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Vietnam, a country in Southeast Asia, is anticipated to experience an increase in energy consumption due to the growth of its manufacturing and industrial sectors, which aims to establish Vietnam as the world's new production hub. Fossil fuels, which are ecologically unfriendly and quickly running out, are now Vietnam's primary energy source. Due to the detrimental effects of fossil fuels on the environment, we can apply strategic decision-making in the industrial sector to choose the best alternative for a renewable energy resource (RER). RERs such as solar energy, wind energy, solid waste energy, biomass energy, geothermal energy, biofuel energy, and hydropower energy are important for generating energy and will be crucial for the survival of humanity, the planet, and other living things in the future. The actions of RER-based industrial development must be encouraged since they will make a significant contribution to overcome environmental impact limitations. The 2-tuple linguistic q -rung orthopair fuzzy set (2TL q -ROFS) is a novel development in fuzzy set theory that presents a decision-making method for selecting the most appropriate alternative. In this paper, we develop a family of the 2TL q -ROF Maclaurin symmetric mean aggregation operators such as the 2TL q -ROF Maclaurin symmetric mean (2TL q -ROFMSM) operator, the 2TL q -ROF dual Maclaurin symmetric mean (2TL q -ROFDMSM) operator and its weighted forms. We also look into a few of the proposed operators' properties and special cases. Then based on 2TL q -ROFS, a new Decision Making Trial and Evaluation Laboratory (DEMATEL) model is constructed, which can use the decision makers' preferences to get the optimum objective weights for attributes. Next, we extend the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to 2TL q -ROF version which not only covers the uncertainty of human cognition but also gives decision makers a larger space to represent their decisions. Utilizing this model the best RER for Vietnam is selected. The outcomes of the hybrid 2TL q -ROF-DEMATEL-TOPSIS method reveal that among the energy resources, hydropower energy ranked highest, followed by biofuel energy. [ABSTRACT FROM AUTHOR]

This paper discusses the effects of green technology innovation, renewable energy consumption and renewable energy investment on environmental quality. Panel data covering 81 countries from 2001 to 2020 are used to estimate the effects. The results indicate the following: First, at the total sample level, the effect of green technology innovation, renewable energy consumption and renewable energy investment on Carbon dioxide (CO 2) emissions is significantly negative at the level of 10–1%; Second, at the subsample level, the green technology innovation and renewable energy consumption of non-Belt and Road (B&R) and high-income countries significantly affect CO2 emissions; while the green technology innovation and renewable energy consumption of middle- and low-income and B&R countries have no significant effect on CO2 emissions; Third, the endogeneity and robustness tests of the model verified that this empirical process is credible. Based on the above results, this paper proposes a series of policy implications needed to achieve carbon emission reduction and environmental quality improvement. [ABSTRACT FROM AUTHOR]

The principal aim of Sustainable Development Goals (SDGs) or Global Goals is to attain a much better and more sustainable future for all. In recent times, microgrids have attracted much attention, given the transformation of software systems and raising the bar for customers in terms of sustainability, reliability and cost predictability. Consequently, there is a need for microgrid development in remote areas. Our paper proposes a hybrid renewable energy microgrid (HREM) that focuses on the affordable, efficient, reliable and sustainable growth of energy systems. This paper presents an optimized off-grid HREM for a remote locality in the south Indian state of Tamil Nadu. The proposed approach employs a configuration of photovoltaic (PV) arrays, AC loads, a diesel generator set, a wind turbine and a battery energy storage system (BESS) connected to AC/DC buses and designed to satisfy the power requirements of a remote, rural community residential area. The primary objective was to carry out a cost optimization of the designed system. A sensitivity analysis was also conducted to obtain a feasible solution from the optimized results and evaluate the robustness of the design. The primary objective was to carry out a cost optimization of the designed system. A sensitivity analysis was also conducted to obtain a feasible solution from the optimized results and evaluated the robustness of the design. A detailed analysis was made by comparing the PV + DG set + battery and PV + wind + DG set + battery and it was found that the former offered better results for the particular location. Overall, it was observed that our proposed system offers renewable energy for residential loads that is relatively inexpensive, reliable and sustainable. [ABSTRACT FROM AUTHOR]

Solar photovoltaic (PV) systems have gained significant attention due to their easy implementation and availability, where proper energy management should be highly concentrated for a successful PV power utilization. In the traditional works, various controlling techniques have been developed for reactive power compensation. But, it lacks with the issues of reduced system performance, increased loss, and high harmonics. Hence, this paper aims to develop a new controlling methodology, named the Synthesis Segmental Multilevel Converter (SSMC) for reactive power compensation in a three-phase grid system. Initially, it extracts the maximum amount of power from the solar PV systems by using an Enhanced Perturb and Observe (EPO) method. Then, the panel separation is performed and the three-phase power input is given to the SSMC converter, where the synchronization and switching pulse generation processes are performed. During synchronization, integrated techniques such as Proportional Integral (PI), Fuzzy Logic Controller (FLC), and Improved Artificial Neural Network (IANN) are utilized to maintain the voltage, magnitude and phase angle in the same level. Consequently, the Inductance Capacitance (LC) filtering technique is applied to reduce the harmonics distortion in the signal. After that, the Park transformation is used to perform the dq0 to abc transformation, which is implemented for reducing the high volume of error. Finally, the error-free signal is fed to the three-phase grid system with reduced harmonics. During experimentation, both the simulation and analytical results have been taken for analyzing the performance of the proposed technique. Moreover, it is compared to the existing algorithms for proving the betterment of the proposed methodology. [ABSTRACT FROM AUTHOR]

