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Fusion is very attractive as a potential energy source, but it is taking a long time to develop into a commercial reality. Given the challenges of climate change and the need for dispatchable power as a complement to renewable energy sources that vary on daily and seasonal timescales, there is great enthusiasm internationally to accelerate the commercialization of fusion energy. Forty-five private companies around the globe, with total financing of $7.1 billion, are engaged in the development of fusion energy. In the United States, the White House has put forward a "Bold Decadal Vision for Commercial Fusion Energy," with bipartisan support from Congress. To develop commercial fusion energy, certain goals must be met. A wide variety of approaches are being pursued to meet these goals. [ABSTRACT FROM AUTHOR]

With the escalating integration of renewable energy sources (RESs) within the manufacturing sector, the synergy between energy and production management has gained paramount importance. To harmonise energy efficiency with production effectiveness, the concept of energy-aware scheduling, comprising off-line, on-line, and hybrid scheduling, has been introduced. While each approach has merits and drawbacks in handling unexpected disturbances, recovering optimal performance, and managing computational costs, their designs often tend to be ad hoc. Currently, there is a lack of a systematic design that effectively balances computational costs, robustness to unexpected disturbances, and optimal performance. Moreover, existing results do not fully leverage the flexibility in factories integrated with Renewable Energy Sources (RESs). In response, this study introduces the paradigm of event-triggered hybrid scheduling (ETHS) to achieve a balance among optimality, robustness, and computational cost by fully exploring the system's flexibility. The efficacy of ETHS is empirically demonstrated through a comprehensive case study involving a real-world manufacturing facility. Diverse scenarios are scrutinised, accompanied by sensitivity analyses pertaining to parameter choices. The outcomes conspicuously underscore the potency of ETHS in facilitating the harmonious alignment of energy and production management within the ambit of manufacturing industries. [ABSTRACT FROM AUTHOR]

With increasing environmental concerns and energy crisis, a variety of renewable energy sources (RES) are being increasingly utilised worldwide. However, the integration of RES such as wind power and photovoltaics in large-scale can lead to increased load fluctuations, which can undermine the overall environmental benefits and pose risks to the secure and stable operation of the power system. To mitigate this challenge, a two-stage electricity production scheduling is developed incorporating energy storage system (ESS) and dynamic emission modelling (DEM). In the first stage, a multi-objective mixed integer programming model schedules the production of RES, increasing penetration rate and system stability. In the second stage, a data-driven dynamic emission model is developed to optimise the load allocation of thermal power unit to reduce the carbon emissions. Furthermore, a flexible operating reserve strategy is proposed to handle the uncertainty resulting from the intermittent character of RES. Experimental results demonstrate that the proposed method effectively schedules the production of RES thereby alleviating the contradiction between high RES utilisation and stable system operation. Compared to the benchmark model, the proposed method can reduce the carbon emissions and total cost of the system by 20.34% and 10.65%, respectively. [ABSTRACT FROM AUTHOR]

This work considers an industrial production site partially powered by a decentralised energy system based on intermittent renewable energy sources. Our objective is to simultaneous plan the industrial production and the energy supply in this site so as to minimise the total cost. A new way of modelling this combinatorial optimisation problem is proposed: it relies on the extension of a multi-product single-resource small-bucket lot-sizing model called the proportional lot-sizing and scheduling problem. This extension involves among others sequence-dependent changeover times overlapping multiple periods and energy-related constraints. Our numerical results show that the resulting mixed-integer linear programming model enables to obtain good-quality production and energy supply plans with a computational effort much smaller than the one required by a previously published large-bucket lot-sizing model. [ABSTRACT FROM AUTHOR]

Many countries are devoting considerable efforts to replace fossil energy with renewable energy to achieve 'Carbon Neutrality'. Straw-based bioenergy is considered as a potential substitute of fossil energy. This paper investigates the government regulations (i.e. penalty and subsidy policy) for a straw-based bioenergy supply chain consisting of power plants and farmers, in which the three parties are of bounded rationality. We develop a three-party evolutionary game model and obtain the evolutionary stable strategies of the three parties. We establish the dynamic penalty model and show that the dynamic penalty policy can encourage power plants to use bioenergy and farmers to collect bioenergy than the existing static penalty policy. Our results further demonstrate if the proportion of the farmers choosing the 'Collecting bioenergy' strategy is low, the government should choose the 'Penalizing the farmer' strategy; otherwise, the government should choose the 'Penalizing the power plant' strategy. We also extend our model to the government's subsidy policy and compare it with the penalty policy. Specially, when the proportion of the power plants (farmers) using (collecting) bioenergy is high, if the government's subsidies are lower than penalties, the government should choose the subsidy policy; otherwise, the government should choose the penalty policy. [ABSTRACT FROM AUTHOR]

In the past two decades, we have witnessed an unprecedented acceleration of the energy transition in China. The implications of the ongoing energy transition will reverberate across the established energy, economic, and environmental systems. This study constructed a new comprehensive evaluation index system to evaluate the energy transition in 30 Chinese provinces from 2000 to 2019. We found that the average score of China's provincial energy transition in 2019 (0.518) was higher than that in 2000 (0.410); the average score of provincial energy transition from 2000 to 2019 was only 0.445. During this period, Yunnan, Sichuan, Qinghai, Fujian, andIEA 2011 Guangdong were the top five provinces in terms of average scores, and Tianjin, Ningxia, Shanxi, Shanghai, and Hainan were the five provinces with the lowest average scores. We also found that provincial energy transition has significant peer-group characteristics, including region, income level, provincial energy trade, and international energy trade. Moreover, compared with the energy transition measured by comprehensive evaluation, the energy transition measured by energy structure underestimated the quality of energy transition in the eastern and central regions. It overestimated the quality of energy transition in the western region. [ABSTRACT FROM AUTHOR]

