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The increasing environmental consideration and the growth of instability of the energy market call for methods that can process the organic fraction of municipal solid waste (OFMSW) into fuel instead of disposal. Due to the pyrolysis and gasification that are efficient procedures to achieve valuable products, gasification of OFMSW with different particle sizes and compositions was carried out in the presence of Ni and Ni-Ce-loaded Y-zeolite in a multizone tubular kiln reactor. During the experiments, 500°C was applied in the first reactor zone, while the 2nd zone was at an elevated temperature of 600°C or 900°C in the presence of steam. The combined pyrolysis and gasification experiments were also carried out without a catalyst with the same operating conditions. The feedstock was collected from the organic fraction of a Hungarian mechanical-biological treatment (MBT) plant and was separated into four different fractions based on particle size: <1 cm dry biomass and fine particles, 1-2 cm paper-rich, 2-6 cm paper and plastic-rich feedstocks, and <6 cm mixture of these fractions. During the experimental work, product yields; gaseous product composition; the ratio of H2/CO, CO2/CO, and CH4/CO; and lower heating value were determined in the function of feedstock composition, the applied temperature, and catalysts. It was found that the hydrogen content and H2/CO ratio of gaseous products were increased due to catalyst application and temperature elevation in the 2nd reactor zone. The addition of Ce to the Ni/Y-zeolite catalyst was advantageous in the case of hydrogen formation at a lower temperature (600°C). The hydrogen and methane content of products obtained from the catalytic pyrolysis-gasification of paper and plastic-rich OFMSWs on elevated temperatures were higher, which increased the lower heating value of those products. Based on the elemental analysis of the obtained solid residues, it was found that paper/plastic-rich feedstock released hydrogen and carbon with a higher extent. 1-2 cm feedstock-related solid residues had the highest H/C ratio which caused a 12.5-12.8 MJ/kg gross heating value. As a result, combined pyrolysis and gasification appear to be an efficient method to attain valuable outputs from OFMSW not only in gas but also in solid products. [ABSTRACT FROM AUTHOR]

Changes are emerging that will significantly alter structure and operation of this century's distribution networks, and photovoltaic (PV) systems will play greater role in energy sector, with implications for power system reliability. Considering uncertainties in solar irradiance and electrical loads and incorporating them into the optimization problem within an appropriate methodology is becoming increasingly important in reshaping distribution networks. In this paper, uncertainty scenarios are handled with Monte Carlo Simulation (MCS) under genetic algorithm (GA) and differential evolution- (DE-) based optimization, and probability distribution functions (pdf) of bus voltages and line current are obtained to be used in chance-constrained stochastic programming. This present study focuses on investigating impact of uncertainties in PV system operating under different irradiance scenarios on power loss with probabilistic constraints in distribution networks instead of precise deterministic limits to contribute more efficient and reliable use of energy. By combining meta-heuristic optimization and MCS technique under one framework, this paper contributes to knowledge base of how to allocate PV plants within distribution networks under chance-constrained strategy. In order to show the effectiveness of the proposed methodology, obtained optimization results are tested using MCS under set of uncertainty conditions and network constraints are evaluated for limit violation probabilities. The effectiveness of this method is investigated based on comparative results of two different optimization methods through probabilistic analysis and simulation. [ABSTRACT FROM AUTHOR]

The rapid deployment of electric vehicles (EVs) in Jordan requires massive efforts to prepare the infrastructures that serve the transportation sector. The lack of EV charging stations is the major obstacle that faces EV drivers. Utilizing renewable energy in EV charging stations contributes to the spread of these stations. Renewable energy technologies are environmentally friendly as they mitigate greenhouse gases that cause the global warming phenomenon. In this paper, an EV charging station, based on a PV-biodiesel-battery hybrid system, is investigated. The importance of this article is to discuss the hybrid system of PV and waste vegetable oil (WVO) along with storage that applies the maximum reliability supply, having an environmentally friendly supply and achieving the lowest energy cost of charging. This station is designed based on renewable and WVO utilization. In fact, WVO, coming from restaurants, is exploited to produce electricity by a diesel generator through direct burning after converting it into biodiesel. The capacity of each station is 14 cars/day with a medium-speed charger of 7 kW. The system is simulated and optimized using iHOGA software where multiobjective optimization is applied to achieve the minimum net present cost (NPC) and CO2 emissions considering three cases, PV-diesel, PV-biodiesel, and PV-WVO, all with battery-hybrid system. These values for the EV charging station that uses the PV-biodiesel-battery hybrid system are 624408 € and 15.4 tons/year, respectively. The corresponding values are 781473 € and 15.14 tons/year and 615310 € and 18.84 tons/year for the systems that work with diesel and WVO, respectively, and energy cost is achieved in best solution to be 0.11 Euro/kWh. Simulation results show that the proposed technique led to enhanced operational efficiency in terms of both NPC and annual CO2 emissions. [ABSTRACT FROM AUTHOR]

Summary: With increasing global warming, the new energy industry has become the mainstay for achieving a sustainable development of human society. The effective diffusion of leading technologies is the source of social benefits obtained from enterprise core technologies, and it is also a necessary factor for the transformation and optimization of industry. In the international context of energy conservation and emission reduction, systematically and comprehensively studying the diffusion mechanism of leading technologies in new energy industry has important theoretical and practical significance for promoting the diffusion of leading technologies in the new energy industry. Based on the introduction of the cellular automaton model and its extension model, this paper constructs the diffusion model of new energy industry's leading technology and analyzes the diffusion mechanism. This mechanism shows that in the case of the market and policy environments in nowadays, the diffusion of new energy industry's leading technology is mainly influenced by promotion intensity, market share of positive and negative idea leaders, as well as the enterprise scale of strong chain and weak chain. This influence is verified by simulation analysis. Based on the diffusion mechanism, suggestions are presented for promoting the diffusion mechanism of new energy industry leading technology. These suggestions aim to provide a reference for the government, industry associations, and enterprises in making relevant decisions. The novelty of the work is: At the industrial level, this paper explores both the development law and diffusion mechanism of the leading technology in the new energy industry, which is conducive to improving and enriching the theoretical system of technological innovation.This paper uses simulation analysis to verify the diffusion mechanism of leading technologies in the new energy industry. This approach effectively improves the diffusion level of leading technology in the new energy industry and provides a reference for energy upgrading. [ABSTRACT FROM AUTHOR]

