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The primary purpose of this paper is to investigate the effects of two variables, trade openness and the issuance of green bonds, on the consumption of renewable energy in Southeast Asian countries. Quarterly data throughout 2016–2021 in the framework of the panel data method were used for the case of 6 selected countries (Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam). The results confirmed that the issuance of green bonds is an effective green financing tool in the implementation of the development policy of the deployment of renewable energy in the countries of the Southeast Asian region. The degree of trade openness has a driving effect on increasing renewable energy consumption due to the increased possibility of transferring green technologies and increasing interactions with leading countries in the field of sustainable development. The typical standard of green bonds, green scientific network (GSN), the development of e-commerce, and the publication of digital green papers are the recommended practical policies of this research. • Green bond is an effective tool to increase of deployment of renewable energy. • Trade liberalism increases the deployment of renewable energy. • Green R&D is a leading factor in the field of clean energy consumption. [ABSTRACT FROM AUTHOR]

In recent decades, the role of green energy in realizing green transition and addressing environmental degradation needs to be brought into full play. To promote green energy development in China, this paper examines the relationship among green economic growth, green finance, and green energy (3G) between 2011 and 2019. The heterogeneous, asymmetric, and mediation impact relationship that exists in the 3G nexus is also explored in this study. Accordingly, the results suggest that: (1) Green economic growth and green finance are positively associated with green energy, and the impact is heterogeneous on different types of green energy and in different regions; (2) the impact of green economic growth on green energy are asymmetric, while that of green finance is consistent; and (3) green innovative technology is an effective mediator between green economic growth and green energy, while the investment effect is not significant. This paper contributes to formulating several reasonable policies for improving the green energy industry and achieving sustainable development. It is essential to give full play to the transformation of green achievements to enhance the role of green economic growth in promoting the green energy industry. • This study explores 3G nexus (green economic growth, finance, and energy (GRE)) in China. • The heterogeneity, asymmetry, and mediating mechanism are further analyzed. • Green economic growth and green finance can significantly promote GRE. • The impacts of green economic growth and green finance on GRE are heterogeneous. • Green technological innovation is an effective mediator in the 3G nexus. [ABSTRACT FROM AUTHOR]

This paper uses panel data on renewable energy in China. Thus, the current analysis fills the gaps by examining the relationship between green technology innovation and renewable energy and CO 2 emissions from 1990 to 2018. The current study examines all concerns connected to panel data analysis with advanced panel estimators, such as cross-sectional dependence, stationarity, variation in slope parameters, and structural break. Our findings show that test results reveal that green technology innovation and renewable energy have a negative and considerable influence on CO2 emissions in the long run. Moreover, the short-run relationship of green technology innovation, on the other hand, is not significant—as evidenced by the findings of robustness tests such as AMG and CCEMG. Other empirical results revealed that GTI, REN and NEN significantly reduced local CO 2 emission, while POP and PI had no obvious reduction effects on CO 2 emissions. Different GTIs had the same spatial "symbiotic effects" on CO 2 emission reduction in the short term, showing positive spatial spillover reduction effects. Lastly, we conclude that the use of green technology innovation has positive externalities. Some policies to assist green innovation technologies and renewable energy resources have been suggested for the Chinese government to enact. • This paper uses panel data on renewable energy in China. • The current study examines all concerns connected to panel data analysis with advanced panel estimators. • The short-run relationship of green technology innovation is not significant. • We conclude that the use of green technology innovation has positive externalities. [ABSTRACT FROM AUTHOR]

Using daily data from the beginning of 2018 to the end of 2022 and the Seemingly Unrelated Regression method, this paper sought to determine the relationship between green and non-green cryptocurrency indices as representative of blockchain technologies on three green bond indices in two periods before the outbreak of COVID-19 and the corona period. The preliminary results confirmed that by spreading the coronavirus, the sensitivity of the green bond market has increased to the gold index. In addition, the green cryptocurrency index (Cardano) significantly impacts green bonds more during the Corona era. The negative effect of the Bitcoin index on the index of green bonds in the Corona era is less than its adverse effect in the pre-corona period. Developing green cryptocurrencies and linking cryptocurrencies and digital green financing are two significant recommended policy implications for scholars and policymakers. • Green cryptocurrency has a greater impact on green bonds during the Corona era. • During coronavirus, the sensitivity of the green bond to gold price has increased. • Bitcoin has negative impact on green bond indices before the COVID-19. [ABSTRACT FROM AUTHOR]