An experiment was conducted to determine the digestible energy (DE) of insect fat (IF) from black soldier fly larvae (BSLF) for growing pigs. Saturated fatty acids (SFA) were the dominant group of fatty acids in the IF, with lauric acid (C12:0) and palmitic acid (C16:0) comprising the greatest concentrations in this group. Linoleic acids (C18:2) and oleic acids (C18:1) were the main unsaturated fatty acids. The IF contained 37.63 MJ/kg gross energy and 2.55 g/kg nitrogen. During the experiment, a DE bioassay was performed wherein growing pigs were fed one of the two experimental diets (either a maize–wheat–barley–soy basal diet or a diet containing 50 g/kg IF plus 950 g/kg of the basal diet). The DE of the IF was calculated based on the differences between the DE values of basal and test diet (substitution method). The DE of the IF was determined to be 36.86 MJ/kg. The IF contains a DE level comparable to vegetable oils, including soybean, rapeseed, corn and palm oils. The results showed that the examined fat from BSLF is a good source of available energy and can be incorporated in pig diets as an alternative energy source. [ABSTRACT FROM AUTHOR]

The stability and reliability of modern power systems, especially those with several renewable energy sources, strongly rely on load frequency control (LFC) and automatic voltage regulation (AVR) for frequency and voltage control under inconstant load demands. In this study, a new cascade tilt integral derivative-fractional order proportional tilt integral derivative (TID-FOPTID) controller is presented that is polished through the salp swarm algorithm (SSA) for LFC of a multi-area power system with AVR in all control areas. The system integrates capacitive energy storage (CES) and deals with governor dead-band and generation rate constraint nonlinear effects in a thermal-hydro-gas three-area multi-source power system (TAMSPS). The analysis of results, due to the SSA-based TID-FOPTID controller compared to TID-FOTID and TID-FOTID + 1 shows a positive outcome. Integrating CES brings additional improvement in the system performance, the overshoot/undershoot, and settling time are minimized. Finally, the sensitivity analysis reveals that the suggested controller will be effective and reliable for enhancing the frequency stability of the complex power system with a high RES integration level. [ABSTRACT FROM AUTHOR]

The power conversion efficiency (PCE) of dye-sensitised solar cells (DSSCs) measures their solar energy conversion performance. With PCEs below 15%, significant energy loss occurs, leading researchers to seek improvements to reduce fossil fuel dependence and enhance DSSCs as an alternative energy source. However, predicting PCE theoretically is challenging due to its dependence on various parameters. In this work, the improved normal model was used to predict the PCE accurately using DFT and TD-DFT of four nanocomposites consisting of catechin natural compound attached to carboxylated graphene quantum dots (GQD) that have been further doped at the centre/edge and decorated with a boronic group. The nanocomposites have been adsorbed on a TiO2 cluster for PCE estimation. This is the first attempt of using decorated GQD with boronic groups in a DSSC and estimating its PCE. The results show that the PCE of catechin improved from 0.077% to the range of 3.96% – 12.61% (B1-CG-C@TiO2 – B2-CG-C@TiO2). This was due to the improved short-circuit current density ($J_{sc}$ J sc ) and fill factor (FF) of all the nanocomposites and the improved open-circuit voltage ($V_{oc}$ V oc ) of all nanocomposites except B1-CG-C@TiO2 in comparison to catechin. This means all the designed nanocomposites are more promising candidates than catechin. Highlights: Adsorption at carboxyl group is the most stable site among hydroxyl and GQD base. The improved normal model gives accurate $V_{oc}$ V oc results. All designed nanocomposites exhibited higher PCEs than isolated catechin. Edged doping exhibited the highest $V_{oc}$ V oc , high $J_{sc}$ J sc , and highest PCE of 12.61%. [ABSTRACT FROM AUTHOR]

The article discusses the risks associated with the swift implementation of energy transition projects, focusing on permitting and regulatory risks, social risks, operational risks, ESG considerations, and geopolitical risks. It highlights challenges such as permitting delays, social conflicts, and operational challenges in remote locations. The article also addresses the importance of ESG due diligence, stakeholder mapping, and an integrated approach to managing ESG risks. Additionally, it explores the geopolitical landscape affecting energy transition projects and funding sources for such projects. The authors provide insights into mitigating risks to attract investment and advance energy transition projects efficiently. [Extracted from the article]

The energy transition necessitates hydrogen generation to meet current energy needs. Low-carbon hydrogen (green hydrogen from renewable energy, and blue hydrogen from gas with CO2 removal and storage) is touted as a replacement, with most authors recognising the 'green' credentials of hydrogen. However, this paper examines the impact of hydrogen generation on water resources in the driest inhabited country on Earth – Australia. After analysing water use, the paper then undertakes a detailed analysis of the Australian Certificate of Origin Scheme. The paper concludes that competition over water will need to be considered in both project approvals and certification schemes. [ABSTRACT FROM AUTHOR]

Public-private partnerships have long existed in literature, primarily in the construction sector. However, there is a paucity of research on the research and innovation ecosystem. This research aims to develop a framework for promoting public-private partnerships in research and innovation to foster public-private linkages. Primary data was collected from 192 participants selected from public and private sector organizations. The relative importance index was used to rank key elements for promoting public-private partnerships in research and innovations. The best practices include sharing knowledge, engaging in win-win partnerships, and establishing innovation hubs and intellectual property policies. Effective elements include leveraging innovation in geographical proximity, a supportive regulatory framework, joint financing of research equipment and tax incentives for research equipment. Priority sectors include renewable energy, smart agriculture and education. Websites and direct engagements are essential platforms for engaging in collaborations. The research recommends that the government should provide seed funding to support the early phases of the research and extend tax exemptions for research equipment and infrastructure. Research institutions should establish innovation hubs and operationalize intellectual property policies. The study proposes a framework for promoting public-private partnerships in research and innovation in a developing country like Zambia. [ABSTRACT FROM AUTHOR]

Renewable energy projects are increasingly being implemented at scale to meet global climate goals, often targeting lands on the margins of the state and affecting the livelihoods of Indigenous or marginalized populations. This article argues a need for project-developers, investors and rights advocates to consider the potentially significant 'gap' between their expectations that the rights of local populations will be settled at the start of a particular investment and the conflicts over rights, recognition and benefits that emerge during implementation that risk derailing investments. This is particularly relevant for renewable investments, as their claims to global and national benefits divert attention from their local impacts. Empirically, this is explored through the case of the Lake Turkana Wind Power project in Kenya. Based on interviews and literature review, the article examines the relations between the key stakeholders in this project by acknowledging their various 'ways of seeing' rights. Ruling elites often see rights as settled once they have been written into law and investors assume that rights have been dealt with at the project's start, but local populations typically begin exploring their rights following project-induced changes. The interaction of stakeholders with such diverse views has important implications for the practice of human rights in the context of renewable energy investments. [ABSTRACT FROM AUTHOR]

