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Résumé: De manière agrégée, les PME sont de grandes consommatrices d'énergie et ont des impacts environnementaux considérables au niveau mondial. Malgré cela, elles attirent encore peu l'attention des chercheurs et des responsables des politiques publiques. Pourtant, sans leur contribution, l'atteinte des cibles nationales en matière énergétique et environnementale est improbable. En ce sens, il devient essentiel de mieux comprendre ce qui les incite à devenir plus mature au niveau énergétique. La présente étude adopte une analyse multiniveau en considérant les aspects individuel, organisationnel, contextuel pour identifier les déterminants de la maturité énergétique des PME. Une étude menée auprès de 409 PME québécoises permet d'établir que ce sont les facteurs organisationnels intangibles qui sont les principaux déterminants de la maturité énergétique dans les PME québécoises. Les facteurs contextuels n'ont pas d'influence et un seul facteur individuel, l'âge du dirigeant, exerce une influence limitée. Cette reconnaissance de la prépondérance des facteurs organisationnels intangibles est un apport aux écrits sur le sujet qui ne font pas cette distinction lorsqu'ils considèrent les freins et accélérateurs des pratiques d'efficacité énergétique. Cela procure aussi un enseignement pratique important: l'acquisition de compétences et d'attitudes proactives dans les PME envers l'efficacité énergétique est un levier d'action à prioriser. In an aggregate manner, SMEs are very large consumers of energy and have significant environmental impacts worldwide. Nevertheless, they still attract little attention from researchers and public policymakers. Yet, without their contribution, the achievement of national energy and environmental targets is unlikely. In this sense, it becomes essential to better understand what motivates them to become more energetically mature. This study adopts a multi-level analysis that considers individual, organizational, contextual aspects to identify the determinants of SME energy maturity. A study of 409 Quebec SMEs shows that intangible organizational factors are determinants of energy maturity in Quebec SMEs. Contextual factors have no influence and only one individual factor, the age of the leader, has a limited influence. This recognition of the preponderance of intangible organizational factors is a contribution to the literature on the subject, which does not make this distinction when considering the obstacles and the accelerators of energy efficiency practices. It also provides an important practical lesson: the development of proactive skills and attitudes in SMEs towards energy efficiency is a lever of action to prioritize. [ABSTRACT FROM AUTHOR]

This research study presents a novel approach to enhance the efficiency and performance of Battery Energy Storage Systems (BESSs) within microgrids, focusing particularly on the integration of wind energy. The inherent inconsistency and unpredictability of Renewable Energy Resources (RERs) necessitate the development of effective integration solutions to accommodate them. Our article provides a customized iteration of the metaheuristic algorithm referred to as the Contracted fitness-dependent optimizer. The proposed methodology involves the adaptive adjustment of migration rates based on habitat suitability indices, while also considering variations in perturbations. The incorporation of Lévy flight and an elimination phase significantly enhances the algorithm’s efficacy in problem-solving. In order to establish the superiority of our strategy over alternative optimization approaches, we conduct simulations across diverse conditions and subsequently compare the outcomes. It was calculated that the daily scheduling cost was 235.2$ and the daily operational cost was USD 268$. In Scenario 3, the total operating expenses and arranging costs for 1 day, respectively, were determined to be 165$ and 115$. Further, the highest depth of discharge level was around 77%. Moreover, a −9.18 kW and 23.02 kW maximum charging and discharging power adjustment was made. The findings of our study emphasize the economic and operational benefits associated with appropriately sized BESSs within microgrid contexts. These advantages have the potential to enhance battery longevity and promote the development of more sustainable energy systems. [ABSTRACT FROM AUTHOR]

Power generation comprises high environmental and ecological impacts. The global power industry is under pressure to develop more efficient ways to operate and reduce the impacts of inherent process variability. With the rapid development of technologies within the energy sector, large volumes of data are available due to in-time operational measurements. With increased computer processing capabilities, machine learning is applied to explore these in-time operational measurements for improved process understanding. This research paper investigates machine learning algorithms for energy efficiency improvement at coal-fired thermal power plants by conducting a systematic literature review. This research is essential since it provides guidelines for applying machine learning towards sustainable energy supply and improved decision-making. Subsequently, efficient processes result in the reduction of fuel usage, which results in lower emission levels for equivalent power generation capacity. Furthermore, this study contributes towards future research by providing valuable insights from academic and industry-related studies. [ABSTRACT FROM AUTHOR]

GHG emissions growth of Vietnam is highest all over the globe and the carbon intensity of this economy is considered second highest in Asian economies. As the energy intensity level is rising constantly, thereby, the predictions indicate that Vietnam will become highest GHG emission in the region. In order to address the issue, the current article aims to investigate the impact of green finance, technology advancement, energy efficiency, industrialization, and population growth on sustainable development in Vietnamese context. The time chosen for the study is 1991 to 2020. The study has used the Dynamic Auto-regressive Distributed Lags (DARDL) and the Bayesian Auto-regressive Distributed Lags (BARDL) model for data analysis. Findings exposed that green finance, technology advancement, REO, REC, industrialization, and population growth all are positively connected with sustainable development. The study guides the regulators in establishing regulations related to sustainable development through the adoption of green finance, energy, and technology. [ABSTRACT FROM AUTHOR]