Human resource management mode refers to a comprehensive summary of management objectives, processes, content, methods, and other elements. The more common two modes are control mode and commitment mode. The enterprise human resource management model has many different types. The generation pair promotes the development of enterprise human resource management from the traditional model to the platform model, processing complex data with the help of data-based technical means, and realizing the integration and sharing of resource data. This paper takes an energy company as an example to carry out a detailed study. The article takes the big data as the background and the company as the research object. From the perspective of human resource management, this paper tries to find out the performance management, compensation and benefits management, and other issues of the company in human resource management under the background of the big data era and puts forward corresponding solutions for the current problems. In particular, the company gave certain opinions on how to build a human resource management system in the context of the current big data era. By conducting field research on the company and issuing questionnaires, this paper finds out the current problems of the company in human resource management and proposes corresponding solutions for these problems. [ABSTRACT FROM AUTHOR]

The development of the vehicle-road cooperative intelligence can effectively resolve the current technical impediment and cost quandary associated with high-level autonomous driving. Nevertheless, the intelligent infrastructure entails initial deployment costs and ongoing energy consumption and maintenance costs, necessitating a comprehensive and quantitative analysis of the costs of intelligent infrastructure and the corresponding changes in comprehensive costs. The cost evaluation model for the cooperative intelligent system is designed in this paper, considering the corresponding intelligent infrastructure layout scheme for different road types within the technical framework. The intelligent configuration and corresponding cost transfer from roadside to vehicle side under the synergy effect is also analyzed. Using Beijing as a case study, the results indicate that the deployment of intelligent infrastructure will effectively reduce acquisition and usage costs of high-level intelligent vehicles and achieve a greater "reuse" effect by serving more intelligent connected vehicles (ICVs). Compared to the vehicle intelligence, collaborative intelligence will reduce cumulative total costs by more than ¥200 billion from 2023 to 2050, even with the inclusion of intelligent infrastructure's costs. [ABSTRACT FROM AUTHOR]

In this paper, a multiobjective framework for simultaneous reconfiguration and allocation of photovoltaic (PV) energy resources in radial distribution networks is performed for minimizing the power losses, lowering network loading factor, and reducing cost of energy resources as well as increasing the voltage stability index. A novel algorithm called the improved clouded leopard algorithm is used to find the set of optimum decision factors in the combined execution of restructuring and also PV resource distribution. The clouded leopard optimization (CLO) algorithm, which is widely used, takes its cues from the sleeping and foraging habits of the animal, and the improved CLO (ICLO) is formed using adaptive inertia weight to overcome premature convergence. In five cases of base distribution network and different contribution of reconfiguration and PV allocation, single- and multiobjective approach has been applied on 33- and 69-bus distribution networks. According to the findings, the best case includes simultaneous reconfiguration and PV allocation in the radial networks based on the multiobjective approach unlike the single-objective method which obtained the highest network performance with the best compromise between different goals. Also, in the best lowest losses, the decrease in the network loading and cost of energy resources and the better voltage profile and stability are obtained satisfying the constraints. The losses, network loading, voltage profile, and voltage stability are improved by 60.40%, 37.89%, 6.17%, and 27.5% for 33-bus network and also enhanced by 71.77%, 41.23%, 4.76%, and 20.48% for 69-bus network, respectively. Also, the results showed that network reconfiguration only has the weakest performance among other cases based on reconfiguration or photovoltaic sources. Moreover, the superior capability of the ICLO in addressing the aim of the study is proved in comparison with the traditional CLO and well-known particle swarm optimization (PSO) and manta ray foraging optimization (MRFO) to obtain the better objective value and statistical criteria to solve the best case. [ABSTRACT FROM AUTHOR]

Reliable operation of energy management systems, grid stability, and managing energy demand responses are becoming challenging because of the flickering nature of solar irradiance. Accurate forecasting of global solar irradiance, i.e., global horizontal irradiance (GHI), plays a significant role in energy policy-making and the energy market. This paper proposes a novel global solar irradiance forecasting model based on the ensemble recursive radial basis function neural networks (ERRBFNNs). The various atmospheric inputs based on the built ensemble recursive radial basis function neural networks make the network more stable and robust to climatic uncertainty. This paper statistically investigates the performance of novel feed-forward neural networks based on forecasting models with various hidden nodes for global solar irradiance forecasting applications. We validated the proposed ERRBFNN global solar irradiance forecasting model using real-time data sets. The simulation results confirm that the proposed ensemble recursive radial basis function neural network based on global solar irradiance forecasting improves the accuracy, generalization, and network stability. Furthermore, the proposed ERRBFNN lowers the forecasting error to the least compared to other state-of-the-art forecasting models. [ABSTRACT FROM AUTHOR]

Under the background of the new power system, the proportion of new energy power generation enterprises in the power market is gradually increasing. With the further expansion of China's power trading scale, the increasingly fierce market competition, and the instability of new energy output, the credit problems of new energy power generation enterprises in the trading process cannot be ignored. Therefore, improving and perfecting the credit system of new energy power generation enterprises is necessary for building a modern market system. Firstly, the credit indexes of new energy power generation enterprises are constructed from the three dimensions of performance ability, performance behavior, and performance willingness. Then, a credit index evaluation model of new energy power generation enterprises is proposed based on the fuzzy best-worst and improved matter-element extension method. Finally, an empirical study is carried out. The analysis results show that scheduling discipline compliance, historical credit, and participation rate of the market-oriented transaction have a more significant impact on the recognition of new energy power generation enterprises. They should focus on market transactions. The model proposed in this paper can effectively deal with the ambiguity of indexes in the credit evaluation of new energy power companies. Through comparison with other models, the effectiveness of the model proposed in this paper in the credit evaluation of power companies is further verified. Construction provides method support. [ABSTRACT FROM AUTHOR]

Energy decision-makers have considered solutions to meet the demand for affordable and highly reliable energy due to population growth and technological advancement. One of these possibilities is the utilization of several energy carriers in one system as an energy hub. Instead of optimizing a single energy carrier, the energy hub optimizes a system with many energy carriers, including electricity, natural gas, and local heat, by use of its converters and storages. In this paper, a novel and new general framework is proposed to evaluate and compare both series and parallel connections of n hub to analyze cost and reliability aspects by considering coupling matrices. In order to compare the outcomes of the connections of several comparable hubs in both series and parallel modes, new indices are proposed and evaluated from the aspect of evaluating the amount of energy not supplied and the amount of energy input to each hub. Additionally, simulations are run for a variety of scenarios in order to better assess the proposed model and investigate each type of connection by evaluating the proposed performance indices. The results show that in all the examined scenarios, the total cost of the energy carriers in the series mode (link in the output) is lower than in the parallel mode (link in the input). [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) paradigm denotes billions of physical entities connected to Internet that allow the collecting and sharing of big amounts of data. Everything may become a component of the IoT thanks to advancements in hardware, software, and wireless network availability. Devices get an advanced level of digital intelligence that enables them to transmit real-time data without applying for human support. However, IoT also comes with its own set of unique challenges. Heavy network traffic is generated in the IoT environment for transmitting data. Reducing network traffic by determining the shortest route from the source to the aim decreases overall system response time and energy consumption costs. This translates into the need to define efficient routing algorithms. Many IoT devices are powered by batteries with limited lifetime, so in order to ensure remote, continuous, distributed, and decentralized control and self-organization of these devices, power-aware techniques are highly desirable. Another requirement is to manage huge amounts of dynamically changing data. This paper reviews a set of swarm intelligence (SI) algorithms applied to the main challenges introduced by the IoT. SI algorithms try to determine the best path for insects by modeling the hunting behavior of the agent community. These algorithms are suitable for IoT needs because of their flexibility, resilience, dissemination degree, and extension. [ABSTRACT FROM AUTHOR]