This article proposes a solution to the Dynamic Economic Emission Dispatch (DEED) problem, which incorporates wind, solar and plug-in electric vehicles (PEVs) into the optimization challenge. The new model, called Wind-Solar-Plug in Electric Vehicle (WSPEV) DEED, utilizes an optimization technique called the Oppositional-based Equilibrium Optimizer (OEO) method with the Weibull and Beta distributions to model wind and solar resources. The charging and discharging patterns of PEVs are also considered in the model. The proposed approach is evaluated through several scenarios involving Renewable Energy Sources (RESs) and PEVs, and the simulation results demonstrate the effectiveness of the proposed model in achieving a sustainable and cost-effective power system. The WSPEV DEED model provides a valuable solution to the DEED problem, which is crucial for successfully integrating RESs and PEVs into the power system for a sustainable future. [ABSTRACT FROM AUTHOR]

Post-apartheid, the South African economy remains characterised by persistent unemployment and world-leading inequality. Transitioning towards more equal and inclusive economic outcomes is hampered by an industrial base concentrated in powerful firms in upstream resource-based carbon-intensive sectors. Pursuing industrialisation in the context of the push towards decarbonisation and sustainability by significant trading partners depends on a massive investment programme in renewable energy and specific high-emitting sectors and developing linkages between sectors to target a just, equitable, and inclusive transition that tackles the country’s deep-rooted inequalities. This paper evaluates South Africa’s main development finance institution, the Industrial Development Corporation’s role in green industrialisation in South Africa. It investigates whether the investments made and the orientation of the IDC positively impacts the structural transformation of the economy, using disclosed and publicly available data. It suggests a set of criteria with which the IDC can assess the transformational impacts of its climate change funding. [ABSTRACT FROM AUTHOR]

AbstractThis study investigated the reduction of CO2 and its conversion into formic acid in a developed double-electrode layer trickle bed electrochemical reactor (TBER) to combat global warming. VulcanXC72 carbon black and polytetrafluoroethylene (C-PTFE) mixture was pasted on stainless steel mesh to form the cathode layers which was characterized using SEM,BET,FTIR, porosity and particles size distribution. Using K2CO3 alkaline solution, CO2 was in situ reduced over the cathode bed suggesting a renewable energy source to replace hydrocarbon fuel. The anode’s plates reduces the reactor voltage and improve the current distribution. The effect of cell voltages, gas and liquid flow rates, K2CO3 concentrations, and temperatures were systematically studied and formic acid production was predicted as well. CO2 was successfully reduced in this system and reached its maximum conversion at 94.47% in 40 min at a reduction temperature of 10 °C which is attributed to the enhancement of CO2 solubility in the electrolyte at low temperatures. At the best conditions, formic acid production increased with time and reached 266 ppm after 60 min, presenting this process as an alternative to the traditional methods. The development of a two-layer reactor working in trickling flow mode is used for the first time in such highly complex processes, where each layer acts as a separate reactor from the other layer. Moreover, to avoid using expensive metals as electrocatalysts and make the process eco-friendly, a conductive carbon black was used as an electrocatalyst. Despite this promising results, the system was designed to be scalable for industrial use and used in wastewater treatment and methane, methanol, and ammonia production. [ABSTRACT FROM AUTHOR]

AbstractWastewater treatment plant sludge contains a high concentration of organic compounds that can be used to produce fuel viahydrothermal carbonization (HTC). This study investigated the combustion reactivity and kinetic parameters of hydrochars produced to understand the combustion behavior of the solid fuel derived from HTC. The hydrochar was produced at various temperatures ranging from 150 to 300 °C, reaction times ranging from 30 to 150 min, and solid loadings ranging from 10% to 30%. The combustion behavior of sewage sludge (SS) and hydrochar was evaluated using thermogravimetric analysis with a constant air flow rate (100 mL/min) and heating rate (10 °C/min) from ambient temperature to 900 °C. It was observed that the HTC temperature, reaction time, and solid loading influenced the combustion characteristics and kinetics of the hydrochar. Additionally, the hydrochar exhibited higher ignition and burnout temperatures and a lower peak temperature than SS, indicating superior performance and reactivity in combustion. The combustion kinetic analysis also revealed that the hydrochar had a range of lower activation energy (29.12–41.60 kJ/mol) than SS (52.95 kJ/mol). Therefore, hydrochar derived from SS has the potential to be used as a substrate for solid fuel production for future renewable energy sources. [ABSTRACT FROM AUTHOR]

AbstractThe development of photovoltaic systems and wind turbines reduces the carbon footprint (CFP) of energy generation. However, these systems deteriorate the stability of the national power system (NPS). The important stabilizing element of the Polish NPS are coal-fired power plants. Since the cold startup of these units takes several hours, the stability of the NPS forces the boilers to operate so that the power can be increased quickly. Therefore, it will be impossible to abandon coal-fired units in the next years, and the boilers will be modernized to reduce their CFP. An important option is to replace coal with a fuel with a lower CFP, e.g. biomass. This paper deals with the CFP for different types of biomass. It also considers methane emissions from coal mines. The CFP for coal and biomass was compared with the CFP for green ammonia. Using 0-dimensional calculations of the boiler, the need to modernize the heating surfaces was assessed when replacing 50% and more of coal with biomass. The changed fouling of heating surfaces was taken into account. The problem of reducing harmful phenomena such as corrosion, erosion and slagging associated with such a change of fuel is also discussed. [ABSTRACT FROM AUTHOR]

As the demand for renewable energy sources increases, the vulnerability of solar panels to lightning strikes becomes a critical concern. This research explores the correlation between lightning-induced voltage fluctuations and the resultant damage intensity on solar panels. The study adopts a systematic approach, first investigating the correlation between lightning-induced voltage assessment using 30kV, 60kV and 90 kV impulse voltage with multi-stage Marx impulse generator and the damage intensity on monocrystalline and polycrystalline solar panels. A portable active infrared thermography equipment with tCam-Mini was employed to conduct this research with wireless streaming. Furthermore, the study integrates Convolutional Neural Network (CNN)-based image classification techniques to enhance the efficiency of damage assessment. The results highlight the potential of neural networks in improving the accuracy and speed of image classification for damaged and undamaged samples. The findings contribute valuable insights into enhancing the resilience of solar panel systems against lightning strikes, ultimately advancing the reliability and sustainability of solar energy infrastructure. A new CNN model was developed to classify the images obtained from thermography with 90.21% accuracy for greyscale and 85.31% accuracy on thermal images. [ABSTRACT FROM AUTHOR]