It is reasonable to expect that the energy needs of the top emerging economies will increase over the coming decades as their economies expand rapidly. There may be environmental costs to using conventional energy from fossil fuels to meet increased energy demand. Therefore, this study aims to investigate the link between energy efficiency and energy transition along with additional control variables like research and development expenditures, trade, and gross domestic product for the top 10 emerging countries between 1990 and 2021. To study the case of these targeted economies, the authors use panel data and novel panel data econometrics techniques for a long-run relationship like the MMQR to observe changes over time between the variables, which is useful in the empirical evidence. The models' primary findings are as follows: The panel cointegration tests confirm log-run associations among the targeted variables. Energy efficiency has the largest influence on the energy transition. The control variables like RDR and TRA decrease renewable energy consumption in the targeted economies. The findings also support the notion that GDP drives renewable energy consumption in the leading emerging economies. Numerous important ecological sustainability-related plans are recommended to the concerned governments based on research findings. [ABSTRACT FROM AUTHOR]

Environmental degradation is one of the main concerns for the countries across the globe, where energy efficiency (E.N.E.F.) is regarded as one of the substantial remedial measures. Still, the factors affecting E.N.E.F. is not extensively explored in the empirical literature. In this sense, the current study tends to analyse the influencing factors of E.N.E.F. in case of the G7 economies throughout 1990–2020. Since this study is dealing with the panel data, therefore, various panel data specifications are used, which validates the slope heterogeneity, panel cross-section dependence (C.D.), and the existence of cointegration between E.N.E.F., economic growth, renewable energy, energy related inflation, and political risk index (P.R.I.). Due to mixed integrating order, this study employed Cross-Sectional Autoregressive Distributed Lag (C.S.-A.R.D.L.) approach, which reveals that all the variables are significant and positive factors of E.N.E.F. in both short and long-run. Also, the results reveals the convergence of model towards the equilibrium with 83.7% speed of adjustment. To tackle the panel data issues such as slope heterogeneity and C.D., this study employed Dynamic Common Correlated Effects–Generalised Method of Moment (D.C.C.E.–G.M.M.), which also indicates the positive and significance influence of the selected variables on E.N.E.F. The estimated results are validated by Augmented Mean Group (A.M.G.) estimator. Moreover, bidirectional causal nexus is found between E.N.E.F. and regressors (economic growth, renewable energy, energy related inflation, and P.R.I.). This study also provides relevant policy measures at the end. [ABSTRACT FROM AUTHOR]

Using efficient and cleaner energy is environmentally friendly and is vital for combating the negative effect of emissions on the environment. Focusing on both developed and developing nations, it is important to report their environmental conditions while targeting economic and energy-related factors. In this regard, the current study is an attempt to investigate the influence of energy efficiency (ENEF), financial inclusion (FIN), economic growth (GDP), environmental-related technological innovation (ERTI), and human capital index (HCI) on the carbon dioxide (CO2) emissions for the five selected nations of RCEP. The variables are found associated in terms of long-run cointegration relationships. The panel quantile regression estimator is utilized for empirical estimations, which provide highly significant estimates across the three selected quantiles (25th, 50th and 75th). The results report that FIN and GDP significantly aggravate environmental degradation by enhancing the CO2 emission level, among which the strongest CO2 emission growth is found in the second quantile. Besides, the ENEF, ERTI and HCI significantly reduce CO2 emission. Based on the empirical findings, this study provides practical implication focusing on the improvement of energy efficiency policies and revising financial inclusion policies in promotion of green investments. [ABSTRACT FROM AUTHOR]

The current paper aims to find scientifically valid approaches to improving the environmental safety of technologies for drying grain materials and granular fertilizers. The methodology for environmental and economic efficiency justification of the energy-saving multi-stage shelf dryers with a convective fluidized bed drying provides design and operational parameters control. Meta-analysis of energy-effective and eco-friendly dryers based on the bibliometric method and the Scopus database is used for this study. The results showed that pollutants concentration in the exhausts could be controlled by modifying the design and the required number of shelves, ensuring the required material residence time to achieve the desired moisture content. The production of electricity using alternative resources like biogas and biofertilizer produced from the anaerobic digestate allows for achieving several Sustainable Development Goals simultaneously. The Goals in scope include Goal 6 Clean Water and Sanitation, Goal 7 Affordable and Clean Energy, Goal 9 Industry, Innovation and Infrastructure, Goal 12 Responsible Consumption and Production, Goal 13 Climate Action, and Goal 15 Life On Land. [ABSTRACT FROM AUTHOR]