Considering sustainable development, technology selection is a multi-criteria decision-making (MCDM) problem that influences the advantages of enterprises or a country. This paper investigates existing wave energy technologies as alternatives to green and sustainable technologies to apply them in the seas and oceans. A framework is presented, and major technologies to extract wave energy are identified. Each technology has been examined in scopes of strategic factors, availability, technical knowledge, technological features, economic, social, and environmental factors as the main criteria. Totally, 20 converters and 52 criteria are considered. The Caspian Sea is considered as a case, and a decision matrix is established by integrating the gathered data and the experts' opinions. By integrating the fuzzy Delphi method (FDM) and preference ranking organization method for enrichment evaluations (PROMETHEE) method, Pelamis is considered the most appropriate technology to harvest wave energy in the Caspian Sea. [ABSTRACT FROM AUTHOR]

Green innovation is a feasible and potential option that governments can adopt to reduce reliance on fossil fuels and speed the transition to renewable energy sources. This study analyzes the relationship between green finance development and green innovation using listed Chinese companies to investigate the role of green finance. In the preliminary analysis, it employs Poisson and negative binomial distributions based on the sample characteristics. The additional research considers enterprises' internal and external characteristics and adds a zero-inflated factor with enterprise-scale and bank competition. Our main findings suggest that green finance positively improves green technological innovation, and zero-inflated factors can significantly lower the possibility of enterprises refusing to engage in green innovation. By using a representative green finance policy in 2012 as a quasi-natural experiment, this paper also demonstrates the promoting effect of green finance development. The above results are still valid by the robustness test. Furthermore, this paper applies the panel threshold model and finds that the enterprise scale and bank competition not only affect the choice of the enterprise but also stimulate the promotion intensity in different development stages. This paper contributes to targeted policy implications for the renewable energy transition. [ABSTRACT FROM AUTHOR]

In the context of sustainable development, the renewable energy technology innovation (RETI) may have a potential impact upon the industrial structure upgrading, while green finance will play a moderating part. This paper studies the role of green finance and renewable energy technological innovation on industrial structure in China. We found that RETI has contributed significantly to the adjustment of industrial structure. The research results of PVAR (Panel Vector Autoregressive) model further prove this dynamic and continuous positive promotion. The threshold regression results indicate that with the improvement of green finance, there is a non-linear relationship between RETI and industrial structure. In areas where green finance is relatively low, RETI can inhibit the upgrading of industrial structure. When the degree of green finance development is relatively high, the influence of RETI on industrial structure is remarkably positive. Heterogeneity analysis shows that in eastern China, renewable energy technological innovation has significantly promoted the industrial structure upgrading. Therefore, policy makers should take various measures to expedite the green finance development and strengthen the green finance support to renewable energy technology innovations. Chinese government has the need to continue to implement related green credit policies and expand the source of green funds. • Study the impact of renewable energy technology innovation on industrial structure. • Green finance is a moderating variable. • Threshold regression model is used to study nonlinear relationship. • Renewable energy technology innovation positively impacts industrial structure. • Green finance has a positive moderating effect. [ABSTRACT FROM AUTHOR]

Green economic growth and sustainable development are inextricably linked, and encouraging green economic growth has practical implications in today's world. In this context, this study examines the impact of environmental regulation on renewable energy development and China's green economy from 1990 to 2018. We look at how environmental regulations affect green economic growth and renewable energy technologies. Using the Meta frontier SBM model's super-efficient data envelopment analysis, it is possible to determine the relative level of green economic growth in China's provinces based on their energy efficiency. Environmental regulations were also assessed using an improved fuzzy inclusive appraisal method. Finally, we investigate the possible mechanism and discuss our findings. The study discovered an unreliable indicator of green growth during the research period, attributed to the non-serious nature of government strategies. The results show that the DEA method consistently confirms how the piece is put together. On the other hand, the sub-results models invariably affect countries with high GDP per capita. Finally, the impact of environmental regulations on the growth of renewable energy sources was studied. Green economic growth depends on environmental regulation policies, which contribute significantly to renewable energy development. Population size, economic development level, technological innovation, industrial structure, urbanization, environmental regulation, and FDI influence green economic growth, but the spatial effect of each influencing factor varies. The findings of this paper form the basis for China's pursuit of green economic growth and the development of renewable energy policies. • Proposed a novel framework on R & D expenditures, low carbon energy transition and green economic growth. • Study analyzes the effects of the multiple R & D expenditures in the context of Belt & Road Initiative economies. • Dynamic linking is considered when the connections of players' change. • Established vibrant empirical model and suggested implications for green economic recovery. [ABSTRACT FROM AUTHOR]