This paper discusses the opportunities and policy levers to increase the use of low-temperature geothermal resources in New Zealand for decarbonising primary industries, in particular, covered crops. Geothermal heat (geoheat) is a local, reliable, resilient and sustainable energy source. Low-temperature geothermal energy (220°C) is available in the Taupō Volcanic Zone with low awareness of the nationwide availability of lower temperature resources. Covered crop growers in New Zealand, needing to decarbonise their operations, are investigating the potential of utilising geoheat, following the example of the Netherlands. The Netherlands has strategically invested in low-temperature geothermal energy, utilising 80 °C water resources, from ∼ 2 to 3 km below the surface to heat greenhouses. Internationally, risk mitigation schemes and insurance programmes have proven pivotal policy instruments for fostering geothermal adoption. This paper discusses the opportunities that the adoption of using low-temperature geothermal provides to New Zealand drawing upon successful models from other countries. [ABSTRACT FROM AUTHOR]

Polarization surrounding nuclear power has intensified in Korea following the 2011 Fukushima disaster. In 2017, President Moon Jae-in implemented an energy policy that shifted the focus from nuclear to renewable energy, a departure from previous governments’ approaches. Additionally, Moon administration supported various participatory governance initiatives to minimize social conflicts, including participatory deliberative polls concerning the construction of the Shin-Kori nuclear power plants. However, the Moon administration’s policy was followed by polarization between nuclear and renewable energy factions escalating toward the end of the term. We employed mixed-method approaches combining media and survey analyses to investigate this issue. The results demonstrate that, despite initially appearing to be policy neutral, renewable energy alternatives underwent polarization under the Moon administration. We emphasize the need to investigate effective strategies for utilizing participatory projects as tools to break, rather than reinforce, the political gridlock impeding energy transition. [ABSTRACT FROM AUTHOR]

With a single-switched DC-DC converter, a hybrid approach is proposed for a fast-charging (FC) dc to dc converter with the controller for an electric vehicle charging station (EVCS) that combines solar photovoltaic (PV), fuel cells (FC), and a battery energy storage system (BESS). The proposed hybrid technique integrates a radial-basis-function-neural-network (RBFNN) and a student-psychology-optimization-algorithm (SPOA); commonly known as the RBFNN-SPOA technique. The PV-FC hybrid electric vehicle systems, like controllers, electric vehicle, and the vehicle's power source, are displayed. The proposed converter architectures have less voltage waveform changes, a low voltage stress on semiconductor power sources, and a high-voltage ratio of conversion. The proposed method is to use FC successfully at battery charge states and varied radiation levels. The FC in the controller of SPOA may change the inputs and outputs depending on the battery state of charge (SoC) and PV irradiation. Similarly, the needed input-torque for the motor is forecasted by the recalling recurrent neural network controller using several manually produced torque signals. The performance of the proposed technique is evaluated in MATLAB and is compared to ant colony optimization (ACO), crow optimization algorithm (COA), and fuzzy logic controller (FLC) approaches. According to the results, the efficiency of the proposed technique is 99.17%. [ABSTRACT FROM AUTHOR]

With the increasing focus on reducing carbon emissions, hydrogen has emerged as a promising alternative energy source. However, the safe transportation of hydrogen poses challenges due to its potential impact on the integrity of pipeline materials. This study aims to investigate the effect of hydrogen charging time on the plastic behavior and ductile fracture characteristics of API 5L X42 pipelines, which are commonly used for transporting hydrocarbons. Tensile tests were conducted on various types of hydrogen-charged specimens at room temperature to assess different fracture modes. Hydrogen was introduced into the specimens using a cathodic electrolytic method, and 24-h charging time durations were considered. Finite element analyses were performed on standard dog-bone and notched tension specimens to evaluate the plastic behavior, employing the Swift hardening law to model the flow stress. Numerical analyses were conducted to determine the loading path leading to fracture initiation. A damage framework based on the Hosford–Coulomb model was utilized to predict ductile fracture under non-proportional loading conditions. The findings of this study provide insights into the fracture behavior of pipelines under hydrogen exposure, aiding in the design and assessment of safe and reliable hydrogen transport systems. [ABSTRACT FROM AUTHOR]

Over the past two decades, the use of microwaves for physical foaming of polymers has undergone significant advancements. Typically, the preparation of polymer foams during physical foaming relies on heat transfer heating, which results in temperature gradients and consumes significant time and energy. In contrast, microwave-assisted physical foaming offers a simple, convenient, fast, and cost-effective approach for obtaining polymer foams. These features render microwaves an alternative clean energy source that can replace or complement the conventional heating in various foaming processes. This review provides an overview of recent research on the application of microwaves to five different methods for preparing polymeric foams, namely batch foaming, bead foaming, steam foaming, salt immersion foaming, and 3D-printing. The study also highlights key challenges and opportunities for the development of microwave foaming processes and identifies potential areas for future research. [ABSTRACT FROM AUTHOR]

Renewable energy, particularly solar power, is clean, cost-effective, and virtually limitless, making it an essential source of energy for developing countries. In the Kurdistan region, however, dependence on fossil fuels remains high, with 85 percent of electricity generated from these sources, whereas solar power contributes less than 1 percent. This study addresses this disparity by employing Boolean logical analytical hierarchy process techniques and a comprehensive set of criteria encompassing technical, ecological, and economic factors to identify suitable sites for solar power plants in Duhok Governorate. The results indicate that 68.5 percent of the governorate's area is deemed suitable for solar power station construction, with the most promising zone comprising 132.2 km2 and capable of generating more than 8,000 megawatts of solar energy. Notably, most suitable areas are concentrated in the south and southwest, particularly in the districts of Bardarash, Shekhan, and Semel. This study paves the way for a significant shift toward renewable energy in northern Iraq. Identifying vast suitable areas for solar power plants offers a practical roadmap to reduce dependence on fossil fuels, provide a clean energy source, and enable a large-scale solar power project. This study empowers policymakers, energy companies, and investors to make informed decisions toward realizing this renewable energy potential, ultimately transforming the energy landscape in northern Iraq. [ABSTRACT FROM AUTHOR]