Hydrogen energy has an advantage over conventional fossil energy because of its clean and low-carbon features, while its stability gives it an advantage over renewable energy sources such as hydropower, photovoltaic (PV) power, and wind power. Using hydrogen as a fuel can achieve zero carbon emissions or even net zero emissions at the end of energy conversion. Moreover, with hydrogen as the carrier, an energy system of multi-energy complementarity will be established by coupling multiple energy systems such as power grids, gas grids and heat networks, which can realize the comprehensive utilization of renewable energy sources in an efficient, stable, and flexible manner. Based on the "dual carbon" goals, this paper targets sectors with high carbon emissions represented by electric power, steel and transportation, analyzes the feasible path of using hydrogen energy to promote deep carbon reduction, and points out the obstacles faced by hydrogen energy development in various sectors. On account of the current development and expected prospects, this paper proposes that the current focus of hydrogen energy industry is to coordinate the development of industrial sectors and regions, build a pattern that can facilitate the industry's systematic and concerted development, address key technical challenges (such as green hydrogen production or hydrogen storage and transportation via pipeline), improve industrial standards, and promote the industry's development in a balanced, coordinated and orderly way. [ABSTRACT FROM AUTHOR]

Green financing is an emergent technology in recent days that supports the nature of environment with reduced carbon emissions. Also, the renewable energy sources or green resources are the most suitable options for improving the economic growth and sustainability of environment. Recently, many industrial organizations over the world were able to provide support to the deployment of green energy projects because it is less harmful to the environment and increases the financial development of country. Therefore, this paper objects to analyze the major effects of green financial strategies for developing the green energy projects. Moreover, it discussed about the recent trends of adopting green projects for ensuring the sustainability of environment with increased energy utilization. In addition to that, it examines various challenges and risks that are associated to the deployment of green financing strategy. The long-term financing, associated risks in project development, minimized return values, and lack of capacity are the major risks of green financing management systems. According to the recent reports, it is stated that the government sectors have an increased responsibility for funding the green projects to support the environment nature. Nevertheless, some of the public and private sectors in different countries are motivating the green energy projects by providing the financial support to the short-term and medium-term organizations for ensuring the sustainability of environment. [ABSTRACT FROM AUTHOR]

In comparison to other alternative energy sources, wind power is more affordable and environmentally friendly, making it one of the most significant energy sources in the world. It is vital to monitor the condition of each wind turbine in the farm and recognize the various states of alert since difficulties with the operation as well as maintenance of wind farms considerably contribute to the rise in their overall expenses. The Supervisory Control and Data Acquisition (SCADA) data-based continuous observation of wind turbine conditions is the most widely used existing strategy to detect the fault early by preventing the wind turbine from reaching a shutdown stage. Several parameters irrelevant to the faults are saved in the SCADA system while the wind turbine is operating. To increase the efficacy of wind turbine fault diagnostics, optimally selected SCADA data parameters are required for fault prediction. Hence, this paper introduces an optimized Convolutional Neural Network (CNN)-based wind turbine fault identification method. For more precise detection, a Self-Improved Slime Mould Algorithm (SI-SMA) is used for the optimal selection of SCADA parameters as well as weight optimization of CNN. The proposed SI-SMA method is an enhanced form of the standard Slime Mould Algorithm (SMA). Eventually, an error analysis and a stability analysis are carried out to check the overall effectiveness of the suggested approach. In particular, the root mean square error (RMSE) of the implemented algorithm is lower, and it is 0.69%, 1.58%, 0.81% and 1.71% better than the existing FF, GWO, WOA and SMA models. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamic links between renewable energy, commodities, and financial stock markets and analyzes the performance of renewable energy investment in an international portfolio diversification strategy across different financial market conditions. By using the dynamic spillover approach, the empirical results show that the renewable energy and oil markets are net emitters of shocks to stock markets. By applying the nonparametric stochastic dominance approach and comparing the optimal maximum Sharpe ratio (MSR) diversified portfolios, the results suggest that the renewable energy index can be a good substitute for traditional diversification, especially during tranquil periods. [ABSTRACT FROM AUTHOR]

In this paper, we explore the economic impact of promotion and realization of an electric vehicle society (EVS). More concretely, this paper emphasizes a computable general equilibrium (CGE) modeling approach to evaluate the following issues: economic impacts of subsidies for promotion of an EVS, the possibility of price reductions, industrial structure change toward an EVS, and modal shift occurring toward an EVS. Our simulation results demonstrate that after applying 5-25% up subsidies to five industries, such as electric vehicle (EV) manufacturing, EV transport, solar power, cogeneration and other transport, the total industrial output and city GDP increase. A large growth rate is found in industries where subsidies are introduced alone with non-ferrous metal industry. However, it is interesting that decreasing proportions are found in oil and coal product, mining, heat supply and gasoline vehicle (GV) transport industries. Moreover, all the commodity prices decrease since subsidies are given to some industries. Hence Toyohashi City's economy shows a direction where the demand for conventional vehicles and energy use are decreased, conversely, the demand for EVs and renewable energy are increased illustrating a different life style from the current one. However, it does not mean that the total CO2 emission is decreased. EV society makes some industrial outputs larger. Due to the fact that some industrial outputs are increased, CO2 emissions of EV manufacturing and nonferrous metal are increased more than decreased industries. Thus, introducing 5-25% subsidies to EV manufacturing, EV transport, solar power, cogeneration and other transport can really represent a realistic alternative society to EVS if the total CO2 emission can be reduced. Therefore, we have to think what can make the total CO2 emission reduced. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel codimension-three-parameter bifurcation analysis of equilibria and limit cycles when integrating Renewable Energy Sources (RESs) power plants with an exponential static load model. The study investigates the effect of solar photovoltaic generation margin, wind power generation margin, and loading factor on the local bifurcation of the modified IEEE nine-bus system. The proposed technique considers the real case of the West System Coordination Council (WSCC), the western states of the USA, by using specific models of RES power plants and static loads. The proposed technique helps to create a set of linearly varying parameters for critical operating points of nonlinear systems. The study explores detailed voltage stability analysis through the examination of bifurcation diagrams. The Hopf, limit-induced, and saddle-node bifurcation branches are identified, defining the parameter space's stable and unstable operational regions. Additionally, the stability regions surrounding the equilibrium points are diligently explored, clarifying the consequences that various bifurcations may exert on these regions. The study offered in this proposed work aids in determining the best ways to monitor and improve these margins while considering system variables and load design. [ABSTRACT FROM AUTHOR]

