Search results

Bioelectricity from sugarcane presents possibilities of gaining prominence as an energy source in the coming years, contributing to sustainable development and being a relevant pillar of Brazil’s energy matrix, based on its advantages and the measures that can stimulate it. The purpose of this study is to contribute to a new framework for improving the regulatory framework for Brazilian sugarcane bioelectricity that facilitates the governance of its stakeholders and their respective relationships.

Exploratory and qualitative research, adopting, in addition to theoretical and practical research, consultations with experts, combined with analysis of documents relating to sustainability reports released by companies in the sector.

In the observed reports of 23 companies, it was found that 14 give full relevance to bagasse energy, and it can be attested that sugar-energy bioelectricity includes social, economic and environmental dimensions. In addition, the work presented elements that can benefit cogeneration, such as reduction or exemption of the distribution system use tariff for energy generation from bagasse; freedom for full commercialization in the free energy market, including small consumers; contractual simplification and solidification of financial compensation for clean energy production.

The work contributes to the advancement of theoretical references of business economics and competitiveness for practical application in competitive sustainability environments.

While science has researched the impact of air pollution on human health, the economic dimension of it has been less researched so far. Renewable energy consumption is an important factor in determining the level of life expectancy and reducing health expenditure. Thus, this study aims to investigate the impact of renewable energy, carbon emissions, health expenditure and urbanization on life expectancy in G-7 countries over the period of 2000–2019.

This study has adopted a novel Method of Moments Quantile Regression (MMQR). Furthermore, as a robustness check for MMQR, the fully modified ordinary least square, dynamic ordinary least squares and fixed effect ordinary least square estimators have been used.

The results indicated that renewable energy consumption, health expenditure and urbanization lead to an increase in life expectancy across all quantiles (5th to 95th), whereas higher carbon dioxide emissions reduce life expectancy at birth across all the quantiles (5th to 95th).

The empirical findings conclude that governments should recognize their potential in renewable energy sources and devise policies such as tax-related regulations, or relevant incentives to encourage further investments in this field.

This paper in comparison to the other research studies used MMQR to investigate the impact of factors affecting life expectancy. Also, to the best of the authors’ knowledge, so far no study has investigated the impact of renewable energy on life expectancy in G-7 countries.

This paper aims at developing an improved method, based on binary search algorithm (BSA) for the steady-state analysis of self-excited induction generators (SEIGs), which are increasingly used in wind energy electric conversion systems. The BSA is also compared with linear search algorithm (LSA) to bring out the merits of BSA over LSA.

All the parameters of SEIG, including the varying core loss of the machine, have been considered to ensure accuracy in the predetermined performance values of the set up. The nodal admittance method has been adopted to simplify the equivalent circuit of the generator and load. The logic and steps involved in the formulation of the complete procedure have been illustrated using elaborate flowcharts.

The proposed approach is validated by the experimental results, obtained on a three-phase 240 V, 5.0 A, 2.0 kW SEIG, which closely match with the corresponding predicted performance values. The analysis is shown to be easy to implement with reduced computation time.

A novel improved and simplified technique has been formulated for estimating the per unit frequency (a), magnetizing reactance (X_m) and core loss resistance (R_m) of the SEIG using the nodal admittance of its equivalent circuit. The accuracy of the predetermined performance is enhanced by considering the SEIG’s varying core loss. Only simple MATLAB programming has been used for adopting the algorithms.

Large-scale industrialization, growth and development have come at the cost of severe environmental degradation, primarily measured in terms of carbon dioxide emissions. Apart from the several measures taken to reduce enviornmental degradation, provision of private capital is a necessity apart from the public capital. There is a debate on impact of carbon dioxide emissions with increase in affluence, technology, population and renewable energy. The purpose of the study is to look into the role of private equity investment on renewable energy and technological patents.

The study extends the use of stochastic impact by regression on population, affluence and technology model to include another factor for investments and capital, i.e. private equity along with renewable energy, population, technology and GDP growth on carbon emissions for the BRICS countries. The time period for the study is from 2002 to 2021, and the relationship between the variables has been tested using pooled mean group/autoregressive distributed lag, fully modified ordinary least squares and panel quantile regression.

First, the results depict a log-run relationship between the variables across the panel using cointegration. Private equity investments do not have a significant impact on carbon emissions. The study proposes important policy implications. There are two schools of thought on the impact of private equity on carbon emissions. For example, inherently private equity investments come with higher stakes and a shorter holding period because of which their primary focus remains on having higher returns instead of responsible investing. However, as private equity adds up to capital, which leads to an increase in productivity and eventually higher economic growth, this could affect carbon emissions. This study supports the first thought. Additionally, renewable energy also affects carbon emissions positively. The policymakers should look into the role and intent of the private equity investors in green investments and invest in technologies and patents that can lead to energy consumption.

The paper is the first of its kind, to the best of the authors’ knowledge, to look into the impact of private equity on renewable energy and technological patents.

This study tests whether environmental awareness affects firm creation by using Google Trends data and a novel region-level data set from Italy.

Forward-looking entrepreneurs drive firm creation. The authors hypothesize that more environmentally conscious entrepreneurs will emerge as environmental awareness rises, increasing the number of green and energy firms. The authors test the prediction using Google Trends data and a novel region-level data set from Italy.

The authors find that not only the number of green and energy-innovative firms but also that of all innovative start-ups increases with rising environmental consciousness. The results imply some “innovation spillover” effects from green sectors to other industries with rising environmental awareness.

The paper hypothesizes that as environmental awareness rises, more environmental-conscious entrepreneurs will emerge, which would increase the number of green and energy firms. Robustness and falsification tests are also offered.