Enhancing agricultural productivity in developing countries is crucial for attaining the sustainable development goal 2.4 by 2030 through integrating information and communication technology (ICT) and renewable energy. Thus, this study investigates the role of ICT, renewable energy, and agricultural credit in enhancing agricultural productivity in developing countries from 2000 to 2021. This study has used the 'Driscoll-Kraay and the Method of Moments Quantile Regression' for robust empirical analysis. The estimated results indicate that renewable energy, ICT, and agricultural credit can enhance agricultural productivity in developing countries. The robustness analysis, however, indicates that the moderation effects of the interaction of ICT with renewable energy and agricultural credit with ICT and renewable energy have a weak and insignificant effect on agricultural productivity over the increasing quantiles. From a policy viewpoint, it is suggested that coherent and effective policies be implemented to encourage the advancement of formal credit institutions to bridge the gap between farmers and lending institutions offering flexible lending options to farmers. Thus, this helps farmers to access and deploy modern technologies and renewable energy in the agricultural field, which ensures sustainable agricultural practices to foster agricultural productivity while enriching environmental quality in developing countries. [ABSTRACT FROM AUTHOR]

Transportation infrastructure plays a significant role in exacerbating climate change as it contributes to a substantial increase in carbon dioxide (CO2) emissions. The sole economic sector in which European countries have not succeeded in reducing greenhouse gas (GHG)emissions is the transportation industry. Therefore, reducing transport-related emissions is a primary focus of emphasis in the European Union's efforts to meet its climate targets. Accordingly, this study analyzes the impact of renewable energy use, patent development, and energy taxes in the transport sector on the three different modes of transport-related emissions (aviation, road, and rail) in the 10 highest-income countries of the European Union over the period 2008–2020. The study uses the novel half-panel jackknife estimator for this analysis. The results of the estimation show that patents contribute to the reduction of CO2 emissions in aviation and rail transportation, while renewable energies are only effective in rail transportation. In the context of road transportation, energy taxes are effective in mitigating CO2 emissions. Based on these findings, it is recommended that European Union policymakers promote the use of electric vehicles and eco- friendly means of transportation in road transport through energy taxes, increase the use of renewable energy sources such as biodiesel in rail transport, and reduce CO2 emissions by supporting patents that promote green innovations in the aviation sector. [ABSTRACT FROM AUTHOR]

Environmental innovation is pivotal in tackling climate change by offering diverse and practical solutions to reduce carbon footprints, promote resource conservation, and enhance ecological sustainability. As anthropogenic activities continue to accelerate global environmental degradation, innovative solutions are imperative for mitigating the impacts of climate change and fostering sustainability. However, the effectiveness of these innovations is threatened by global uncertainties and rising income inequalities. Uncertainties in geopolitical landscape and economic disparities may impede the development and widespread adoption of eco-friendly technologies and practices. Given the above background, this study empirically investigates the influences of environmental innovation, world uncertainty and income inequality on renewable energy generation for a balanced panel of 58 countries between 1990 and 2020. The estimated models also control for the effects of globalisation and economic growth. After diagnosing for necessary panel diagnostic tests including cross-sectional dependence, heterogeneity, and panel unit-root, the Westerlund cointegration test confirms a significant long-run relationship between the variables of the study. Using panel Augmented Mean Group (AMG) estimation, the results reveal that while environmental innovation continues to promote the renewable energy generation, global uncertainty and income inequality hamper it. More importantly, the moderating effects of world uncertainty and income inequality reduce the favourable impact of environmental innovation on renewable energy generation. Besides, economic growth and globalisation continue to play critical roles in speeding up the quest for renewable energy. The PCSE estimation technique confirms the significance of these baseline findings. Potential policy implications are also discussed. [ABSTRACT FROM AUTHOR]

One possible way to achieve environmental sustainability is by addressing the issue of rising CO2 emissions, which significantly cause climate change by intensifying the greenhouse gas effect. The Organization for Economic Cooperation and Development (OECD), which substantially contributes to global CO2 emissions, necessitates a paradigm shift towards using clean energy sources and promoting green innovations to ensure environmental sustainability. Thus, this study aims to inspect the role of renewable energy use, green technology innovation, political stability, and fiscal decentralization in attaining environmental sustainability by limiting CO2 emissions for seven OECD economies from 2000 to 2019. This study has employed the 'Cross-Sectional Augmented Autoregressive Distributed Lag and Augmented Mean Group Estimator' for robust empirical analysis. The results indicate that renewable energy use, political stability, and fiscal decentralization can mitigate CO2 emissions and ensure environmental sustainability in OECD economies. In contrast, green technology innovation exhibits an insignificant effect on CO2 emissions. Furthermore, the moderation effects of fiscal decentralization and political stability exhibit a negative relationship with CO2 emissions. Notably, this study advises OECD nations to encourage regional cooperation to ensure political stability and devolution of fiscal powers to promote green innovation and renewable energy use to achieve sustainable goals. [ABSTRACT FROM AUTHOR]

Why do some European countries succeed in developing offshore wind power? This study compares the Spanish and Danish cases from the 1970s to 2021. By completing the literature on both policy failure and success with concepts from psychology, the study stresses the relevance of public funding instability, federal architecture, intertwined political interests and policy discourse as dimensions that impact the rise of offshore wind power. Drawing on this framework, the Danish success suggests that strong leadership based on a shared objective can create efficient institutions able to avoid veto players and secure financial investments over time. This process can boost the rise of a self-confident discourse that will reinforce the virtuous circle. [ABSTRACT FROM AUTHOR]

This study investigates the impacts of China's carbon mitigation policies spanning from 2011 to 2023 on the stock returns of seven distinct nonrenewable and renewable energy markets. We apply contagion tests, examining variations in linear, asymmetric, and external dependence to identify the transmission of policy shocks from the coal market to energy markets. Among the analyzed carbon reduction policies, both cap-and-trade schemes and coal capacity cut policies present stronger evidence of policy contagion between the coal and energy markets compared to national development plans. Additionally, nonrenewable energy markets demonstrate more pronounced evidence of policy contagion than renewable energy markets during the implementation of carbon reduction plans. [ABSTRACT FROM AUTHOR]