The boost converters have become one of the most important part of renewable energy plants. The two parameters of boost converters, high voltage gain and high efficiency, have received more attention. In this paper, a boost converter with high voltage gain and high efficiency was used. The proposed topology is a boost converter with high transmission power and reduced voltage stress on the converter components, especially voltage stress on the main switch of the converter. This boost converter has a high efficiency using a new loss reduction technique called active snubber circuit with energy recovery. The proposed nonisolated topology converter was designed with a power of about 500 W, an input voltage of 48 V and an output voltage of 380 V and efficiency of more than 97%. The simulation results of the proposed converter showed different modes of the boost converter. A laboratory model was constructed and the claims of the proposed boost converter were proved. [ABSTRACT FROM AUTHOR]

In fifth generation (5G) systems, green heterogeneous network (HetNet) is capable of achieving energy efficiency by densely deploying renewable-powered small cells. However, the small cells may suffer performance degradation due to the limited backhaul from macro base station (BS) and renewable intermittency. In this paper, we introduce a distributed HetNet architecture in which the renewable-powered small cell BSs collaboratively exchange information and allocate the spectrum and power resources by themselves. Considering the uncertainty of the available spectrum, renewable energy supply and traffic loads, a stochastic optimization problem is formulated to maximize the energy efficiency for distributed small cell BSs. A distributed resource allocation algorithm is proposed to obtain the optimal spectrum and power allocating strategies for each small cell. Finally, the numerical results demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Bioenergy is a significant renewable energy source with great potential for addressing global environmental challenges. This study aims to construct and analyze the patent collaboration network of bioenergy in Chinese provinces along the Belt and Road (BR) initiative. By collecting and analyzing co-patents from the China National Intellectual Property Administration (CNIPA) between 1993 and 2017, this research investigates the network's structure, evolution, and the provincial differences in bioenergy technology development. The results reveal an increasing number of co-patents since 2006. I-I, E-E, E-R, and E-U are common types of collaboration, and this paper believes that E-E will be the most important type in the future. The network is relatively sparse and in its early development stage. However, the cohesion of the network is gradually increasing, and it has good development potential. From the perspective of IPC, the scope of patents for bioenergy is relatively narrow, and the breadth and depth of research need to be improved. Moreover, the study highlights Guangdong as a promising province for bioenergy and emphasizes the close collaboration between provinces along the Belt and Road and those not along it, such as Guangdong and Jiangsu. [ABSTRACT FROM AUTHOR]

Hybrid Renewable Energy Systems (HRESs) are noteworthy devices for enhancement of reliability and performance compared to standalone systems, which are in a combination of more than one energy conversion system in a single unit. The recent developments in materials and technologies of HRESs are cost-effective and are more suitable power options for isolated rural areas. Many researchers have reported to have enhanced the performance of HRESs across India. Hence, this paper presents a comprehensive review of various HRESs that have been reported for their performance evaluation with respect to economic distance limit, techno-economic sensitivity, and optimum analysis. Also, different hybrid combinations are compared based on the factor of Net Present Cost (NPC), Cost of Energy (COE), renewable fraction, maximum renewable penetration, operational cost, and/or emission. Some case studies on various combinations of HRES for telecommunication application, rural electrification and water distillation are discussed and compared. It is concluded from the comprehensive review that there is scope for further studies on hybrid system across the country with adoption of different and newer combinations, materials and thermodynamic approaches. This paper will be helpful to researchers and scientists in understanding the state-of-the-art technologies in the hybrid system. [ABSTRACT FROM AUTHOR]

The development of micro-grid renewable energy system in China has achieved rapid growth in recent years, and the micro-grid renewable energy system has been drawing more and more attention by its flexible operation. Due to the randomness, fluctuation, uncertainty of the wind and photovoltaic renewable generation, abundant flexibility is required to meet the needs of safe, reliable and independent operation of the micro-grid energy system. We need to connect large energy systems to accept outside assistance when the micro-grid renewable energy system is short of adjustment capability. Independent operation and network operation will affect the economic benefit of the micro-grid energy system, so it is practically meaningful to study on the economic benefit evaluation of the micro-grid renewable energy system. This paper proposes a micro-grid energy system operation simulation model about wind and photovoltaic generation, the uncertainty of which is tackled based on the scenario generation and extraction techniques. Based on the proposed indices, the economic benefit could be evaluated by simulating the micro-grid energy system operation. The proposed method is validated by a real micro-grid energy system. [ABSTRACT FROM AUTHOR]