The paper expresses the problem of flexibility pricing in energy hubs (EHs) that are in connection with electricity, heat, and gas networks considering of uncertain energy generation sources. Scheme includes a bilevel formulation. Its upper-level states for modeling of the flexibility services are provided by various resources within the EH. The problem considers maximization of the expected profit of these resources in the flexibility market. The problem constraints include the flexibility model of flexible resources such as storage devices, responsive loads, and controllable distributed generations (DGs). The flexibility model of resources relies on their active and heat power. The lower-level problem calculates energy and flexibility prices and formulates the flexible operation of energy resources considering EHs. Here, constraints include optimal power flow equations in the energy networks; operation model of EHs with power sources, storage devices, and different responsive loads; and flexibility limits of EHs. Also, a linear approximation model is adopted in the suggested design using conventional linearization techniques. Next, the Karush–Kuhn–Tucker (KKT) method is used to derive a single-level model for the problem. The scheme adopts scenario-based stochastic programming (SBSP) so that uncertainties of renewable power, energy price, load, and energy consumption of mobile storage devices are properly modeled. Finally, the results validate the suggested design's potential in modifying and enhancing the operation, flexibility, and economic situation of energy networks and EHs. [ABSTRACT FROM AUTHOR]

This paper uses the 5-five-minute high-frequency data of energy-listed companies in China's A-share market to extract the jump of energy stock prices and build a dynamic stock price jump complex network. Then, we analyze the clustering effect of the complex network. The research shows that the energy stock price jump is an important part of stock price volatility, and the complex network of energy stock jump risk has obvious time-varying characteristics. However, the infection problem of stock price jump risks needs specific analysis. China's coal industry has an important influence on the development of China's energy industry. According to the clustering analysis results of the network community, the clustering effect of the network community has time-varying characteristics. After October 2017, the clustering effect of the jumping risk of the coal industry and the new energy industry is obvious. The risk contagion within the new energy industry community is a key point for the development of the new energy industry. [ABSTRACT FROM AUTHOR]

Summary: This paper conducts strategic analysis and development plan design of energy digital transformation from a global perspective. First, this paper analyzes the reasons for the digital transformation of the energy industry, and elaborates on the current status of the digital transformation of the energy industry. Second, this paper uses the "SWOT" model to conduct a strategic analysis of the digital transformation of energy. Finally, this paper uses the "IETB" model to design the development plan. The results showed that: (1) Energy digital transformation is an effective approach to optimize the energy allocation and improve the energy scheduling. (2) The biggest barriers and uncertainties are mainly from the current weaknesses and the future threats. (3) The joint action of factors from Institution, Economy, Technology as well as Behavior achieves an effective scheme to promote the digital transformation of energy. HIGHLIGHTS: Reasons for the digital transformation of energy.The development status of the digital transformation is outlined.Using the "SWOT" model to conduct a strategic analysis of the digital transformation of energy.Using the "IETB" model to design the development plan. [ABSTRACT FROM AUTHOR]

As an energy source, solar cells can be central to peak load control in different power companies. Hydrogen production can be cost-effective if the generated electricity is unusable. Shades reduce solar cell current and fundamentally alter panel function, making it necessary to restore panels to optimum power generation. Owing to the issues outlined in this paper, the energy-economic-environmental effect of a shade detection algorithm was examined for different shade scenarios, and domestic-scale solar hydrogen production was evaluated. As the effect of the partial shade detection algorithm on the amount of solar hydrogen production has not been investigated quantitatively so far, this issue was discussed in this study. The algorithm and laboratory equipment developed by the authors were used to detect the partial shadow. Thanks to the respected reviewer, the following sentence was added to the abstract. The analyses in HOMER V2.81 software used 20-year average data for a residential building in the city of Tehran obtained from the NASA website. The results recommended that the designed algorithm increases hydrogen production in different scenarios between 5.8% and 32.9%. The results also revealed that the designed algorithm significantly lessen the pollutants between 100 kg/year and 240 kg/year. [ABSTRACT FROM AUTHOR]

Optimal management of sources, storage, and responsive loads in the energy network leads to improvement of economic and technical situation of the network. However, note that single-layer energy management requires to provide the network operator with more amounts of information. This results in the increase in the processing speed for the network operator. Also, coordination of sources, storage, and responsive loads in the form of an aggregator such as an energy hub can play an important role for them in promoting the economic situation and energy efficiency. So, this paper presents the participation of grid-connected energy hubs (EHs) in the day-ahead (DA) and real-time (RT) energy markets. Scheme has a two-stage optimization framework. In the first stage, participation of EHs in the hourly DA energy market is executed based on a two-layer energy management system that is modeled as bilevel problem. EH model in DA market is formulated in upper-level problem aimed at maximizing their profit subject to meeting the linearized constraints of the EH's operation. Lower-level problem deals with the operation of energy networks to minimize cost of energy purchase from the upstream network constrained to linearized optimal power flow equations. The second stage of participation of EHs in a 5 min RT market has an objective function to minimize the unbalance between the EHs' profits in the mentioned two markets. This stage is subject to the upper-level constraints and the lower-level formulation in the first stage. Robust optimization models the uncertainties of load, renewable power, energy price, and energy demand of mobile storage to achieve an optimal robust solution. Benders decomposition algorithm solves bilevel formulation in two-stage scheme. Numerical results confirm capabilities of the scheme in enhancing operation status of the networks and economic situation of EHs. Hence, the Benders decomposition algorithm is able to extract the optimal solution in shorter computation time. Two-layer energy management needs shorter computation time than the single-layer management. Simultaneous modeling of two real-time and day-ahead energy markets reduces the unbalance cost between these markets. The proposed scheme can enhance the operating and economic indicators of the network by up to around 18% and 26% compared to power flow studies of energy networks. [ABSTRACT FROM AUTHOR]