The purpose of this paper aims to design a robust wind turbine emulator (WTE) based on a three-phase induction motor (3PIM).

The 3PIM is driven by a soft voltage source inverter (VSI) controlled by a specific space vector modulation. By adjusting the appropriate vector sequence selection, the desired VSI output voltage allows a real wind turbine speed emulation in the laboratory, taking into account the wind profile, static and dynamic behaviors and parametric variations for theoretical and then experimental analysis. A Mexican hat profile and a sinusoidal profile are therefore used as the wind speed system input to highlight the electrical, mechanical and electromagnetic system response.

The simulation results, based on relative error data, show that the proposed reactive power control method effectively estimates the flux and the rotor time constant, thus ensuring an accurate trajectory tracking of the wind speed for the wind emulation application.

The proposed architecture achieves its results through the use of mathematical theory and WTE topology combine with an online adaptive estimator and Lyapunov stability adaptation control methods. These approaches are particularly relevant for low-cost or low-power alternative current (AC) motor drives in the field of renewable energy emulation. It has the advantage of eliminating the need for expensive and unreliable position transducers, thereby increasing the emulator drive life. A comparative analysis was also carried out to highlight the online adaptive estimator fast response time and accuracy.

This study aims to investigate the feasibility of proposed microgrid (MG) that comprises photovoltaic, wind turbines, battery energy storage and diesel generator to supply a residential building in Grindelwald which is chosen as the test location.

Three operational configurations were used to run the proposed MG. In the first configuration, the electric energy can be vended and procured utterly between the main-grid and MG. In the second configuration, the energy trade was performed within 15 kWh as the maximum allowable limit of energy to purchase and sell. In the third configuration, the system performance in the stand-alone operation mode was investigated. A whale optimization technique is used to determine the optimal size of MG in all proposed configurations. The cost of energy (COE) and other measures are used to evaluate the system performance.

The obtained results revealed that the first configuration is the most beneficial with COE of 0.253$/KWh and reliable 100%. Furthermore, the whale optimization algorithm is sufficiently feasible as compared to other techniques to apply in the applications of MG.

The value of the proposed research is to investigate to what extend the integration between MG and main-grid is beneficial economically and technically. As opposed to previous research studies that have focused predominantly only on the optimal size of MG.

The analytical framework proposed in this study aims to link the capital portfolio approach to sustaining human well-being, 2015 sustainable development goals and development action ARC-D concepts. Nepal case study is a “tribrid” power generation system that combines distributed solar, hydro and wind power generation capacities for the resilience of a community of around 500 people in a remote village with a total installed capacity of 28 kW. The second case study is about the solarization of 900 health centres in Chhattisgarh, India, with off-grid solar PV with a cumulative capacity of 3 MW.

Critical infrastructure at the community scale needs to be resilient to maintain community-level functionality in the face of adverse impacts. The present study provides two case study sites from Nepal and India to demonstrate various elements of resilience building for critical infrastructures, especially for the energy sector.

Granular technology and distributed generation in Nepal and India can act as critical infrastructure in providing on-demand electricity service to enhance community-level resilience along with future opportunities of scale up.

The analytical framework for evaluating community-scale resilience through critical infrastructure design and application of the framework using evidence based on case studies are the original contributions.

Just transition is a fundamental concept for supply chain management but neither discipline pays attention to the other and little is known about how supply chains can be orchestrated as socioecological systems to manage these transitions. Building from a wide range of just transition examples, this paper explores just transition to understand how to move beyond instrumental supply chain practices to supply chains functioning in harmony with the planet and its people.

Building from a systematic review of 72 papers, the paper identifies just transition examples while interpreting them through the theoretical lens of supply chain management, providing valuable insights to help research and practice understand how to achieve low-carbon economies through supply chain management in environmentally and socially just ways.

The paper defines, elaborates, and extends the just transition construct by developing a transition taxonomy with two key dimensions. The purpose dimension (profit or shared outcomes) and the governance dimension (government-/industry-led versus civil society-involved), generating four transition archetypes. Most transitions projects are framed around the Euro- and US-centric, capitalist standards of development, leading to coloniality as well as economic and cultural depletion of communities. Framing just transition in accordance with context-specific plural values, the paper provides an alternative perspective to the extractive transition concept. This can guide supply chain management to decarbonise economies and societies by considering the rights of nature, communities and individuals.

Introducing just transition into the supply chain management domain, this paper unifies the various conceptualisations of just transition into a holistic understanding, providing a new foundation for supply chain management research.

The study is called for to eliminate the noise between the significant macro variables from the perspective of the cause-and-effect approach to indicate why and how the return of solar projects is being affected by these.

The study aims to investigate the spread between unit selling electricity prices of a monthly production of 250 KW solar project installed in Türkiye and USD/TRY.

A relational framework is designed by drawing on the variables determined as crude oil prices, United States (US) 2-year yield, Dollar Index (DXY), USD/TRY, the annual inflation rate of Türkiye, and unit selling electricity prices. Then, a multivariate approach is performed through Matlab to analyse the correlational relationships and structure the curve estimation models.

The observations show that the gradually rising spread between unit selling electricity price and USD/TRY signals the reduction in return-on-investment rate of solar energy projects because of the particular causes of the European energy crisis by the reason of Russia and Ukraine war and escalating risks in DXY and US treasury yields as a result of federal fund rate hikes against inflationary pressures. Solar energy investments are delicate instruments to global oil shocks and higher DXY in controlling Inflation and currency volatility; therefore, resilient policies should solicit the demand because of environmental and economic reasons to reduce the external dependency of Türkiye.