Renewable energy (RE) can play a vital role in ensuring a sustainable energy platform for the future, and in addressing climate change. Investment in RE in the upper middle-income countries (UMICs), which are a major contributor to global carbon dioxide (CO2) emissions, can be an important recovery strategy for mitigating climate change damage. Existing literature suggests that governance (also referred to as 'institutional quality') is an important determinant of renewable energy investment (RE investment). Yet, governance conditions in UMICs have remained almost unchanged in the recent past, despite the substantive increases in income levels and investment in the RE sector. This paper outlines an investigation into the role of governance in RE investment in UMICs and considers whether the influence of governance on RE investment depends on a country's income level. This analysis used pooled ordinary least squares (OLS), panel-corrected standard errors and panel-fixed effects models to evaluate data from 35 UMICs, from 1996 to 2017. The results suggest that good governance raises RE investment in UMICs. In particular, the control of corruption, government effectiveness, regulatory quality and rule of law are statistically significant aspects of good governance that boost RE investment. However, this effect is conditional on the level of economic development (income level) of a country. The marginal effect of governance on RE investment is larger in lower income countries and vice versa. Among the controls, trade openness in UMICs is predicted to have an adverse impact on RE investment. [ABSTRACT FROM AUTHOR]

This paper presents a Stochastic Stackelberg–Nash–Cournot Equilibrium model with continuous market demand distribution to examine the effectiveness of ambient charges as an effective policy measure for reducing nonpoint source pollution in a hybrid scheme. To do so, we consider the supply side of an energy market with hybrid technology that competes in an oligopoly market setting. Within such a setting, each power plant or firm uses a mix of fossil fuels (F) and renewable energy sources (R) to generate power at any given time. The demand for electricity is not realized at the time when the firm (leader) makes the decision. The competition between the two energy sources available to leader is assumed to be of Nash–Cournot equilibria, implying that they use one energy source to generate electricity, whilst holding the other energy source as a constant when the followers reactions are known. Based on the assumption that the demand function is affine and power plants cost functions are quadratic, we obtain the Stackelberg–Nash–Cournot equilibrium. Hence, our analysis provides an interesting insight into the effectiveness of using ambient charges, within the context of a Stochastic Stackelberg–Nash–Cournot competition, as an environmental economic policy measure when included within a robust hybrid scheme. From an economical point of view, this allows pollutants to develop specific control technologies by undertaking research and development (R&D) measures or production processes to maintain emissions standards in a hybrid scheme. From a policy implementations point of view, the environmental authority can use the pollution abatement technology ratio to set ambient charges and industry specific pollutant quantitative limits subject to technological variations. [ABSTRACT FROM AUTHOR]

In recent years, the use of security gateways (SG) located within the electrical grid distribution network has become pervasive. SGs in substations and renewable distributed energy resource aggregators (DERAs) protect power distribution control devices from cyber and cyber-physical attacks. When encrypted communications within a DER network is used, TCP/IP packet inspection is restricted to packet header behavioral analysis which in most cases only allows the SG to perform anomaly detection of blocks of time-series data (event windows). Packet header anomaly detection calculates the probability of the presence of a threat within an event window, but fails in such cases where the unreadable encrypted payload contains the attack content. The SG system log (syslog) is a time-series record of behavioral patterns of network users and processes accessing and transferring data through the SG network interfaces. Threatening behavioral pattern in the syslog are measurable using both anomaly detection and graph theory. In this paper, it will be shown that it is possible to efficiently detect the presence of and classify a potential threat within an SG syslog using light-weight anomaly detection and graph theory. [ABSTRACT FROM AUTHOR]

This paper proposes a control scheme that enhances both the power quality and voltage synchronization of the Self-Excited Induction Generator (SEIG) driven by a wind turbine supplying power to a remote region. A reactive power constraint of SEIG under load disturbances is balanced by a modified Second-Order Generalized Integrator (SOGI) with Fuzzy Logical Controller (FLC) controlled Quasi-Impedance (QZ) source network-based Static Compensator (STATCOM). The combination of STATCOM and the photovoltaic system, battery and flywheel enhances the active power potential of conventional STATCOMs by means of a hybridized STATCOM system. This system is intended for the optimum use of energy generated from renewable energy sources by physical energy storage systems such as flywheels and batteries. This tends to compensate for the deviation of both active and reactive power and hence increase in active power, reliability and system stability. For analyzing device behavior, the dynamic hybrid STATCOM model with FLC dependent ESOGI has been developed. In standalone operation, simulated and experimental findings indicate the increased capability and system efficiency under variable load conditions. [ABSTRACT FROM AUTHOR]

Photo-catalysis has shown a prominent and effective role for the degradation of textile dyes and organic compounds on large scale to keep environment and water reservoirs clean and usable. Photo-catalysts produce hydrogen through water splitting which is an eco-friendly source of renewable energy. Photo-catalysts are used for solar cells construction. Photo-catalysis generates an electron–hole (e−–h +) pair due to light interaction. The electron–hole (e−–h +) pair produces ⋅OH and O 2 • − , which play the main role in degradation process; it leads to redox reaction and oxidizes organic pollutants to H2O and CO2. Major causes of water, air and soil pollution are organic pollutants, heavy metals and non-biodegradable dyes released by different industries. These pollutants especially phenols and dyes have seriously affected the water reservoirs. This paper gives a critical review on visible and solar light photo-catalysis and techniques used for the photo-degradation of hazardous pollutants. A systematic study has been carried out from the published literature on photo-degradation of organic pollutants, factors effecting the photo-degradation and the various operating parameters. The role of semiconductors/nano-catalysts for eco-friendly renewable energy sources, such as hydrogen and solar cells production is also elaborated for future energy crises. The published data has shown that different parameters, such as pH of the system, light intensity, catalyst amount, initial concentration and amount of photo-catalysts play a crucial role for the degradation of various dyes and organic pollutants. Photo-catalysis has also shown significant results for remediation of volatile organic pollutants and acid gases from air. This review has focused to find an efficient, low cost and result oriented photo-catalyst and the effective environment for reaction. The concluded data has shown that photo-catalysis is economically suitable and fit for the treatment of waste water, industrial effluents and energy production. [ABSTRACT FROM AUTHOR]