Several advantages make wind-driven permanent magnet synchronous generators (PMSGs) very promising in the wind energy market, especially their fault ride-through capabilities. With the high penetration levels of today, both the grid and wind power (WP) systems are being affected by each other. Due to grid faults, the DC-bus in PMSG systems typically experiences overvoltage, which can negatively affect the generator parameters and trip the system. However, advancements in power electronics, control systems, fault limiters, FACTS, and energy storage technology make it possible to find and design satisfactory solutions and approaches. The most recent FRTC-improving techniques are mainly modified or external techniques based on controllers in PMSG-based WP. This paper evaluates the in-depth schemes of FRTC, introducing the underlying theory and traits of the different approaches to highlight the advantages and drawbacks of each. Five scenarios of DC-link voltage under zero-grid voltage are carried out by using the MATLAB SIMULINK program to assess the FRTC methods. This study shows that external device-based approaches can be efficient, but some of them are expensive, thus updated controller methods are recommended to cut costs. Research findings of this study are expected to support the deployment of FRTC technologies, as well as provide valuable input into WP research on grid integration. [ABSTRACT FROM AUTHOR]

Since the existing research on the direct introduction of ecological principles into the financing field is very weak, there is no systematic and dynamic research on financing efficiency from the perspective of ecology. Through in-depth analysis, this paper finds that the industrial financing ecology affects financing efficiency through financing scale, financing cost, financing structure, financing speed, and capital allocation. At the same time, financing efficiency also affects the industrial financing ecology through industrial policy, financial system, legal culture, ecological displacement, and genetic reorganization, this leads to the interaction and coevolution of the industrial financing ecology and financing efficiency. To measure the degree of synergy between the financing ecology and financing efficiency, we construct a composite system synergy model and take the new energy industry as an example to carry out empirical research, the empirical results show that the synergy between China's new energy industry financing ecology and efficiency at the current stage still has great room for improvement. [ABSTRACT FROM AUTHOR]

The European Union is facing the highest natural gas prices in 15 years, owing largely to an upward trend in electricity prices, which is also on an uphill curve. However, the rise in electricity and natural gas prices is a widespread phenomenon that is being felt not only in Europe but also globally, as economic activity resumes and energy consumption returns to prepandemic levels. Consequently, this paper investigates how COVID-19 influenced the Romanian energy market. To accomplish our goal, we used daily data for variables and market indices that characterize COVID-19 and the energy market from July 1 to December 21, 2021. The results of the GARCH (1, 1) model estimation show that the major performer in Romania's energy allocation and supply market had the highest conditional variance. In addition, the ARDL model was chosen because of the variable integration mix (order 0 and 1), as well as the VAR and the Granger causality framework. The empirical results of ARDL models provide the first conclusion of the analysis, indicating that the number of short-term connections was greater than long-term connections, which is also explained by the presence of short episodes of high volatility recorded in the investigated time interval. Another conclusion drawn from this study is that COVID-19 cases registered in Europe and around the world have made a significant contribution to explaining the evolution of the energy market, owing to the large number of cases registered in these regions and the level of contagion transmitted from these markets to the energy market. Furthermore, based on the Granger causality test results, only one-way causal relationships were identified from the variables that capture the evolution of the COVID-9 pandemic to the yields of Romanian energy companies. The novelty of this article is the examination of the impact of COVID-19 on the energy market throughout the fourth wave of coronavirus using the GARCH framework, the ARDL model, which allows for the capture of both short- and long-term reactions, the variance decomposition, and the Granger causality test. Because of the ongoing changes in the pandemic's evolution, additional research on this topic is undoubtedly on the horizon in the near future. [ABSTRACT FROM AUTHOR]

Summary: Multicomponent multiphase fluid flows are commonly seen in the engineering practice of hydrocarbon production and transportation; thus, the phase‐wise heat and mass transfer mechanisms underneath the macroscopic flow and transport behaviors are essentially needed for better understanding of the physical phenomena and optimization of the industrial processes. Flash calculation, as the main approach computing phase equilibrium conditions, has arisen increasing interests to establish the thermodynamic foundations of multiphase flow simulation, as well as to determine whether two‐phase model is needed. In this paper, the general thermodynamically‐consistent flash calculation scheme will be developed, and the general adaptability to various special mechanisms will be analyzed. A unified framework of thermodynamics‐informed neural network will also be designed to accelerate conventional iterative flash calculation schemes that will be applied in various engineering scenarios to provide certain suggestions to the energy industry based on the predictions and analysis. Novelty Statement: A thermodynamically‐consistent flash calculation scheme incorporating various special mechanisms that are often met in energy industry.A unified thermodynamics‐informed neural network structure for various engineering demands in the energy industry.Suggestions to the energy industry to optimize the productions based on the phase transition predictions and analysis. [ABSTRACT FROM AUTHOR]

In this paper, the optimal scheduling of energy grids and networked energy hubs based on their participation in the day-ahead energy wholesale and retail markets is presented. The problem is formulated as a bilevel model. Its upper level minimizes the expected energy cost of electricity, gas, and heating grids, especially in the form of private distribution companies in the mentioned markets, in the first objective function, and it minimizes the expected energy loss of these networks in the second objective function. This problem is constrained by linearized optimal power flow equations. The lower-level formulation minimizes the expected energy cost of hubs (equal to the difference between sell and purchase of energy) as an objective function in the retail market. Constraints of this model are the operation formulation of sources and active loads and the flexibility limit of hubs. The unscented transformation approach models the uncertainties of load, renewable power, energy price, and energy demand of mobile storage. Then, the Karush–Kuhn–Tucker approach and Pareto optimization technique based on ε-constraint are adopted to extract the single-level single-objective formulation. Finally, obtained results verify the capability of the present method in improving the economic status of hubs and the economic and operation situation of the mentioned networks simultaneously so that the proposed scheme by managing the power of energy hubs compared with power flow studies has been able to reduce operating costs by 8%, reduce energy losses by 10%, and improve voltage profile and temperature by 36% and 30%. [ABSTRACT FROM AUTHOR]

In this paper, we define the concept of level graphs on interval-valued fuzzy graphs (IVFGs) and introduce the notions of α , β − α , β − homomorphism, isomorphism, weak isomorphism, and co-weak isomorphism of IVFGs by α , β − homomorphism. Also, an application of homomorphism of IVFGs has been presented by using coloring-FG. [ABSTRACT FROM AUTHOR]

