Journal of Renewable and Sustainable Energy is an online-only journal dedicated to publishing significant advances covering all aspects of renewable and sustainable energy relevant to the physical science and engineering communities. As a web-based journal with rapid publication time, Journal of Renewable and Sustainable Energy is responsive to the many new developments expected in these fields. The interdisciplinary approach of the publication ensures that the editors draw from authors from around the world across a diverse range of active and expanding fields. The journal is published online only on a bi-monthly basis (6 issues per year).
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Increasing energy demand has created the challenge of supplying safe, economical, and durable energy with minimal impact on the environment. Therefore, governments have developed and executed several strategies such as increasing efficiency in energy systems in addition to replacing existing sources with renewable energies. One of the most important renewable energy sources that have a competitive advantage compared with other resources is solar energy and its related technologies. However, development of this technology, its related products, and their competitiveness in the market has created a plethora of challenges. In this study, the focus is on the analysis of photovoltaic technology development in the context of different technology generations. The S-shape curve of each generation and sub-technologies of photovoltaic is designed and analyzed. Results show that the first generation of photovoltaic technology is in growth and early maturity stage. The second generation is also in growth stage, but the third generation is mainly in the introduction stage.
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The photovoltaic (PV) industry encounters a serious oversupply problem, which has caused a fierce competition among the crystalline silicon module suppliers to get the business from the PV system assemblers. This paper has developed a mechanism to coordinate a c-Si module supplier and a PV system assembler considering the government subsidy. A centralized, a decentralized, and a joint bargaining coordination decision models in a PV supply chain are formulated and analyzed. Using the world PV industry data, the numerical and sensitivity analyses are conducted to assess the impact of key parameters on the decision models. The research result has shown that a joint bargaining coordination mechanism is optimal for the studied PV supply chain. Both a PV system assembler and a c-Si module supplier gain more profit from the joint bargaining coordination model than that from either the centralized or the decentralized decision model. Policies for the sustainable PV industry development are also recommended.
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In this paper, a methodology of sizing optimization of a stand-alone hybrid PV/wind/battery power generation system (HPWGS) is proposed. The main objective of this optimization is to minimize the total annual cost (TAC) of the hybrid system considering power balanced constraint and determination of the optimal number of wind turbines, PV panels, and batteries. For this purpose, a new meta-heuristic nature-inspired algorithm, called Grey Wolf Optimizer is utilized. The obtained results show that the proposed methodology finds optimal sizing of the HPWGS easily with fast convergence and lower cost. Comparing the results of this new method with the well-known published works in the literature, the superior capabilities of this proposed method are demonstrated. Moreover, the results show that the reliability characteristics are weakened with decreasing the component availability, and the supply reliability of the HPWGS is improved by increasing the inverter efficiency while the TAC is decreased. Furthermore, the HPWGS can cover the load demand variations with high reliability.
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In this study, the potential of solar energy in Ma'an area has been assessed and the optimal tilt angles for maximizing the collected radiation were determined using a validated model for calculating solar irradiation on south facing tilted surfaces. Ma'an area was selected for this study because it receives higher level of solar radiation worldwide, which motivates the national and the international companies to invest in solar energy. The trajectories of monthly, seasonal, bi-annual, and annual optimal tilt angles were specified. The results showed that an annual optimal fixed tilt angle of 28.7° would result in 0.20% and 16.1% extra collected radiation when compared with that collected by a surface with the latitude fixed tilt of 30.2° and horizontal surface, respectively. The increases in the yearly average collected radiation were 22.0% for monthly, 20.9% for seasonally, 17.0% for semi-annual, 40.5% for one axis tracking, and 45.9% for two axes tracking compared with that on a horizontal surface. The results suggest that adjusting the panel four times a year is recommended.