The regards to widespread impact of distribution networks and ever increasing demand for electricity, some strategies must be devized in order to well operate the distribution networks. In this paper, to enhance the accountability of the power system and to improve the system performance parameters, simultaneous placement of renewable energy generation (REG) sources (e.g., wind, solar and dispatchable distributed generators (DGs)) and capacitors are investigated in a modified radial distribution network with considering ZIP loads. To enhance all network parameters simultaneously to the best possible condition multi-objective functions are proposed and solved using non-dominated sorting genetic algorithm (NSGA II). The employed objectives contain all economical, environmental and technical aspects of distribution network. One of the most important advantages of the proposed multi-objective formulation is that it obtains non-dominated solutions allowing the system operator (decision maker) to exercise his/her personal preference in selecting each of those solutions based on the operating conditions of the system and the costs. It is clear that the implementation of each non-dominated solution needs related costs according to the technology used and the system performance characteristics. However, there is a paucity of objective methodologies for ranking the obtained non-dominated solutions considering economical, environmental and technical aspects. So, in this paper, data envelopment analysis (DEA) is suggested for this purpose. In other words, in this paper, first NSGA II is applied to the siting and sizing problem, and then the obtained non-dominated solutions are prioritized by DEA. The significant advantage of using DEA is that there is no need to impose the decision maker's idea into the model and ranking is done based on the efficiencies of the non-dominated solutions. The most efficient solution is the one which has improved network parameters considerably and has lowest costs. So, using DEA gives a realistic view of solutions and the provided results are for all, not for a specific decision maker. To validate the effectiveness of the proposed scheme, the simulations are carried out on a modified test case 33-bus radial distribution network. [ABSTRACT FROM AUTHOR]

Increased utilization of nonlinear loads in the power distribution system with profound integration of renewable energy requires improved power quality control. This paper proposes a Reformed Second Order Generalized Integrated (R-SOGI) control scheme for enhancing the output of the Dynamic Voltage Restorer (DVR) for the objective of achieving the desired sinusoidal voltage wave shape at the common point of services and harmonic reduction. The DVR incorporates a Solar Photovoltaic (SPV) system using the Z-source Inverter (ZSI), providing the necessary active power to mitigate the voltage sag/swell and power demand. ZSI offers step-down as well as step-up abilities, it makes the converters to operate in the conditions of shoot-through. Therefore, the application of ZSI-based DVR topology seems very promising. The compensating reference voltage is generated by the R-SOGI algorithm, which offers superior output under conditions for grid voltage irregularities, including voltage sag/swell and unbalanced and distorted utility grid voltages. In comparison to DVR based on the VSI voltage inverter (VSI), the response from ZSI-DVR to a reduction of voltage distortions and harmonics is investigated. An experimental SPV ZSI-DVR prototype is developed in the laboratory to check the effectiveness of the controller and is tested under balanced and unbalanced supply and dynamic load conditions. [ABSTRACT FROM AUTHOR]

As a compact city-state with a modern electricity grid and relatively clean energy sources, Singapore seems ideal for the deployment of the battery electric vehicle (BEV). A fleet of 89 BEVs were deployed in a test-bed that was concluded in 2013. The paper conducts a cost-effectiveness analysis and financial analysis of the Renault Fluence ZE and its comparable gasoline model to assess the economics of BEVs. It concludes that BEV adoption in Singapore is both undesirable (due to higher social costs) and unlikely (due to higher private costs) in the immediate and near future. Where 94% of the population live in high-rise apartments, there will be a heavy reliance on costlier communal charging stations, thereby mitigating the operating savings that BEVs could have offered if home chargers were used. Lifetime costs are not as sensitive to changes in oil prices as expected. For the BEV to be socially viable, the breakeven carbon price amounts to S$9,700 per tonne of CO2, which suggests that BEVs are not a cost-effective means of reducing carbon emissions in Singapore, or battery prices would need to be halved. Nevertheless, the study demonstrates that exempting the BEV batteries from taxation could support BEV adoption if that were to be a government objective. [ABSTRACT FROM AUTHOR]

Accurate prediction of wind power is of vital importance for demand management. In this paper, we adopt a cluster-based ensemble framework to predict wind power. Natural groups/clusters exist in datasets and learning algorithms benefit from group/cluster wise learning - a philosophy that is not well explored for wind power prediction. The research presented in this paper investigates this philosophy to predict wind power by using an ensemble of regression models on natural clusters within wind data. We have conducted a series of experiments on a large number of locations across Australia and analyzed the existence of clusters within wind data, suitability of linear and nonlinear regression models for the proposed framework, and how well the cluster-based ensemble performs against the situation when no clustering is done. Experimental results demonstrate prediction improvement as high as 17.94% through the usage of the cluster-based ensemble regression algorithm. [ABSTRACT FROM AUTHOR]

The world is witnessing a transformation from the conventional electrical grid into the smart grid. The smart grid can provide an effective solution to alarming problems associated with a conventional grid with increased reliability, efficiency, and sustainability. Integration of distributed energy resources (DERs) comprising of renewable energy sources (RESs) is a vital component of the smart grid. DERs not only can provide a viable solution for environmental concerns arising due to conventional fossil fuel-based plants, but can also contribute towards the system reliability. However, the integration of DERs is associated with several challenges.  Thus, the successful deployment of DERs in smart grid framework calls for a comprehensive analysis. This paper presents an exhaustive review of various challenges associated with increased penetration of DERs. An organized classification of various technical challenges along with their mitigation measures has been critically reviewed. Smart inverters equipped with advanced control structure are emerging as a potential solution to address these challenges effectively. Hence, a review of smart inverter along with its functional capabilities has also been discussed in this paper. [ABSTRACT FROM AUTHOR]