This paper develops a regional new energy industry (NEI) competitiveness evaluation index system based on the theoretical framework of the "diamond model" and the unique characteristics of the new energy industry and made an empirical analysis of Jilin province with analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method. The analysis results show that the new energy industry in Jilin Province has a good foundation, and the government's role, talent support, technological innovation, and market factors are acceptable. However, due to location factors and resource endowments, regional GDP and per capita consumption expenditure are low. The lack of intrinsic motivation of industrial competitive advantage has resulted in the poor overall competitiveness of the new energy industry in Jilin Province. Then, it is advised to take targeted measures to work closely with national NEI development strategy, optimize the industrial technology innovation ability and the talent support, actively guide social capital flows and new energy consumption, optimize regional energy consumption structure and industrial structure by creating a complete NEI chain, and revitalize the whole economy. [ABSTRACT FROM AUTHOR]

In the transition towards sustainable energy sources, hydrogen has emerged as the predominant alternative after fossil fuels. This comprehensive literature review investigates into the evolving landscape of hydrogen launching strategies within the energy market. Numerous countries have strategically initiated efforts to introduce products based on hydrogen, highlighting the global acknowledgment of the potential inherent in hydrogen. Despite witnessing significant growth in the adoption of hydrogen energy worldwide, barriers to its widespread commercialization persist. This review identifies key barriers, including cost structures, technical complexities, and marketing challenges, hindering the establishment of a robust hydrogen energy market. The article critically examines the actions already undertaken to harness hydrogen energy for commercial purposes, looking at scientific insights and statistical data. By carefully examining the current state of hydrogen energy initiatives, the review highlights gaps in existing strategies that require thoughtful consideration. Insights derived from scientific and statistical analyses inform the identification of barriers and contribute to a nuanced understanding of the challenges faced in the journey towards hydrogen energy commercialization. Ultimately, the article presents a strategic proposal outlining marketing actions geared towards expediting the commercialization and widespread adoption of hydrogen energy. Grounded in a thorough review of existing literature and supported by scientific and statistical evidence, this comprehensive analysis offers valuable insights for stakeholders seeking to navigate the intricate landscape of hydrogen energy in the global energy market. [ABSTRACT FROM AUTHOR]

Rotor blades are the main part for generating electrical energy and the primary source of stresses in a wind turbine (WT). The stresses caused by the blades increase the load on the hub, tower, and foundation of the WTs. In this research, the asymmetry of the blade angle with each other has been investigated as one of the factors affecting the stress distribution using Monte Carlo (MC) simulation. The focus of this study is on the stresses caused by the asymmetry of the blades angle when there is the fault in the sensors. A deep understanding of the blade stress distribution due to sensor faults can improve control designs, increase WT operating time, and reduce energy generation costs when these faults occur. [ABSTRACT FROM AUTHOR]

In recent years, solar and wind energy have been increasingly abandoned due to the blind expansion of the new energy industry. Due to the competitive relationships between different types of new energy, reasonable industrial development planning needs to be implemented to not only save the cost of government subsidies but also clarify the investment direction of social capital. Based on the panel data of OECD countries between 2006 and 2018, the stochastic frontier analysis (SFA) was used to measure the efficiency of new energy generation (NEG) and the influencing factors were analyzed in this paper. Results were as follows: the efficiency of NEG in OECD countries is improving; the efficiency of NEG is positively correlated with technical innovation, government policies, economic level, and education level and negatively correlated with urbanization. Based on the empirical results of this study, problems in the development of the new energy industry have been discussed and suggestions to improve the efficiency of NEG have been proposed. [ABSTRACT FROM AUTHOR]

Changjiang Economic Zone (CEZ) faces the urgent task to promote the energy conservation and emission reduction of the transportation industry. This study constructs an evaluation system for transportation industry energy efficiency (TIEE) and evaluates TIEEs of 11 CEZ provinces in 2000–2017, using the super-slack-based measure (Super-SBM) model containing undesired output. On this basis, the panel data model was adopted to explore the impactors of TIEE. The main results are as follows: CEZ provinces varied significantly in TIEE. In the sample period, Jiangsu, Jiangxi, Zhejiang, Sichuan, Shanghai, and Anhui achieved relatively satisfactory TIEEs; Hunan, Hubei, and Guizhou performed generally on TIEE, calling for some improvement; Chongqing and Yunnan did not perform well, leaving a huge room for improvement. Judging by TIEE trends in the lower reaches, middle reaches, and upper reaches, TIEE of the lower reaches exhibited a U-shaped trend (first decrease and then increase) and TIEEs of the middle reaches and upper reaches did not fluctuate significantly, except for a few years. There was a marked difference between the three regions in TIEE: TIEE in the lower reaches was much higher than that in the middle reaches and upper reaches. In addition, the panel data model demonstrates that TIEE is significantly promoted by economic growth and transportation structure, obviously suppressed by industrial structure, opening-up, and transportation infrastructure, and not clearly affected by government influence or environmental regulation. [ABSTRACT FROM AUTHOR]

The present work analyzes the feasibility of using solar water heating systems (SWHS) to supply the hot water required in the winemaking industries. The hot water demand of the sector was characterized by selecting patterns that encompass the wide range of existing casuistry. After determining the production potential of the SWHS by using an experimental system, 22500 energy simulations were carried out, combining different locations, energy prices, and prices of the necessary investment. The results demonstrate that the seasonality and irregularity of a winery's demand pattern drastically condition the viability and profitability of SWHS. In wineries with high demand, which are relatively uniform throughout the year, the solar system with optimized design achieves energy consumption reductions between 32% (low radiation) and 52% (high radiation), with payback between 4.3 and 7.2 years. On the other hand, in wineries with highly seasonal consumption, SWHS are not profitable even in very favorable cases. [ABSTRACT FROM AUTHOR]

The energy sector accounts for about two-thirds of all human-related greenhouse gas (GHG) emissions due to the reliance on fossil-based fuels. This is a significant concern as it can have dire consequences on the survival of humankind and disrupt other natural processes. The research indicated that some mitigation measures to curb GHG emissions are to increase energy from low-carbon sources such as nuclear. However, due to the continuous adverse climate change impact, a comprehensive systematic review of research in this area must be conducted to inform policy practice and future studies. This study attempts to address this gap by mapping the global reflections on the potential of nuclear technology to mitigate GHG through a bibliometric review process. A total of 741 studies were retrieved from the Scopus database and a few from Google Scholar, spanning from 1962 to 2022, and analyzed using a science mapping tool—VOSviewer. The study confirmed that fossil fuels are a significant source of greenhouse gas emissions and contributor to greenhouse emissions. Those authors concluded that promoting clean and alternative energy sources to fossil fuels would help reduce carbon emissions. Although renewable energy has proven to be very efficient among pollution and climate change mitigation sources, nuclear energy is the most dependable option for meeting national and regional CO2 emission targets while meeting energy supply needs. The bibliometric analysis with VOSviewer suggested that only five African countries, including Ghana, have contributed to the research area with limited collaboration. As a result, it calls for stakeholders to make informed decisions to invest resources in research to address the challenge on the continent. The MESSAGE planning model is recommended for the study. [ABSTRACT FROM AUTHOR]