The virtual power plant (VPP) has been recognized as an effective way to facilitate penetration of renewable and distributed energy resources in electricity markets. This paper introduces an adaptive curtailment strategy for a VPP comprising a wind power plant and uncertain demand, and explores the economic advantage of adaptively adjusting wind power curtailment. A two-stage stochastic model is proposed to deal with the uncertainties in wind power generation (WPG), load demand and market prices. In the model, the bid decision is made in the face of uncertainties in the first stage, while the control (curtailment) decision is made based on realized uncertain parameters in the second stage. This paper provides the closed-form optimal curtailment decision and characterizes the optimal bid decision. An efficient binary search algorithm is developed for optimizing the bid decision. By using a distribution-free approach, we show that as the prediction accuracy of WPG improves, the optimal bid decision converges toward the expected minimal power exchange, leading to a decrease in expected operational cost with diminishing marginal return. Numerical experiments based on real-world data demonstrate that compared with the existing greedy strategy and coordinated strategy, the proposed model can decrease the expected operational cost up to 16.9% and 11.0%, respectively. [ABSTRACT FROM AUTHOR]

For the renewable energies (REs), solar power generation is currently the most common. Some countries are currently competing to develop Space Solar Power (SSP) projects, hoping to take the lead in this race to obtain energy from space with high conversion efficiency. In Taiwan, the SSP generation project is expected to cost US$4 billion in research and development in the next five years, and subsequent costs will be astronomical. From an energy management perspective, these proposed improvement measures will be powerful to improve the effectiveness of generating electricity for the SSP system and the solar panels on the ground, so that obtained energy from them can be integrated into an integrated energy (IE), as well as corresponding recycling measures and a reliable energy storage system (ESS) are used. This ESS can store much solar energy to avoid the phenomenon of duck curve and negative electricity prices. Therefore, combing with the concept of the IE, there is a theoretically performable solar energy policy for energy transition in the future. However, in Taiwan, such energy transition using the REs concerns must be considered not only in terms of energy availability at an affordable price, but also from a political and social perspective. [ABSTRACT FROM AUTHOR]

Robotic fish will become the next generation of submersibles due to their advantages of high propulsion efficiency, high mobility, excellent environmental compatibility and good load capacity. However, short battery life and high charging costs would be the main obstacles restricting the deployment of robotic fish for long–term ocean monitoring and cruises. The present methods of either using a mother ship or laying cables are very expensive. In order to greatly reduce the cost, a nearby cheap charging station is necessary. In this paper, a comprehensive review of underwater automatic charging methods and systems for robotic fish based on the existing marine renewable energy conversion technology is carried out, including robotic fish underwater docking and charging technology. Based on the review and comparative analysis, a design idea for a novel and feasible system for underwater charging for a school of robotic fish through renewable energy is proposed. [ABSTRACT FROM AUTHOR]

The integration of renewable energy sources (RESs) into current power networks addresses rising global energy demand and mitigates greenhouse gas emissions. This transition shifts the role of frequency regulation from synchronous generators to power converters, serving as interfaces between the grid and RESs. This paper proposes a hybrid method for optimizing power flow in hybrid power-generating systems. The proposed hybrid technique is the combined execution of an Adaptive-Neural-Fuzzy-Inference-System (ANFIS) and Pelican Optimization Algorithm. Hence it is named as ANFIS-POA technique. POA optimizes current and voltage controllers, while ANFIS predicts optimal system parameters. Implemented in MATLAB, the proposed strategy achieves an impressive efficiency of 96%, outperforming existing strategies like genetic algorithm (GA) and particle swarm optimization (PSO). With a faster settling time (0.56 s), a shorter rising time (1.32 s), and a reduced peak time (5.78 s), the proposed approach performs better than existing methods. Additionally, it significantly lessens system costs (Rs. 99,450) and demonstrates superior statistical performance in terms of lower error rates and improved key metrics like accuracy, precision, and recall compared to existing methods. [ABSTRACT FROM AUTHOR]

Conversion of the conventional electrical grid into a smart and sustainable grid involves several considerations. The primary factors, however, are renewable energy penetration, associated storage systems, and energy generation costs. This research endeavors to conduct a thorough survey and analysis of the solar irradiance on various hydropower locations in India, including Run-of-River (RoR), Run-of-River with Pondage (RoRP), Reservoir Storage (S), Multi-Purpose Storage (MP) and Pumped Storage Systems (PSS). The hydroelectric projects in rural Indian regions have been the subject of the proposed case study. As a preliminary study, the probabilistic variables like minimum, maximum, and mean solar irradiance are calculated for 252 High-Scale Hydropower Plant locations (HSHPs) using the past 40 years day ahead solar radiation data to identify the high-irradiance hydropower plant location in each state of India. This study concludes that the maximum mean solar irradiance location in each state as these sites are well suited for hybrid PV-hydro systems. The identified high-irradiance locations 40 years day ahead data sets are analyzed employing 8 machine learning models and 2 deep learning models. This analysis aims to forecast solar irradiance, serving as a crucial foundation for the initial phase of the implementation of hybrid PV-hydro. [ABSTRACT FROM AUTHOR]

Inaccessibility and expensiveness of vital infrastructures are the main problems in some urban and rural areas to supply fresh water, sustainable energy, and wastewater treatment. An effective solution is the integration of several systems in an environmentally friendly technology of the photosynthetic microbial desalination cell (PMDC). The aim of this study is to assess the process characterisation of an algae-based PMDC, which was loaded with a high-strength mixture of human feces and urine (HFS). The PMDC was also able to efficiently remove COD and total nitrogen of HFS by 50% and 94%, respectively. The maximum power density, voltage, and desalination efficiency of 362.5 mW/m², 175.2 mV, and 60% were accomplished. Adequate parameter adjustment led to a remarkable maximum of 2.25 g/L.d in the ion removal rate. In addition, an energy balance was governed showing that zero or positive net energy in PMDC is feasible by replacing the main energy consumers. Based on the results, this type of MDC had a high efficiency for simultaneous saline water desalination and HFS treatment, which makes it attractive for further studies of upscaling and its application in remote areas. [ABSTRACT FROM AUTHOR]