Refuse-derived fuel (RDF) is a kind of renewable energy source to produce energy for replacement of fossil fuels. Aggressive working conditions in RDF facilities cause the shredder blades to wear out quickly. So, the purpose of this paper was to study the effect of plasma-nitriding process on wear resistance of shredder blades made of AISI D2 tool steel in the service condition of RDF facility. Shredder blades were commercially available from two different suppliers (A and B suppliers). These hardened shredder blades were plasma-nitrided in the mixed nitrogen and hydrogen atmosphere at a volume ratio of 3:1 at 450∘C for 12, 18 and 24 h at a total pressure of 250 Pa. Characterisation of plasma-nitrided layers on the shredder blades was carried out by means of microstructure and microhardness measurements. Wear tests of plasma-nitrided shredder blades were performed under actual working conditions in the RDF facility. Wear analysis of these shredder blades was conducted using three-dimensional (3D) optical measuring instrument GOM ATOS II. The compositional difference of the shredder blades provided by A and B suppliers played an important role on the nitrided layer. The case depth of A-blades significantly increased with increasing plasma-nitriding time. However, the case depth of B-blades was fairly lower at the same nitriding time and only slightly increased with increasing plasma-nitriding time. Plasma-nitriding process significantly improved the surface hardness of the shredder blades. Maximum surface hardness values were achieved at nitriding time of 18 h for both blades. In this case, this increase in surface hardness values was above 100%. At nitriding time of 24 h, the maximum surface hardness of A-blades significantly decreased, whereas this decrease in surface hardness of B-blades was the negligible value. The wear test results showed that plasma-nitriding process significatly decreased the wear of shredder blades; 18 h nitriding for A-blades and 24 h nitriding for B-blades had better wear-reducing ability in the service condition of RDF facility. In these cases, the decreases in the total volume wear loss for A- and B-blades were 53% and 60%, respectively. [ABSTRACT FROM AUTHOR]

Reduced part count multilevel inverters (RPC-MLIs), an emerging technology for grid interfacing applications of renewable energy sources. RPC-MLIs overcome the limitations of conventional two-level and classical multilevel inverters (NPC, FC and CHB) by the use of reduced part counts for generation of same number of levels in the output. Focus of this paper is on to present review of the RPC-MLIs for researchers and engineers and classification of all the topologies. RPC-MLIs are compared considering its circuit complexity and performance. The comparison exposes advantages and disadvantages of topologies, as well as a wide spectrum for future research. This paper also draws the most potential topology in the field of grid integrated applications. Promising topology is simulated here under the same load and input source condition using real time simulator. [ABSTRACT FROM AUTHOR]

This paper proposes distributed generation-integrated unified power quality conditioner (UPQC-DG) with adaptive fuzzy proportional–integral (AFPI) controller to improve the power quality (PQ) of a distribution network. In the proposed system, the DG units are integrated at dc-link of the UPQC to provide additional functionalities. The additional functionalities which are unique to the proposed system is to (i) export the available active power from renewable energy sources to the grid, (ii) compensate long term PQ problems, (iii) compensate voltage interruption. Additionally, the dc-link voltage of the system is controlled by using the proposed AFPI controller to effectively improve the dynamic performance of the system during disturbances. Unlike conventional PI controller, in the proposed controller, the gains are not fixed. It is dynamically adjusted by the fuzzy logic-based intelligent supervisory control system according to system operating conditions. The effectiveness of the proposed system is verified using extensive simulation studies and necessary results are compared with the existing literature. [ABSTRACT FROM AUTHOR]

This paper explores the dynamic relationships between renewable energy consumption and a number of institutional and political factors for a group of countries from Europe, Asia and Latin America spanning the period 1995-2011. The paper employs the methodology of long and short-run panel causality approach as well as the methodology of the panel Error Correction model. The empirical findings provide strong evidence that, after controlling the economic environment, both political and institutional factors exert a strong and statistically significant effect on renewable energy consumption. These findings are expected to have serious implications for policies related to clean energy. [ABSTRACT FROM AUTHOR]

Renewable energy sources and storage devices are combined as a hybrid energy system to provide reliable electricity to the load. Naturally, such sources have distinct voltage–current characteristics. In this paper, a dual input positive output voltage DC–DC converter is used as power electronic interface for integration of the above nature of sources. Different modes of operation of the above converter such as buck, boost and buck–boost are discussed with necessary circuit and equations. A detailed current and voltage stress analysis of various switching devices available in the converter is also discussed. This analysis helps to select the switching devices in an optimized and cost-effective manner. The effect of equivalent series resistance of such storage elements on the output voltage is investigated in detail. The MATLAB simulation of the power converter is carried out, and a prototype of the converter is also fabricated. A power control strategy is proposed for the power converter with the objective of voltage regulation during the load side and source side disturbances. Different experimental analyses of the fabricated converter in the laboratory environment have been conducted, and the test results are presented in this paper. [ABSTRACT FROM AUTHOR]

This paper is a review of uncertainty modeling techniques used in smart grid studies. The literature dealing with uncertainty from various sources in smart grid is analyzed and presented. In a modern power grid, the risk may arise due to different reasons; in-termittent renewable energy sources, uncertain consumer reactions on demand response, driving patterns of electric vehicles, etc. The paper has two objectives. First is to bring out the trends in uncertainty handling techniques used in electrical power system problems, and second to introduce the scope of new risk processing techniques with the perspective of recent smart grid issues. [ABSTRACT FROM AUTHOR]