In light of the current integrated energy system (IES) transactions, the interaction between the supply and demand sides is not fully considered. With the overall development of the carbon trading market, there is a need to deeply explore the interests of multiple entities in energy trading under the step-by-step carbon trading mechanism. Therefore, research on the optimization and scheduling of multicomprehensive energy systems based on step-by-step carbon trading and hybrid games is proposed. Firstly, the interests and demands of various integrated energy systems and users in multi-integrated energy system energy trading should be comprehensively considered. Based on the master-slave game and Nash bargaining theory, an optimization model of multiple integrated energy systems is built under the step-by-step carbon trading mechanism and load aggregation, representing the interests of the entire user side. Secondly, the proposed game optimization model has been established to prove it can maximize social benefits. IES and user game optimization models have been established, with multi-IES being leaders with the goal of maximizing their own benefits, guiding the optimization between IES and load by formulating energy prices. Users are followers who aim to maximize comprehensive benefits and respond to IES's decisions through cooperation. Finally, using the improved gray wolf algorithm to solve the built model, it has been proven through comparison of calculation examples that the proposed method can reduce carbon emissions, effectively coordinate the optimization scheduling of multi-IES, and achieve the fair distribution of multi-IES cooperation benefits. This improves the effectiveness of individual and social benefits. [ABSTRACT FROM AUTHOR]

As an important foundation of and driving force for rural revitalisation, green and low-carbon energy development is an intrinsic requirement for meeting the people's needs. Rural energy utilization efficiency is low, and there is an urgent need to develop and use renewable green energy. Therefore, the purpose of this study is to explore and clarify the entanglement mechanism between new energy enterprises (NEEs) and village collectives (VCs) considering the mutually beneficial evolutionary stability strategy of the main participants in the rural new energy industry (RNEI) regarding the quantum entanglement state. The quantum evolutionary game model for NEEs and VCs was constructed, and a set of quantum strategies of both parties was introduced. This not only expands the strategy set of the classical game model but also considers the characteristics of quantum entanglement in the implementation of the quantum game. This study also analysed the evolution path and stability strategy of participants in the process of RNEI's development. The results of this study are presented as follows: (i) after considering the entanglement of states, it is easier to adopt the complete quantum strategy to realize the complete incentive situation that "income increases with the increase of one's own efforts," which is conducive to the development of the RNEI. (ii) Observable and quantifiable performance indicators are of greatest importance. Both parties involved in the development of the RNEI should make relevant information open and transparent to promote the smooth implementation of the RNEI development process. (iii) The signing of the "entanglement contract" requires a scientific, complete, specific, and quantifiable performance evaluation system to be established by a professional and independent third-party organization. The study not only makes a certain theoretical contribution to clarifying the mechanism of entanglement between NEEs and village collectives but also provides a theoretical basis for scientific and effective cooperation between NEEs and village collectives. [ABSTRACT FROM AUTHOR]

In electricity markets, the optimal management of buying and selling energy is achieved based on the correct interaction of players. This study proposes a multiobjective bilevel model for optimal decision making of retailer based on interactions with selected customers and wholesalers with appropriate environmental performance in electricity market contracts. In this regard, at the upper level, the retailer's first objective which is profit maximization is realized, while at the lower level, the objective of minimizing customer costs is achieved. Also, the second goal of the retailer is to buy more energy from wholesalers with better environmental performance. For the presented model, in order to properly model the uncertainty of the generation capacity of wholesalers, the robust optimization approach (ROA) has been used. Finally, the mixed integer linear programming (MILP) based on McCormick's linearization method and Karush–Kuhn–Tucker conditions will be solved by CPLEX solver in GAMS software. The final results show the optimal decision of the retailer in choosing customers with the aim of maximizing profit so that the selected customers also pay the minimum cost for the purchased energy. [ABSTRACT FROM AUTHOR]

The recent advancements in demand-side management techniques add significant benefits to the distribution systems. One such technique is transactive energy management systems (TEMS) which motivate the energy end-users to take part in local energy trading. The end-users can effectively increase the monetary benefits by trading the surplus generation/demand within the local energy market (LEM). The LEM operator frames a viable market clearing strategy to fix the market clearing price to enhance the monetary benefits of all the market players. In this study, LEM architecture with different market clearing strategies is proposed for TEMS to ensure profitable power transactions between the neighboring end-users. An optimal energy management algorithm is also proposed for time scheduling the operation of flexible loads and batteries, considering dynamics in end-users' behavior, variations in utility parameters, and the intermittent nature of renewable power generation. Further, an optimal load scheduling algorithm is developed at the end-users' premises to improve the profits in the LEM. Correspondingly, the trading strategies are extended to increase market reliability by penalizing participants for their abnormal activities in energy trading. The proposed framework is validated with different case studies considering ten residential participants in a locality. [ABSTRACT FROM AUTHOR]

Typically, diesel or other fossil fuel-based related applications meet electricity demand. Nonetheless, as the cost of fossil fuels rises, as do their harmful emissions, there is a sudden transition toward stand-alone hybrid renewable energy systems (HRESs). The proposed project proposes electrifying VIT University in Vellore, Tamil Nadu, India, using an off-grid HRES. The goal of enhancing hybrid energy system (HES) regulation, size, and component selection is to provide society with a cost-effective power supply. This article's primary purpose is to show how to utilize HOMER Pro Software to reduce total net present cost, cost of energy, and CO2 emissions. After that, the findings were compared to four different HRES configurations. The efficient solution for transmitting power at the lowest energy cost is configuration 1 (solar + fuel cell + battery + wind + diesel generator) which is found to be the optimal solution for supplying energy with 0% unmet load at the least cost of energy, which is at 24.91 Rs/kWh. These data are used to calculate the optimal size of energy storage components based on long-term system behavior using HOMER and to forecast short-term generation and demand changes while maintaining system dependability and grid voltage. Using and incorporating model predictive control (MPC) for an interlinking converter (ILC), the proposed HRES design is validated for the study area in a novel way that sequentially applies HOMER and MATLAB simulations. [ABSTRACT FROM AUTHOR]