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The knowledge of the climatic parameters' evolution represents a determining factor for design, dimensioning, performance assessment, and energetic management of renewable energy conversion systems. In particular, the solar energy conversion systems are essentially sensitive to sunlight and ambient temperature. However, for the efficient functioning and better performance of renewable energy systems, the information of solar radiation and its components at particular location in the ground is very essential. But harvesting this energy efficiently is a huge challenge. In developing countries like ours, the number of observing stations is inadequate and direct measuring is not always available for various reasons. Therefore, the need for empirical relations becomes effective alternatives to estimate global solar radiation for the places where measurements are not carried out and for the places where measurement records are not available. In this paper, four empirical models are evaluated across four localities in Cameroon and Senegal and compared with the solar radiation values measured by the meteorological stations or obtained from different databases. The studied models are those of Hargreaves and Samani [J. Irrig. Drain. Eng., Am. Soc. Civ. Eng. 108(3), 225–230 (1982)], Annandale et al. [Irrig. Sci. 21, 57–67 (2002)], Bristow and Campbell [Agric. For. Meteorol. 31, 159–166 (1984)], and Goodin et al. [Agron. J. 91, 845–851 (1999)]. According to the simulation results, the mean yearly radiation received are 3.8414 kWh m−2 d−1 for Yaounde; 3.9869 kWh m−2 d−1 for Garoua; 2.2539 kWh m−2 d−1 for Dakar; and 5.9159 kWh m−2 d−1 for Gandon. Of all the models evaluated in this study, those proposed by Annandale et al. [Irrig. Sci. 21, 57–67 (2002)] and Goodin et al. [Agron. J. 91, 845–851 (1999)] produced estimates that are statistically significant at the particular confidence level, i.e., 1 − α = 99%, as the calculated t values are less than the critical t value (2.5758). Taking into account the foregoing, we can state that these models are suitable in estimating solar radiation in the localities where only air temperature data are available.
Latest Articles
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What influences personal purchases of new energy vehicles in China? An empirical study based on a survey of Chinese citizens
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Currently, many Chinese cities are suffering from the mounting pressures of deteriorating environmental quality, particularly in the form of serious air pollution that contributes to fog and haze. An important reason for urban air pollution is the rapid increase in automobile ownership and usage, which has increased gasoline consumption and waste gas production. Thus, it is important—and even necessary—to develop new energy vehicles (NEVs) to mitigate the environmental problems associated with automobile usage. However, the market share of NEVs in China is still relatively low. For the sake of boosting NEV sales, research should be conducted on this market, particularly regarding Chinese consumers' preferences for and intentions to purchase environmentally friendly vehicles. This study employs a carefully designed questionnaire survey of potential electronic vehicle consumers in seven Chinese cities. An empirical analysis based on the survey data is performed to investigate the main factors influencing the purchase of electronic vehicles. The estimation results indicate that monthly income, the number of cars a family owns, sustainability and vehicle comfort strongly influence consumers' purchasing behavior. Furthermore, age, marital status, city of residence, the number of cars a family owns, and the extent of police familiarity concerning NEVs are all proven to be significantly determinants of consumers' purchasing intentions. Moreover, based on our results, several political suggestions are provided to encourage the development of the Chinese NEV market.
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Renewable energy strategies and energy security
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This paper considers the effects of renewable energy strategies on energy security. Based on theoretical analysis, we conclude that energy supply shocks benefit firms with a sacrifice of consumer surplus, while the effects on social welfare depend on the degree of environmental concerns. Meanwhile, renewable energy strategies improve energy security by reducing the consumption of conventional energy and by reducing emissions. Furthermore, the total consumption of conventional energy decreases with the number of firms that adopt renewable energy. In addition, for low marginal costs of renewable energy, the efficiencies are equivalent for different covering rates of governmental subsidies. For high fixed costs or marginal costs, governmental subsidies yield excess capacity.