Solar energy is the abundantly available source of renewable energy with least impact on environment. Direct absorption solar collector (DASC) is the commonly used device to absorb heat directly from sun and make use of it for different heating applications. In the past, many experiments have been done to increase the efficiency of DASC using nanofluids. In this paper, an examination of solar collector efficiency for hybrid CeO2/CuO-water (0.1% by volume) nanofluid under various flow rates and proportions of CeO2/CuO nanoparticles is investigated. The experiments were conducted at flow rates spanning from 20cc/min to 100cc/min and with CeO2/CuO nanoparticles proportions of 1:0, 1:0.5, 1:1, 0.5:1 and 0:1. The efficiency increases from 16.5% to 51.6% when the flow rate is increased from 20cc/min to 100cc/min for hybrid CeO2/CuO (1:1)-water nanofluid. The results also showed an increase in efficiency of 13.8%, 18.1%, 24.3%, 24.9% and 26.1% with hybrid combination of CeO2/CuO at ratios 1:0, 1:0.5, 1:1, 0.5:1 and 0:1, respectively, in comparison with water at a flow rate of 100cc/min. [ABSTRACT FROM AUTHOR]

In this paper, we explore the structural, electronic, thermoelectric and elastic properties of intermetallic compounds ScTM (TM = Cu, Ag, Au and Pd) using density functional theory. The produced results show high values of Seebeck coefficients and electrical conductivity for these materials. High power factor for these materials at room-temperature shows that these materials may be beneficial for low-temperature thermoelectric devices and alternative energy sources. Furthermore, elastic properties of these compounds are also calculated, which are used to evaluate their mechanical properties. The Cauchy's pressure and B/ G ratio figure out that these compounds are ductile in nature. The calculated results also predict that these compounds are stable against deforming force. [ABSTRACT FROM AUTHOR]

Recent studies have publicized that renewable energy resources are the only answer to trim down energy crisis and also able to diminish green house gases. Thats why disperse generation is very significant for sustainable development in power sector. This paper presents an analytical algorithm to find optimal location and a best suitable size of distributed generator (DG) to minimize system losses. Authors also prove that scatter generation is used not only to reduce the gap between demand and supply of power with minimum amount losses, but it can also improve the reliability of distribution system. The results obtained from a case study of 34 bus radial distribution system have proved the efficiency of algorithms for loss minimization and competency of DG to enhance the reliability indices of the conventional distribution system. [ABSTRACT FROM AUTHOR]

In developing countries, firms usually have limited capital, infrastructure, and institutions for technological learning. Hence, knowledge of firms about external and internal learning mechanisms as well as using other firm's experiences lead to reduced cost and time of technological learning. Present paper contributes to renewable energy firm's knowledge by analyzing cause and effect relationships of internal and external technological learning mechanisms. For this purpose, internal and external technological learning mechanisms were extracted by literature review. Then, cause and effect relationships of learning mechanisms in Iranian renewable energy firms were investigated by the DEMATEL method. The results indicate that firms should use a combination of internal and external learning mechanisms to enhance their technological capability. Moreover, intramural research and development, trial and error, reverse engineering of competitor's products, imitation of competitors, and licensing agreement have been the most frequent technological learning mechanisms used by Iranian renewable energy firms. These are the issues that need to be addressed by renewable energy firms and policymakers in developing countries. [ABSTRACT FROM AUTHOR]

Finding an alternative energy resource which can produce clean energy at a low cost is one of the major concerns of our times. The conversion of light energy into chemical energy is one key step forward in the direction. With that end in view photochemical water oxidation to produce oxygen plays a crucial role. In the present paper we have synthesized a soft oxometalate {PMoO@MoFe} n(1) from its well-known precursor polyoxometalate constituent [Muller et al., Chem. Commun. 1, 657 (2001)]. It is known that in the matter of catalysis, high surface area, possibility of heterogenization, recoverability makes soft oxometalates (SOMs) attractive as catalytic materials. Here we exploit such advantages of SOMs. The SOM based material acts as an active catalyst for photochemical water oxidation reaction with a maximum turnover number of 20256 and turnover frequency of 24.11min. The catalyst material is stable under photochemical reaction conditions and therefore can be reused for multiple photo catalytic water oxidation reaction cycles. [ABSTRACT FROM AUTHOR]

This paper proposes a photovoltaic (PV)-based three-phase four-wire (3P4W) series hybrid active power filter (SHAPF) it comprises of a series active power filter (SAPF) and an LC shunt passive filter. The proposed system eliminates both the current and voltage harmonics and compensates reactive power, neutral current and voltage interruption. A SAPF demands a source of energy for compensating the voltage sag/swell. This system introduces a new topology for SHAPF utilizes the PV with DC-DC boost converter as a source of DC power for SAPF. The compensation current reference evaluation is based on the twin formulation of the vectorial theory of electrical power theorem with fuzzy logic controller (FLC). The PV array/battery managed DC-DC boost converter is employed to step up the voltage to meet the DC bus voltage requirement of the three-leg voltage source inverter (VSI). The foremost benefit of the proposed system is that, it will provide uninterrupted compensation for the whole day. This system utilizes the renewable energy accordingly saves the energy and shares the load during the solar irradiation available. The simulation and experimental studies are carried out to validate the effectiveness of the proposed PV-SHAPF. [ABSTRACT FROM AUTHOR]

