indicator; in the IEEE 69–300 system, the corresponding values are 2.6 %, 12.83 %, 12.55 %, and 0.01 %, respectively.

Assessment of the Renewable Energy Consumption Capacity of Power Systems Considering the Uncertainty of Renewables and Symmetry of Active Power

The rapid growth of renewable energy presents significant challenges for power grid operation, making the efficient integration of renewable energy crucial. This paper proposes a method to evaluate the power system’s capacity to accommodate renewable energy based on the Gaussian mixture model (GMM) from a symmetry perspective, underscoring the symmetrical interplay between load and renewable energy sources and highlighting the balance necessary for enhancing grid stability. First, a 10th-order GMM is identified as the optimal model for analyzing power system load and wind power data, balancing accuracy with computational efficiency. The Metropolis–Hastings (M-H) algorithm is used to generate sample spaces, which are integrated into power flow calculations to determine the maximum renewable energy integration capacity while ensuring system stability. Short-circuit ratio calculations and N-1 fault simulations validate system robustness under high renewable energy integration. The consistency between the results from the M-H algorithm, Gibbs sampling, and Monte Carlo simulation (MCS) confirms the approach’s accuracy.

Photovoltaics rooftop regulations and their connection to pro-environment consumer behavior in Indonesia

To address environmental issues, Indonesia aims to achieve a 23% renewable energy share by 2025 and 31% by 2050, according to the National Energy Plan. This article examines the regulations governing the management of rooftop solar power plant (rooftop-PV) in Indonesia and their connection to pro-environment consumer behavior. Despite Indonesia’s ambitious targets for Renewable Energy (RE) growth, progress in the field still needs improvement. Pro-environmental behavior (PEB) within the community is crucial for adopting rooftop PV as a more environmentally friendly energy alternative. This research employs a qualitative descriptive methodology with content analysis to evaluate the current situation. The research findings indicate that rooftop PV offers economic benefits through cost savings for consumers and is supported by existing regulations. However, some businesses feel that the government needs to expedite revising relevant regulations to address investment stagnation and installed solar panel capacity. Concerns arise that proposed policy changes may hinder the growth of rooftop PV businesses and the achievement of national capacity targets. The role of pro-environment consumer behavior, which has the potential to drive rooftop PV adoption, will be influenced by psychological and social factors, as well as changes in applicable regulations.

Challenges and Opportunities in Nigeria's Renewable Energy Policy and Legislation

Endowed with abundant renewable energy resources, Nigeria stands at a pivotal point in its energy development journey. This study explores the landscape of renewable energy policy and legislation in Nigeria, highlighting the challenges and opportunities that shape the sector. The research begins with an overview of Nigeria's current energy framework, emphasizing the critical role of renewable energy in achieving sustainable development. It examines existing policies and legislative frameworks, identifying the key government agencies responsible and outlining their respective functions. Despite the country's vast potential, numerous barriers impede the growth of renewable energy. These include legal and regulatory inconsistencies, institutional inefficiencies, financial constraints, and technical challenges. The study delves into these issues, providing a comprehensive analysis of how they hinder progress in renewable energy adoption. Conversely, the research identifies significant opportunities to enhance renewable energy policy and legislation including potential legislative reforms, institutional strengthening, financial incentives, and the promotion of technological innovation and infrastructure development. By leveraging these opportunities, Nigeria can create a more robust and conducive environment for renewable energy growth. The study concludes with strategic recommendations for policymakers and stakeholders to bridge the existing gaps and foster a sustainable energy future for Nigeria. It also outlines future research directions aimed at optimizing renewable energy policies and practices. Through this comprehensive analysis, the study aims to contribute to the ongoing discourse on renewable energy in Nigeria, providing insights to guide effective policy-making and legislative action.

Pv-load matching based on combination of different consumers: A case study in Swedish contexts

The transition towards sustainability necessitates robust growth of renewable energy, especially solar power. However, increasing the shares of solar power may lead to mismatch of electricity supply and demand, thus worse solar power performance could be received due to lower self-consumption and self-sufficiency. This issue has attracted more attention recently as it also requires additional costs for controlling and battery integration. This study combines several load profiles from consumers having different behaviors with different proportions to find out the optimal shares with higher level of PV penetration and self-sufficiency. A visualizing matching layout is proposed to present the PV-load matching level of all the possibilities at different seasons based on a Swedish context. It is found an 8% improvement of self-sufficiency reaching 70% in summer without additional equipment and scarification of self-consumption. The results could assist in the design and planning of the future power sector. Regarding specific targets, various optimal solutions could be found based on the layout.

HUGO – Highlighting Unseen Grid Options: Combining deep reinforcement learning with a heuristic target topology approach

With the growth of Renewable Energy (RE) generation, the operation of power grids has become increasingly complex. One solution could be automated grid operation, where Deep Reinforcement Learning (DRL) has repeatedly shown significant potential in Learning to Run a Power Network (L2RPN) challenges. However, most existing DRL algorithms have only considered individual actions at the substation level. In contrast, we propose a more holistic approach by proposing specific Target Topologies (TTs) as actions. These topologies are selected based on their robustness. In this paper, we present a search algorithm to find the TTs and upgrade our previously developed DRL agent CurriculumAgent (CAgent) to a novel topology agent. We compare our upgrade with the CAgent and significantly increase its L2RPN score by 10%. Further, we achieve a 25% better median survival time with our TTs included. Later analysis shows that almost all TTs are close to the base topology, explaining their robustness.

The effect of eco-friendly and financial technologies on renewable energy growth in emerging economies

Successfully integrating renewable energy sources depends on eco-friendliness, financial technology, and economic growth (GDP). This paper examines the dynamic effect of innovative financial and green technology on renewable energy for 38 emerging economies from 2006 to 2021. Using the dynamic First-difference Generalized Method of Moments (FD-GMM) model, the analysis identifies a critical GDP threshold of 1831.772 US dollars, significant at the 1 % confidence level. Below this threshold, GDP negatively affects green energy adoption, while above it, GDP positively influences the shift to greener energy, supporting the predicted U-shaped relationship in the data. The results conclude that eco-friendly and financial technology positively and significantly influence renewable energy adoption, where the dynamics and barriers to adopting eco-friendly and financial technologies in emerging countries may differ from those in developed nations. Based on the findings, relevant energy policies have been recommended for energy stakeholders, Tech firms and decision-makers.