This research examines the effect of environmental policy stringency on green innovation in renewable energy technology and whether the green innovation response differs with varying degrees of environmental policy. Based on panel data of 33 countries over the period 1990–2015, we show that a stringent environmental policy does encourage green innovation in renewable energy technology, and this impact is more pronounced in OECD countries and high-income countries. More specifically, a stringent non-market-based environmental policy induces more patents in renewable energy generation. The findings also show that a stringent environmental policy yields green innovation for geothermal energy, hydro energy, and marine energy, but not for wind energy and solar energy. Heterogeneity analysis suggests that innovation capacity and environmental pressure enhance the impact of environmental policy stringency on green innovation in the renewable energy field. Finally, the paper presents that clean energy investment plays the role of a mechanism through which environmental policy stringency spurs green innovation in the renewable energy field, offering insights into the influence of environmental policy stringency on green innovation. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) technology can directly convert radiation into electricity, which is an important way to construct a low-carbon society. The assessment of five commercially available PV technologies is a representative multi-criteria decision making (MCDM) issue with a large amount of ambiguous and subjective information. Although some scholars have made improvements to the evaluation method, the problem of uncertain information has not been completely solved. A novel approach is put forward in this paper based on cloud model and grey relational analysis (CMGRA), integrating the fortes of cloud model for dealing with uncertainty and the merits of grey relational analysis for overcoming the errors caused by small sample size. An illustrative example of PV technology selection is applied to validate the feasibility and effectiveness of CMGRA. The newly proposed approach provides both sustainable choices for technology selection and policy supports for governors to construct low-carbon society. • An integrated MCDM method is developed to select the sustainable PV technology. • Environmental and social criteria are considered in selection of PV technology. • The randomness in technology decision making is handled with cloud model theory. • The grey relational analysis method is used to manipulate problem of small sample size. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) technology can directly convert radiation into electricity, which is an important way to construct a low-carbon society. The assessment of five commercially available PV technologies is a representative multi-criteria decision making (MCDM) issue with a large amount of ambiguous and subjective information. Although some scholars have made improvements to the evaluation method, the problem of uncertain information has not been completely solved. A novel approach is put forward in this paper based on cloud model and grey relational analysis (CMGRA), integrating the fortes of cloud model for dealing with uncertainty and the merits of grey relational analysis for overcoming the errors caused by small sample size. An illustrative example of PV technology selection is applied to validate the feasibility and effectiveness of CMGRA. The newly proposed approach provides both sustainable choices for technology selection and policy supports for governors to construct low-carbon society. • An integrated MCDM method is developed to select the sustainable PV technology. • Environmental and social criteria are considered in selection of PV technology. • The randomness in technology decision making is handled with cloud model theory. • The grey relational analysis method is used to manipulate problem of small sample size. [ABSTRACT FROM AUTHOR]

One of the strategic objectives of the European Union is to increase the renewable energy consumption level, in a market which brings together technological, financing and customer engagement innovations. However, little is known about the impact of the financial sector on renewable energy consumption. The aim of the paper is to examine the effect of financial development on renewable energy consumption using a panel data of 28 countries in the European Union (EU) over the period 1990–2015. Our research is based on a panel fixed effects model, where renewable energy consumption is given as a function of income, energy prices, financial development, and foreign direct investments. The results of the empirical analysis show that all three different dimensions of financial development (banking sector, bond market, and capital market) have a positive effect on the share of renewable energy consumption. Additionally, our results show that capital market development does not influence renewable energy consumption in the new EU Member States. Our empirical results give valuable insights into how best to deploy capital in the renewable sector, in order to provide cost-competitive options to customers, with the final objective of expanding higher value-added services. • The effect of financial development on renewable energy consumption is analysed. • All three different dimensions of financial development have a positive effect on the share of renewable energy consumption. • The capital market development does not influence renewable energy consumption in the new EU Member States. • Financial development can promote the implementation of green technologies. [ABSTRACT FROM AUTHOR]