The spillover effect of the energy markets and the CET plays an important role in guiding the realization of two-carbon target; using the network spillover methodology of Diebold, Yilmaz, Jozef Barunı´k, and Toma´sKrehlı´k, we examine both the static and dynamic connectedness of CO2 emissions trading (CET) market, steam coal market, new energy, and traditional energy market in China from early Dec 2013 to the end of July 2021. At last, we verified the stability of the model and obtained the following findings: (1) the total spillover effect index is 13.91% between those markets, and it is mainly focused on short term. Moreover, the dynamic spillover effect is time-varying, and it is greatly influenced by the domestic and international environment; (2) the connectedness of the CET market with other energy markets is neutral, the development of new energy market is strong, it is the main transmitter to other markets, especially to the traditional energy market except for the steam coal market, and the coal market is an effect transmitter. These results provide a theoretical reference for investors and policy makers who are concerned with the return connectedness among the CET market, new energy market, and steam coal market in China. [ABSTRACT FROM AUTHOR]

To solve the problems of large fluctuation of photovoltaic output power affecting the safe operation of the power grid, a hybrid energy storage capacity configuration strategy based on the improved Harris hawks optimization algorithm optimizing variational mode decomposition (IHHO-VMD) is proposed. In this strategy, the improved Harris hawk optimization algorithm is used to adaptively select k and α in VMD parameters and decompose the photovoltaic output power and distinguish between correlated and uncorrelated modes. Similarly, the moving average method (MA) is used to extract the continuous component signal in the uncorrelated mode, and it is reconstructed with the related mode as the grid-connected power that meets the national standard. The hybrid energy storage system (HESS) is used to stabilize the fluctuation component signal. The minimum annual configuration cost of the energy storage system is established as the objective function. The simulation results show that the improved algorithm reduces the cost of the hybrid energy storage system by 6.15% compared with the original algorithm, suppresses the power fluctuation, and improves the economy and stability of the system. [ABSTRACT FROM AUTHOR]

Ammonia (NH3) is a carbon-free and hydrogen-rich (17.8 wt% H2) chemical that has the potential to revolutionize the energy sector. Compared with hydrogen (H2), NH3 can be easily liquefied, stored, and transported globally. However, the conventional thermocatalytic process to synthesize NH3 accounts for 2% of global energy consumption and 1.2% of CO2 emissions annually. To make the process further efficient, new catalysts must be developed to allow for NH3 synthesis in milder conditions with high thermal stability. To this end, we have developed ruthenium (Ru) supported on perovskite (BaCexOy) via a ball-milling-assisted exsolution method that allows for a more tunable morphology. Reactivity is compared with the catalyst prepared via the conventional impregnation technique. The as-synthesized catalysts are characterized by XRD, H2-TPR, TEM, XPS, and APT. The NH3 synthesis is carried out in a packed-bed tube reactor thermochemically. Using N2 instead of Ar as the carrier gas during exsolution can favour reactivity by increasing active sites and perhaps improving metal-support interaction. The impregnated sample shows higher reactivity than the exsolved catalyst; however, the long-term durability is slightly better using the exsolved catalyst. Finally, APT results interestingly show that the exsolved catalyst is more resistant to hydride formation and hydrogen poisoning, which is one of the main deactivation mechanisms for such metallic catalysts. [ABSTRACT FROM AUTHOR]

Energy sources will contribute enormously to global economic development in the coming years. Global energy sectors mainly depend on fossil fuels, which contribute to greenhouse gas emissions. With the threat of declining oil supplies and the need to reduce CO2 emissions, the development of viable substitutes for fossil fuels is high on the global priority list. Currently, there is an increased focus on using low alcohols as fuels and petrochemicals. Catalytic conversion is a viable approach for upgrading low alcohols to fuels and value-added chemicals. This review study shows that optimal catalyst modification improves catalytic performance in the volarization of bioethanol. Heterogeneous catalysts are widely used in bioethanol conversion due to their activity. However, further studies are needed to address the challenges of limited selectivity, catalyst deactivation, recovery, and regeneration for improved biofuel production. [ABSTRACT FROM AUTHOR]

Ghana is experiencing an increase in energy demand as a result of increased industrialization activities. Nonrenewable energy sources, such as combustible fuels like petroleum, are the primary source of energy. Nonrenewable energy resources are associated with a number of issues, including environmental pollution. Renewable energy is a sustainable source of energy that is critical to the energy sector and the economy’s progress. Hydropower, biomass, solar energy, and wind energy are among the renewable energy resources available in Ghana. In Ghana, key institutions are responsible for the management and development of energy sources in the renewable energy sector. Among these institutions is the Ministry of Energy, which is responsible for the formulation and implementation of laws and policies, for instance, the Renewable Energy Act of 2011. Volta River Authority (VRA), Ghana Grid Company (GGC), and Electricity Company of Ghana (ECG) are among the institutions under the Ministry of Energy. There are also regulatory agencies established by parliamentary act to ensure that all actors in the sector are working properly. Among these are the Energy Commission, the Public Utilities Regulatory Commission (PUR), and the National Petroleum Authority. Active nongovernmental organisations (NGOs), research institutes and universities, and industry are also involved in renewable energy activities. Ghana is experiencing an increase in energy demand as a result of increased industrialization activities. Nonrenewable energy sources, such as combustible fuels like petroleum, are the primary source of energy. Nonrenewable energy resources are associated with a number of issues, including environmental pollution. Renewable energy is a sustainable source of energy that is critical to the energy sector and the economy’s progress. Hydropower, biomass, solar energy, and wind energy are among the renewable energy resources available in Ghana. In Ghana, key institutions are responsible for the management and development of energy sources in the renewable energy sector. Among these institutions is the Ministry of Energy, which is responsible for the formulation and implementation of laws and policies, for instance, the Renewable Energy Act of 2011. Volta River Authority (VRA), Ghana Grid Company (GGC), and Electricity Company of Ghana (ECG) are among the institutions under the Ministry of Energy. There are also regulatory agencies established by parliamentary act to ensure that all actors in the sector are working properly. Among these are the Energy Commission, the Public Utilities Regulatory Commission (PUR), and the National Petroleum Authority. Active nongovernmental organisations (NGOs), research institutes and universities, and industry are also involved in renewable energy activities. [ABSTRACT FROM AUTHOR]