AbstractTime-varying coefficient models can capture evolving relationships. However, constructing asymptotic confidence bands for coefficient curves in these models is challenging due to slow convergence rates and the presence of various nuisance parameters. A residual-based sieve bootstrap method has recently been proposed to address these issues. While it successfully produces confidence bands with accurate empirical coverage, its applicability is restricted to strictly stationary processes. We introduce a new bootstrap scheme, the local blockwise wild bootstrap (LBWB), that allows for locally stationary processes. The LBWB can replicate the distribution of the parameter estimates while automatically accounting for nuisance parameters. An extensive simulation study reveals the superior performance of the LBWB compared to various benchmark approaches. It also shows the potential applicability of the LBWB in broader scenarios, including time-varying cointegrating models. We then examine herding effects in the Chinese renewable energy market using the proposed methods. Our findings strongly support the presence of herding behaviors before 2016, aligning with earlier studies. However, contrary to previous research, we find no significant evidence of herding between around 2018 and 2021. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

As a renewable energy source, ocean wind energy plays an important role in addressing challenges such as global energy shortages and climate warming. In the past decade, the offshore wind power industry has developed rapidly. However, its development has also inevitably affected local social, economic and environmental aspects. Therefore, a timely understanding of offshore wind power dynamics development is crucial for its healthy and sustainable development. Based on this, this study designs and develops a more economical, reliable and real-time offshore wind turbine (OWT) extraction method by combining deep learning and the Google Earth Engine (GEE) cloud computing platform. The method consists of two main steps. The first part utilizes multiple semantic segmentation models to construct a multi-model detection method to initially detect OWTs. The second part utilizes the GEE cloud computing platform for installation time detection and secondary purification processing of the preliminary results. The results show that the number of global OWTs reached 13,609 by 2023, and the accuracy of the detection results reached 99.93%. China has been the fastest-growing country in offshore wind power in the last decade, from installing only 4 units in 2015 to installing 6,775 units in 2023 and surpassing the UK in 2020 and becoming the country building the most OWTs worldwide. Currently, 85% of the world's OWTs are located in China and European North Sea waters. Additionally, other regions have great potential for offshore wind development. Finally, this study provides the world's most up-to-date and complete OWT dataset, which can provide data support for research on marine ecological and environmental protection, marine spatial planning, and socioeconomic benefits. [ABSTRACT FROM AUTHOR]

Frequency control in a microgrid (μG) is problematic due to low inertia of distributed generators (DGs) and uncertainty of the renewable energy source-dependent DGs. Consequently, deploying distributed storage units (DSUs) in a μG is crucial for quickly arresting frequency deviations. The electric vehicle (EV) technology, as DSU, is being preferred over conventional energy storage due to its lower cost and slower degradation rate, facilitating demand side response in a μG. The adoption of the EV technology necessitates an open communication infrastructure in the μG, with a pre-existing communication time delay (CTD). This article explores the impact of EV integration on load frequency control (LFC) performance of a multi-microgrid (MμG) system and determines an optimal CTD value simultaneously. A cyclical parthenogenesis algorithm-optimized 2DOF-FOPID controller is implemented to obtain dynamic responses of the MμG system. Simulation results reveal significant improvements in dynamic responses when integrating EVs in the MμG, with a 97.33% increase in objective function value. The recommended controller also outperforms standard controllers in terms of how quickly frequency and tie-line power variations settle down to zero. Thus, the proposed controller meets the LFC requirements. Robustness of the proposed LFC scheme is tested against parametric variations in the MμG system. [ABSTRACT FROM AUTHOR]

The global demand for lithium is steadily increasing, driving an increased focus on exploration efforts worldwide. Lithium, a crucial metal for lithium-ion batteries (LIBs) used in renewable energy technologies, is vital in the global drive to reduce carbon emissions. India’s ambitions to become a manufacturing hub for LIBs and achieve 100% electric vehicle (EV) sales by 2030 require significant quantities of lithium. However, challenges due to limited domestic reserves within the country, prompting efforts to define new exploration targets and develop existing lithium occurrences. Recent discoveries in northern Jammu and Kashmir and southern Karnataka highlight promising lithium deposits. This study focuses on India’s lithium exploration within pegmatite belts across various cratonic blocks, identifying significant potential for lithium exploration and mining. Notably, spodumene-rich pegmatites are found in Karnataka’s Dharwar Craton, while lepidolite-rich pegmatites exist in Rajasthan’s Aravalli-Delhi Fold Belt and the Madhya Pradesh-Chhattisgarh region. Regions like Bihar-Jharkhand, Maharashtra, Odisha, and Assam-Meghalaya also exhibit promise for lithium exploration. These findings emphasize the diverse lithological settings where lithium exploration can be strategically pursued in India. This study recommends adopting modern exploration techniques and developing cost-effective extraction technologies to advance India’s lithium exploration efforts. These initiatives are crucial in meeting the escalating demand for lithium and advancing India’s clean energy objectives in the transition to renewable energy sources. [ABSTRACT FROM AUTHOR]

Recently, there has been a shift in the global energy landscape to move to reliable, clean, and eco-friendly renewable energy sources to address global issues such as climate change and greenhouse gas emissions. One such energy source is wave energy; researchers attempt to develop models that can accurately forecast the availability of wave energy as an alternative energy source. In this paper, an Artificial Neural Network (ANN) model along with statistical models such as time series models, and regression models are proposed for forecasting wave energy at a site in Fiji using the wave height and wave period as the independent variables. The performance of the proposed models developed is compared using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and the goodness-of-fit ($R^2$R2) value. The proposed model is then further benchmarked with the naïve model. The empirical results reveal that the proposed ANN model outclassed all the other models and was more efficient and accurate in forecasting wave energy than the regression and time series models. By accurate wave modelling and by incorporating impedance matching, maximum power generation can be achieved. [ABSTRACT FROM AUTHOR]

This manuscript proposes a hybrid method for energy management (EM) of a solar photovoltaic (PV) hybrid microgrid (MG) for the residential distribution system (DS). The proposed approach integrates the single candidate optimizer algorithm (SCOA), and gradient boost decision tree algorithm (GBDT), called the SCOA-GBDT algorithm. The main contribution of this manuscript is to (a) effectively achieve battery storage, solar PV, and loads to improve energy savings and lessen the loss of conversion; (b) effectively handle solar photovoltaic, battery storage, and loads to recognize cost-effective power distribution using the proposed technique; and (c) effectively handle weak photovoltaic power prevalent in the DC side of MG by an auxiliary-battery arrangement to preserve energy. The proposed energy management strategy lowers the conversion losses in the residential DS. Here, the dc loads are provided by a solar photovoltaic, the utility-grid provides the AC loads, and an auxiliary-battery bank is considered for storing the energy. Then, the performance of the proposed technique is done in MATLAB software and is compared to different existing approaches. From the simulation outcome, it is concluded that the proposed approach reduces costs and losses compared to the existing approaches. [ABSTRACT FROM AUTHOR]