As climate warming intensifies, reducing greenhouse gas emissions has become a national consensus for many countries. Green finance plays an important role in promoting energy efficiency and lowering such emissions, but there is scant literature that analyzes the impacts and mechanisms of green finance on energy efficiency. Based on China's provincial panel data from 2010 to 2018, this research measures the green finance index using the panel entropy weighting method and systematically evaluates the relationship between green finance and energy efficiency using the fixed-effects model. The results show the following. (1) Green finance significantly contributes to energy efficiency and remains the same after a series of robustness tests such as endogeneity treatment, replacement of explanatory and interpreted variables, and replacement of regression models. (2) Green technology innovation and energy structure optimization are the transmission mechanism of green finance for energy efficiency, which means that green finance improves energy efficiency by promoting green technology innovation and energy structure optimization. (3) There is regional heterogeneity, temporal heterogeneity, and industry heterogeneity in the impact of green finance on energy efficiency. The positive effects of green finance on energy efficiency are more pronounced in resource-dependent regions, regions with irrational industrial structure, north regions, industrial sectors, and after 2013. The conclusions of this paper offer some policy recommendations, including promoting the development of green finance, building a cooperation platform for green finance and technological innovation, enhancing the depth and breadth of renewable energy utilization, and building differentiated green finance strategies according to local conditions. [ABSTRACT FROM AUTHOR]

Different from the existing studies, this study find the two paths that green finance development (GFD) affects renewable energy development are the clean biased technical progress path and financial constraint path, and at its different stages, there are significant differences in driving effects of GFD and government policies. Through empirically analyzing impact of GFD on renewable energy development with mediation effect model and China's provincial panel data in 2007–2019, this study obtains following conclusions: On the one hand, GFD can promote energy technology innovation to bias to clean energy technology. On the other hand, it can ease the enterprises' finance constraint, thus promotes renewable energy development. In initial stage of renewable energy development, government's supporting policy is the key driving factor, and role of GFD is weak. In growth stage of renewable energy development (accounting for more than 20%), GFD significantly promotes renewable energy development, and driving role of government supporting policy has gradually weakened. In view of above results, the policy recommendations of this paper are, first, government departments and financial institutions should form joint force to promote the growth of green finance scale. Second, balance administrative means and market tools according to the regional renewable energy development stage. [ABSTRACT FROM AUTHOR]

Abstract: Distributed generation expansion planning (DGEP) has been frequently reported in the literature around the world. In this scope, renewable technologies which are considered as a kind of distributed generations are developing due to their environmental benefits. However, only a few renewable energies have proven to be competitive so far, while their economic viability is also limited to certain regions of the world. In this paper, an encouraging mechanism is proposed in favor of clean technologies in the planning process. This mechanism is defined based on a grant function of emission not polluted which is paid to DG owners to promote renewable and clean technologies. In the planning process, a multi-objective optimization algorithm is applied to produce a Pareto set of optimal planning schemes by taking into account different objective functions (cost and grant functions). The best planning scheme among the Pareto set is chosen based on a composite utility which are obtained through a Monte Carlo simulation of uncertain situations. Distributed generation technologies which are considered in this paper are conventional and renewable technologies, namely photovoltaic (PV), wind turbine (WT), fuel cell (FC), micro turbine (MT), gas turbine (GT), and reciprocal engine (RE). To assess the ability of the proposed method, a typical distribution system is used for expansion planning under two environmental scenarios. [Copyright &y& Elsevier]

Several studies of distribution network enhancement focused only on the optimization of either the integration of distributed generations (DG) or network reconfiguration. However, very few researches have been done for distribution network reconfiguration simultaneously with the DG location and sizing. This paper presents a multi-objective management operations based on network reconfiguration in parallel with renewable DGs allocation and sizing for minimizing active power loss, annual operation costs (installation, maintenance, and active power loss costs) and pollutant gas emissions. The time sequence variation in wind speed, solar irradiation and load are taken into consideration. An efficient evolutionary technique based on the Pareto optimality is adopted to solve the problem. A fuzzy set theory is used to select the best compromise solution among obtained Pareto set. The obtained results prove the efficiency and the accuracy of the suggested method for the network manager to find the optimal network configuration simultaneously with DG location and sizing considering multiple criteria. [ABSTRACT FROM AUTHOR]

Abstract: The implementation of the Carbon Pollution Reduction Scheme (CPRS) and the expanded Renewable Energy Target (RET) which drive to a smart grid application are likely to have a significant and ongoing impact on energy markets in Australia. One of the key issues is the transmission pricing scheme. The main task in the development of the transmission service charges are it must be non-discriminatory, transparent, economically efficient, and allow full recovery of costs. Most importantly, the pricing strategies should implement fairness and practicality. Currently, the National Electricity Market (NEM) has been using the Cost Reflective Network Pricing (CRNP) and Modified Cost Reflective Network Pricing (MCNRP) method for allocating the transmission service charges among the load. The drawbacks of both methods are: (1) the load will be burdened with high TUoS charges as this charges are only paid by load (2) inaccurate transmission usage evaluation as the contributions of counter-flows are totally being neglected. Therefore, in this paper, a novel transmission pricing method which is called Distribution Factors Enhanced Transmission Pricing (DFETP) method is introduced in order to increase the utilization efficiency of the network as well as to promote the green technology in a market environment. The proposed approach is tested on the 10-machine IEEE 39-bus (New-England) system and 59-bus system of the South East Australian power system using Matlab simulation program to prove its effectiveness. [Copyright &y& Elsevier]