As one of the vital ergonomics operations, occupational health and safety (OHS) measures are important for each and every production environment. Furthermore, the severity of adverse impacts or occurrence probability of OHS risks can be much higher, especially for particular companies dealing with hazardous or dangerous materials or products. Although eminent instances exist in the OHS literature, studies linking OHS to operational supply chain management (SCM) activities and aim to embed ergonomics sentiment into decision procedures in a way that reduces OHS risks are unfortunately lacking in the literature. In this point of view, a novel approach grounding on inventory control aiming OHS risk minimization was developed, and a case study regarding a gas distribution energy company was performed as demonstration. Integrated ABC-VED matrix was developed and employed to handle the inventory management problem by emphasizing OHS risks' influence as well as proposing cost-effective solutions, while spherical fuzzy sets (SFS) and simple additive weighting (SAW) method were used to enlighten the best SCM-related decisions in terms of ABC-VED results, to minimize the OHS risks of maintenance employees and possible adverse impacts on human health. Three different actors participated as decision makers (DMs) by the employment of SFS-SAW group decision making approach, where computed categories and delineated research outcomes were scrutinized in details by benchmarking of the results in terms of varying DM assessments and supplier company driven inventoried item groups, where sensitivity analysis on overall results were also performed. 103 out of 270 items of a protoset were analyzed, a subset of 51 items listed in Category I was determined to be used in further analysis. Illustrative explanations of diversification of criteria weighting scores regarding different parties in the decision making process were also presented with several schematic representations of research outcomes in the light of multidimensional benchmarking debates. [ABSTRACT FROM AUTHOR]

People's daily life heavily depends on energy. The core business of electric power enterprises is commercial energy sales. In the daily work of power enterprises, energy marketing is the most important field which will directly affect the development of enterprises. Although national macro-control exists as a useful way to control the energy market, it also increases the risk of the energy market. Nowadays, the development of the energy market is affected with the adjustment of industrial structure. In the energy market, China's power companies are state-owned enterprises and have their unique advantages for developing, but there are still some problems in risk awareness, which require us to take measures to control and prevent the impact risk. [ABSTRACT FROM AUTHOR]

Summary: Gaza has been suffering from a major crisis in the energy sector, and there is a need to adopt sustainable sources of renewable energy such as wind energy to meet the growing energy needs. This study focuses on wind energy harvesting potential as a renewable, clean source of energy in the Gaza Strip for a sustainable economy and environmental conservation. Three‐blade horizontal turbines were tested with rotor diameters of 4.4, 3.8, and 3.2 m. The effect of the wind speed and the rotor diameter on the tip speed ratio (TSR), the power factor (Cp), and the turbine produced power were investigated. The result showed that annual energy of 4851.87, 3618.85, and 2566.28 kWh achieved at rotor diameters of 4.4, 3.8, and 3.2 m, respectively. The result also exposed that the total saving per year is equal to $824.8, $615.2, and $436.3 at rotor diameters of 4.4, 3.8, and 3.2 m, respectively. The payback periods of a turbine with 4.4 m rotor diameter were 8.3 years. Also, using a turbine with a rotor diameter of 4.4 m can reduce 4124 kg/yr of CO2 emissions. It is recommended to encourage the private sector to invest in wind energy in Gaza to ensure economic growth and environmental sustainability. [ABSTRACT FROM AUTHOR]

The pursuit of middle-income economic status by Ghana comes with an associated increase in electricity and energy demand. Meanwhile, an increase in either electricity or energy consumption is likely to result in greenhouse gas (GHG) emissions as a result of increasing reliance on fossil fuel consumption. Presently, there is evidence of the impact of climate change on various aspects of Ghana's socio-economic structures such as energy production, agriculture, and forestry. Therefore, it is imperative to develop and implement a long-term low-carbon sustainable energy supply strategy that will support the electricity demand of the major economic ambitions envisaged. This study applied a quantitative modelling and simulation methodology using the Model for Energy Supply Strategy and their General Environmental Impacts (MESSAGE) analytical tool to analyse the electricity generation system and the impact of fuel options on the environment. It was found that the inclusion of low-carbon emission energy conversion technologies such as renewables and nuclear energy is critical to curtailing carbon dioxide (CO2) emissions in Ghana's energy sector. Therefore, the incorporation of climate-friendly energy sources into the electricity sector is necessary to achieve sustainable, resilient, and clean electricity generation. Ghana's fulfilment of its international commitment to climate change depends on reducing its dependence on fossil fuels for electricity generation, thus, exploring the inclusion of zero-emitting sources into the country's energy mix. [ABSTRACT FROM AUTHOR]

Energy is essential to the development of a country, and several studies have been carried out on the production and use of energy by industrialised countries. However, little research and development has been carried out in developing countries on renewable energy. Also, the importance of traditional fuels such as biomass has not been emphasised in developing countries like Ghana, which rely on fossil fuels. Ghana relies heavily on imported petroleum fuel obtained from fossil fuels. However, fossil fuels are faced with many limitations including environmental pollution and an escalating price. Hydropower, biomass, biofuel, wind, and solar energy are the major renewable energy resources expected to be fully exploited in the future. This study, therefore, assesses the sources of the main renewable energy in relation to policy, the conditions of the market and food security. The government of Ghana has put in place a favourable business environment for the renewable energy sector by setting explicit feed-in tariffs (FITs). In addition, various acts and legislation have been passed and formulated by the relevant institutions (Renewable Energy Act (832) of 2011). The study revealed that there is an increase in the exploitation and use of energy from renewable resources when compared with the past decades. However, this exploitation is still limited due to barriers such as the cost of technologies, financing issues, and scientific and technical barriers. [ABSTRACT FROM AUTHOR]

Summary: Energy has been considered as one of the essential needs of mankind along with air, water, and food and witnessed evolution of civilization since evidence of human life. Managing energy resources is one of the challenging problems being capital intensive. Addressing this involves critical thinking and decision making with all possible aspects, technically known as set of primary and secondary criteria. There exist a number of literature sources addressing applications of multicriteria decision‐making (MCDM) in different energy‐related areas. Some are focusing on energy policy making, few are explaining site selection of solar PV, wind farm, and hydro power plants, and a few are describing applications in load management. Moreover, a few literature in this field elaborates various MCDM methods and their applications. In this article, an extensive and exhaustive study is carried out incorporating almost all possible applications of MCDM in renewable energy area. Various energy‐intensive applications are mapped with MCDM methods along with governing sensitive parameters. Hence, this study facilitates practicing engineers, decision‐makers, academician, and researchers to identify areas and MCDM techniques researched over the past decade in energy sector for planning, managing, selecting renewable resources, etc. [ABSTRACT FROM AUTHOR]

The key technology research and development (R&D) of new energy automobile industry is a collaborative innovation activity of multi-innovation subjects, and how to set up effective incentive mechanisms and safeguards to stimulate innovative subjects and urge them to invest in corresponding efforts is crucial to ensure the success of key technologies R&D in the new energy automobile industry. To solve the incentive problem of key technology R&D of new energy automobile industry, considering government subsidy and the risk attitude of government and innovation subject, from the perspective of stakeholder negotiation and system coordination, introduce the minimum-cost consensus method into grey target decision-making and set constraint conditions to ensure a stable and effective incentive method. Then use a case to verify the effectiveness and rationality of the proposed model. [ABSTRACT FROM AUTHOR]