The usage of various inverters in various industries has gained considerable attention in the power electronics industry in recent years. The harmonic distortion that is induced by various renewable energy sources, along with the growing use of nonlinear loads and power electronic devices, has a significant impact on the distribution system. This is because of the rise in penetration of various renewable energy sources and the usage of nonlinear loads and power electronic devices. In addition, distributed generation (DG) units with inverters (such as solar (PV) and wind turbines) that are integrated into distribution networks are viewed as significant harmonic producers that have substantial adverse effects on power quality. The power quality in the system suffers because of these generators. This study proposes a method of harmonic mitigation for addressing power quality problems that are present in distribution systems as a solution to the challenges that have been found. These concerns have been brought to light as a result of previous research. The standard two-level and three-level inverters were the basis for the development of the multilevel inverter (MLI), which was meant to address their shortcomings. One of the effective technologies that can maintain constant performance is the hybrid power generating system. A hybrid energy system has several benefits, including high dependability, cheap cost and minimal emissions. When used in a hybrid power production system, the reduction of total harmonic distortion (THD) becomes absolutely necessary (HPGS). In this context, the research provides a novel approach for high-performance quantum computing called quantum coyote optimization algorithm-based THD reduction (QCOA-THDR). The QCOA-THDR approach that has been presented has been tested with several converters, including SEPIC, buck–boost and Cuk converters. Additionally, the proportional as well as the integral gain variables of the proportional integral (PI) controller are set in order to achieve decreased total harmonic distortion (THD). In addition, the QCOA system is formed by combining the ideas of quantum computing (QC) with the traditional COA. This is how the QCOA system comes to exist. A limited number of simulations were run, and the results are being analyzed from a variety of perspectives in order to investigate the improved effects that the QCOA-THDR approach has on data. The QCOA-THDR method was shown to have superior results than the more modern techniques, as shown by the comparison research. [ABSTRACT FROM AUTHOR]

To investigate the impact of natural disasters on energy poverty, this study employs a panel dataset of 113 countries covering the period 2000–2014. We also conduct an asymmetric analysis on the natural disaster–energy poverty nexus. In addition, we analyze the impact mechanism between natural disasters and energy poverty. The main findings indicate that natural disasters deteriorate the energy poverty status, and this impact is asymmetric. Furthermore, technological innovation can reduce the positive impact of natural disasters on energy poverty. Also, renewable energy infrastructure is an important pathway through which natural disasters affect energy poverty. [ABSTRACT FROM AUTHOR]

China’s coal resource tax reform, introducing an ad valorem tax to replace previous volume-based tax from December 2014, marked a new stage of the resource pricing mechanism reform. In particular, coal, as a pollution-intensive energy, is the main source of energy for China. With this in mind, it is the time to ask what the impacts of this reform would be on Chinese economy. A computable general equilibrium (CGE) model is applied to explore the impact of a 5% ad valorem coal resource tax on Chinese economy under four scenarios involving distinguished electricity pricing mechanisms and tax revenue recycling scheme by deducting consumption tax. Simulation results show that levying ad valorem tax will reduce the output of energy-intensive industries with minor negative impact on economy. A consumption tax deduction can offset the negative impact on real GDP and help the economy to restructure. The concern that reform will push up inflation is unnecessary, even under the market price mechanism of electricity. In terms of winners, export-oriented industries benefit when no tax revenue recycling, while industries producing private consumption goods benefit when ad valorem coal resource tax revenue is used to deduct consumption tax. [ABSTRACT FROM AUTHOR]

The current work describes a novel technique for wind turbine rotor optimization. The aerodynamic design and optimization of wind turbine rotor can be achieved with different methods, such as the semi-empirical engineering methods and more accurate computational fluid dynamic (CFD) method. The CFD method often provides more detailed aerodynamics features during the design process. However, high computational cost limits the application, especially for rotor optimization purpose. In this paper, a CFD-based actuator disc (AD) model is used to represent turbulent flow over a wind turbine rotor. The rotor is modeled as a permeable disc of equivalent area where the forces from the blades are distributed on the circular disc. The AD model is coupled with a Reynolds Averaged Navier-Stokes (RANS) solver such that the thrust and power are simulated. The design variables are the shape parameters comprising the chord, the twist and the relative thickness of the wind turbine rotor blade. The comparative aerodynamic performance is analyzed between the original and optimized reference wind turbine rotor. The results showed that the optimization framework can be effectively and accurately utilized in enhancing the aerodynamic performance of the wind turbine rotor. [ABSTRACT FROM AUTHOR]

Despite being the regions with the least levels of carbon emissions in the world, African countries are facing unique challenges on climate change, increased carbon emission levels and the need for environmental governance improvement. This study, therefore, examined the implications of economic growth and governance on CO2 emissions in West Africa. Specifically, the study investigated the role of governance in moderating the effect of economic growth on CO2 emissions in West Africa. The study utilized data for 16 West African countries from 2000 to 2020 in an unbalanced panel data framework. Empirical analyses were conducted using the Instrumental Variable Fixed Effects estimator with Driscoll and Kraay Standard Errors, as well as the Instrumental Variable Quantile Regression in order to account for serial correlation, endogeneity and conditional heteroskedasticity. The following conclusions were drawn from the results. First, economic growth significantly increases CO2 emissions in the region with the Environmental Kuznet Curve hypothesis present. Second, the quantile regression estimates reveal that the effect of economic growth on CO2 emissions is higher in countries where the initial level of carbon emissions is considerably high. Third, the results further show that in the presence of improved governance quality, economic growth does not significantly influence CO2 emissions in the region. Fourth, political stability and regulatory quality were the only indicators of governance that significantly impacted environmental pollution in the region. Finally, we found that other factors such as trade, urbanization, and renewable energy also significantly influenced CO2 emissions in the region. The study concludes by highlighting the importance of governance in moderating the effect of economic growth on CO2 emissions, as well as the importance of heterogeneous analysis for understanding the dynamism in economic relationships. [ABSTRACT FROM AUTHOR]