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Behavioral change in buying low carbon farm products in China: An application of the theory of planned behavior
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As global warming becomes increasingly pressing, many countries have begun to adopt carbon labeling on agri-products. Thus, it is prospective and significant to conduct a study on assessing the behavioral change in buying low carbon farm products in China, a country new to carbon labelling. Using a sample of the actual buying behavior of 873 subjects in China, we first examine the impact of Attitude, Perceived behavioral control, and Subjective (i.e., declarative and injunctive) norms on Actual behavior. Then, we investigate the mediating role of Behavioral intention in Actual behavior's relation with Attitude, Perceived behavioral control, and Subjective norms, respectively. Further, we explore the role of Subjective injunctive norms in the model based on the theory of planned behavior. Declarative norms, Attitude, and Perceived behavioral control explain a significant proportion of variance in actual buying behavior of low carbon products. Intentions fully mediate the relationship between Declarative norms and Actual behavior while partially mediating for Attitude and Perceived behavioral control. Injunctive norms moderate the relationship between Declarative norms and Actual behavior while partially mediating the relationship between Declarative norms and Attitude. Perceived behavioral control partially mediates the relationship between Declarative and Injunctive norms. These results suggest potential revisions to the theory of planned behavior model and practical implications to facilitate behavioral change from diagnostic and interventional perspectives.
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Coal price fluctuations in China: Economic effects and policy implications
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The price of coal fluctuated widely in the past few years in China. It is widely believed that rising coal prices can push up the inflation; this affected the determination of the policy of controlling coal price. This paper examines whether the rising coal price determines inflation in China. Bootstrap correlation test indicates that the Consumer price index (CPI) is not always positively correlated to the coal price in preceding months. The Bootstrap Granger test shows that coal price Granger-causes the CPI with 4–6 lags. However, many regression coefficients in the Granger test are negative and significant, which is consistent with the result of the bootstrap correlation test and contradicts the cost-push theory. Based on the Vector autoregression (VAR) model, bootstrap impulse response analysis reveals that coal price affects the CPI, but the directions of the effects vary and cancel each other out over a long period. Therefore, we find no evidence that shows a rise in coal price leads to cost-push inflation. Electricity price regulations, the price filter effect in the industry chain, and the Fisher currency trading equation theory can be used to explain this phenomenon. Finally, we conclude that both coal prices and the CPI are caused by inflation (in addition to market liquidity) instead of being the cause.
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Charging and discharging model of lithium-ion battery for charge equalization control using particle swarm optimization algorithm
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This study presents a charging and discharging controller of a lithium-ion battery for charge equalization control of a battery storage system using the particle swarm optimization (PSO) algorithm. The charge equalization controller is designed using a bidirectional flyback DC–DC converter for exchanging the amount of energy from a battery series stack to an overdischarged cell to be charged and vice versa. The constant current–constant voltage charge proportional–integral (PI) control and discontinuous current mode control are applied to charge and discharge the lithium-ion battery on a flyback converter operation. This proposed system utilizes the PSO algorithm to optimize the values of the PI controller parameters. Optimization results produce the ideal values of the PI controller parameters with minimum error indices, thereby regulating the pulse-width modulation to the MOSFET switching drive of the flyback converter and upgrading the battery charge performance for charge equalization. The PSO algorithmic approach-based developed system is proven to be robust and competent for high-tech storage systems toward the advancement of sustainable electric vehicle technologies and renewable source of applications.
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A fuzzy interval optimization-based approach to optimal generation scheduling in uncertainty environment
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This paper proposes a fuzzy interval optimization approach to solve the Environmental/Economic Dispatch (EED) problem with uncertain parameters in the constraints and the objective functions. The objective functions considered are fuel cost and the gaseous emissions of the generating units. Two different types of fuel cost functions are considered in this study, namely, the conventional quadratic function and the augmented quadratic function to introduce more accurate modeling that incorporates the valve loading effects. The latter model presents non-differentiable and nonconvex regions that challenge most gradient-based optimization algorithms. In the proposed approach, objective functions are fuzzified and integrated to represent the fuzzy decision value. On the other hand, load uncertainties are modeled using fuzzy intervals. This fuzzy EED problem formulation provides a modeling flexibility, relaxation in constraints and allows the method to seek a practical solution. The obtained fuzzy multi-objective optimization problem is solved using non-dominated sorting genetic algorithm-II, known for its global searching capabilities, to get the best compromise among all the objectives. The performance of this solution is examined and applied to the standard IEEE 30-bus six-generator test system and the Indian power network of 82-bus by comparing its results with that of the existing methods. Different cases with different complexities have been considered in the study reported in this paper.
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