Abstract: Solar photovoltaic technologies have for some time been promoted as a cost effective means of rural electrification in developing countries. However, institutional structures resulting in poor maintenance have adversely affected the sustainability of past solar projects. In Fiji, the Renewable Energy Service Company (RESCO) program is the latest attempt to promote solar-based rural electrification in a fee-for-service model, aiming to remove the high upfront capital costs associated with solar technologies and using a public–private sector partnership for maintenance. This paper assesses the program using survey and interview data. Major flaws are identified, relating to incorrect treatment of principal–agent problems, information asymmetries, motivational problems, and resourcing of government agencies. General lessons for fee-for-service solar home system models emerge, including that incentives for stakeholders must take centre stage in designing and administering such programs, and that active government support and ownership are required to make programs sustainable. [ABSTRACT FROM AUTHOR]

Abstract: Renewable energy sources (RES) are mainly used in the electrical sector. Electricity is not a storable commodity. Hence it is necessary to produce the requested quantity and distribute it through the system in such a way as to ensure that electricity supply and demand are always evenly balanced. This constraint is actually the main problem related to the penetration of new renewables (wind and photovoltaic power) in the context of complex energy systems. Moreover the design of optimal energy resource mixes in climate change mitigation actions is a challenge faced in many places. The paper analyzes the problem of new renewable energy sources penetration. The case of Italian scenario is considered as a meaningful reference due to the characteristic size and the complexity of the same. The various energy scenarios are evaluated with the aid of a multipurpose software taking into account the interconnections between the different energetic uses. In particular it is shown how the penetration of new renewable energy sources is limited at an upper level by technological considerations and it will be more sustainable if an integration of the various energy uses (thermal, mobility and electrical) will be considered. A series of optimized scenarios are developed. In each case the maximum RES penetration feasible with the constraints was defined. Then analysis is applied to an energy system model of Italy showing how an integrated development of CHP and electric mobility can aid a further integration of wind and photovoltaic energy power. Finally the primary energy consumption saving possible in case of consistent penetration of intermittent renewables and CHP was identified. [ABSTRACT FROM AUTHOR]

Abstract: Utilization of renewable energy sources and the application of environmentally sound energy technologies are essential to sustainable development and will help to secure the quality of living and the well-being of the future generations. Turkey presently has considerable renewable energy sources. The most important renewable sources are hydropower, wind, solar, geothermal, and biomass. The use of renewable energy as a topic to study energy and its forms permits a novel way to motivate students, particularly those who energy topics taking conscience with the environment. This paper presents the analysis and classification of renewable energy sources and how to find out their origin and a way to motivate students in energy topics related to renewable sources and also, the development of didactic competencies in special blended learning arrangements for educationalists, trainers and lecturers in adult education in the field of renewable energies in Turkey. [ABSTRACT FROM AUTHOR]

Abstract: At the beginning of 2010, only 2000 wind megawatts had been installed offshore. Although the first offshore wind farm experiment took place in 1990, most of the facilities built up to now have been pilot projects. Then, offshore wind power can be considered as an incipient market. However, just at this moment, the growth of this technology finally seems to be happening, being several countries at the top of its development (the United Kingdom, Denmark, Holland, Sweden and Germany). This current situation, the raw materials problems and the general commitments to reduce the emissions of greenhouse gases are leading to predict a promising future for this technology. This paper deals with a brief revision of the state of the art of offshore wind power, followed by a critical discussion about the causes of the recently growth that is currently happening. The discussion is based on the comparison of offshore wind energy with other renewable energies (like onshore wind, marine hydrodynamics, hydraulic, solar, etc.) and even with conventional power. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a long-term dynamic multi-objective planning model for distribution network expansion along with distributed energy options. The proposed model optimizes two objectives, namely costs and emissions and determines the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on distributed generation units and network reinforcements over the planning period. An efficient two-stage heuristic method is proposed to solve the formulated planning problem. The effectiveness of the proposed model is demonstrated by applying it to a distribution network and comparing the simulation results with other methods and models. [Copyright &y& Elsevier]