This study considers an estimator for the asymptotic variance-covariance matrix in time-series quantile regression models which is robust to the presence of heteroscedasticity and autocorrelation. When regression errors are serially correlated, the conventional quantile regression standard errors are invalid. The proposed solution is a quantile analogue of the Newey-West robust standard errors. We establish the asymptotic properties of the heteroscedasticity and autocorrelation consistent (HAC) covariance matrix estimator and provide an optimal bandwidth selection rule. The quantile sample autocorrelation coefficient is biased toward zero in finite sample which adversely affects the optimal bandwidth estimation. We propose a simple alternative estimator that effectively reduces the finite sample bias. Numerical simulations provide evidence that the proposed HAC covariance matrix estimator significantly improves the size distortion problem. To illustrate the usefulness of the proposed robust standard error, we examine the impacts of the expansion of renewable energy resources on electricity prices. for this article are available online. [ABSTRACT FROM AUTHOR]

This article explores the use of Acridine Yellow G (AYG) as a photocatalyst for the synthesis of pyrano[2,3-d]pyrimidines in water. The researchers discovered that AYG was most effective as a catalyst at a loading of 0.2 mol%. The reaction yielded a compound called 4a with a 96% yield. The method was successful with various substrates and the resulting products were easily obtained and purified. The article also provides a plausible mechanism for the photocatalytic process and includes optimization studies for the solvent and light source. Additionally, the article discusses the application of AYG as a photocatalyst in a tandem Knoevenagel-Michael radical cyclocondensation reaction. The study found that visible light could be used as an energy source at room temperature in an air atmosphere for reactions in an aqueous medium. The method was efficient, utilized non-toxic solvents, and achieved excellent yields. Furthermore, the reaction could be scaled up to meet industrial and environmental requirements. [Extracted from the article]

This study examines the impact of investment freedom, technological innovation, renewable energy, and economic growth on load capacity factor (LCF) within the context of Sustainable Development Goals (SDGs) 7 and 13 for a group of high investment freedom countries (Luxembourg, Germany, Austria, Australia, Canada, Denmark, Netherlands, United Kingdom, Chile, Singapore, New Zealand, United States of America, Belgium, Finland, Uruguay, Latvia, Spain, Sweden, and Switzerland). Furthermore, this research assesses the impacts of achieving carbon neutrality by 2030. The data set covers the years between 1995 and 2019. Moreover, the validity of the load capacity curve (LCC) hypothesis is analyzed in all countries. Long-run coefficients are estimated using the Regularized Common Correlated Effects (rCCE) estimator, and the robustness analysis is performed using Common Correlated Effects (CCE) estimators. The overall assessment of the panel reveals that the LCC hypothesis is invalid in the selected nations, with the exception of Belgium. Other findings indicate that investment freedom reduces the LCF for New Zealand. However, investment freedom increases LCF, improving environmental quality in Latvia. Technological innovation decreases LCF for Singapore and increases it for Germany. Renewable energy increases LCF for the UK and Spain. Finally, policy implications for improving environmental quality are discussed. [ABSTRACT FROM AUTHOR]

With an emphasis on the European Renewable Energy Clusters (RECs), the study examines the impact of local and global collaborations on technological competitiveness within RECs. Drawing on illustrative examples from wind and solar energy clusters in Europe, the research challenges the prevailing notion of the need for extensive global collaborations for innovation. Instead, it highlights the pivotal role of local collaborations and technologically homophile community ties in sustaining technological competitiveness within green high-tech clusters. The article contributes to the green-tech innovation and clusters literature by providing valuable insights into how companies in clusters engage in patent collaborations, particularly in the context of green energy technologies. The study spans the period from 1998 to 2018, offering a comprehensive analysis of collaborations in two mature renewable energies: wind and solar. It particularly investigates the Wind cluster in Navarra, Spain and the Munich Solar cluster in Germany. [ABSTRACT FROM AUTHOR]

Among the most significant non-linear challenges for power network design and smooth functioning of current modern updated power system networks is the optimum power flow (OPF) problem. Importance of the electrical system modeling has recently come to light due to the incremental use of energy from renewable sources in power systems networks. The goal is to use wind, solar and tidal sources to recreate the issue of OPF. In this work, Weibull, Lognormal, and also Gumbel probability distribution functions were applied to simulate the uncertainties of wind, photovoltaic, and tidal energy system. Additionally, by adding test scenarios of unpredictable wind, solar and tidal energy systems involving minimization of the cost function, loss of active power, voltage deviation, and increase stability of voltage. In accordance with the chosen thermal producing units, the solutions were evaluated using different locations using IEEE 30-bus systems of testing that incorporate renewable energy sources. The proposed power system planning problem was solved by multi-objective function where unified power flow controller are utilized as flexible AC transmission systems controllers via recently introduced optimization algorithms and the simulation outcomes of the aforementioned technique have been compared with Multi Objective Adaptive Guided Differential Evolution algorithms. The adaptive improved flower pollination algorithm (AIFPA) is a strong and reliable algorithm that is presented in this work. The AIFPA can efficiently deal with many kinds of high-complexity objective regions in multi-objective optimization situations. Utilizing an IEEE 30-bus test system, the suggested approaches' performance was examined and evaluated for a range of objective functions. The simulation results obtained from the proposed algorithm were effective in finding the optimal solution compared to the results of the meta-heuristic algorithm and were reported in the literature. [ABSTRACT FROM AUTHOR]

This paper presents a Hybrid Renewable Energy system combining multiple sources of renewable energy, such as PV, Wind, and energy storage devices, to provide a reliable and sustainable power supply. Cascaded converters are used to efficiently transform and manage the energy from these sources. To achieve optimal performance and reliable operation, a real-time closed-loop control algorithm is designed and implemented for the cascaded converter. The control algorithm facilitates the smooth integration of energy from various renewable sources, optimizing the utilization of available resources and ensuring a consistent power supply. The algorithm maximizes the energy conversion efficiency of the cascaded converter, reducing energy losses and minimizing waste. It also optimizes the integration of renewable sources, regulates output parameters, and ensures efficient energy conversion. [ABSTRACT FROM AUTHOR]