Hasil untuk "Renewable energy sources"

Letao Yang, Xi Kong, Fei Li et al.

Abstract The projected increase in world energy consumption within the next 50 years, coupled with low emission requirements, has inspired an enormous effort towards the development of efficient, clean, and renewable energy sources. Efficient electrical energy storage solutions are keys to effective implementation of the electricity generated from these renewable sources. In step with the development of energy storage technology and the power electronics industry, dielectric materials with high energy density are in high demand. The dielectrics with a medium dielectric constant, high breakdown strength, and low polarization hysteresis are the most promising candidates for high-power energy storage applications. Inspiring energy densities have been achieved in current dielectrics, but challenges exist for practical applications, where the underlying mechanisms need to be understood for further enhancing their properties to meet future energy requirements. In this review, we summarize the principles of dielectric energy-storage applications, and recent developments on different types of dielectrics, namely linear dielectrics, paraelectrics, ferroelectrics, and antiferroelectrics, are surveyed, focusing on perovskite lead-free dielectrics. The new achievements of polymer-ceramic composites in energy-storage applications are also reviewed. The pros and cons of each type of dielectric, the existing challenges, and future perspectives are presented and discussed with respect to specific applications.

R. Baños, F. Manzano-Agugliaro, F. G. Montoya et al.

Y. M. Atwa, E. El-Saadany, M. Salama et al.

Canan Acar, I. Dincer

W. Mrozik, M. Rajaeifar, O. Heidrich et al.

There is a growing demand for lithium-ion batteries (LIBs) for electric transportation and to support the application of renewable energies by auxiliary energy storage systems. This surge in demand requires...

S. Harris

This article reviews the National Audubon Society's report ''Side Effects of Renewable Energy Sources (SERES).'' The report, prepared by Dr. Larry Medsker, surveyed nine types of renewable energy, identifed the possible problems with each type, and showed how the problem could be minimized or avoided. Tables that list the consequences of development and the accompanying environmental stresses on land, air, water, wildlife, and flora are contained in the report.

Staffan Jacobsson, V. Lauber

Mohammed Yekini Suberu, M. Mustafa, N. Bashir

Anya Castillo, D. Gayme

Anis Omri, D. K. Nguyen

N. Apergis, J. Payne

Mohammadali Ranjbar, Hamid Reza Baghaee, Amin Ramezani

The rapid proliferation of electric vehicles (EVs) has transformed power distribution networks, making the development and optimal management of Electric Vehicle Charging Stations (EVCS) a critical concern. Integrating EVCS with Renewable Energy Sources (RES) not only reduces fossil-fuel dependency but also enhances grid sustainability and lowers operational costs. However, variability in RES generation and unpredictable user charging patterns complicate station management. Strategic siting of EVCS is vital to minimizing network losses, flattening load profiles, and improving power quality. In response, this paper offers a systematic review of recent research on EVCS planning and control, examining optimization techniques for station location and capacity, advanced planning and control models, and grid-interactive charging strategies. We assess intelligent economic charging approaches—including dynamic scheduling, prediction-based control, and real-time grid interaction—and demonstrate how multi-objective optimization frameworks can reconcile cost efficiency, stability, and energy efficiency. Drawing on the IEA's Global EV Outlook 2025 projection of over 40 million EVs by 2030 (20 % CAGR since 2020), we underscore the need for scalable, RES-integrated charging frameworks aligned with techno-economic and policy-driven targets. Finally, we identify emerging trends in machine learning and artificial intelligence applications for predictive control and chart future research directions to enhance EVCS performance and grid integration.

Peng Wu, Zongze Li

As renewable energy continues to rise in the global energy mix, wind energy is gradually increasing its share in the power system as a clean, renewable form of energy. However, the volatility and uncertainty of wind power bring new challenges to power system operation, making the need for its efficient prediction and intelligent dispatch more and more urgent. Based on this, a method combining genetic algorithm and backpropagation neural network is proposed for wind power prediction and energy storage scheduling. In this study, the improved genetic algorithm-backpropagation algorithm was generated by optimizing the weights and thresholds of the backpropagation neural network through the genetic algorithm, and optimizing the crossover and mutation processes of the genetic algorithm using similar block-order single-point crossover operator and shift mutation operator. Moreover, the improved genetic algorithm-backpropagation Neural Network wind energy prediction model was successfully constructed. Subsequently, the improved genetic algorithm was applied to search for the parameters of support vector machine and an improved genetic algorithm-support vector machine photovoltaic power generation prediction model was established. The experimental results showed that the average absolute percentage error of the improved genetic algorithm backpropagation neural network algorithm was 2.4%, and the accuracy was significantly higher than that of the traditional backpropagation neural network algorithm. The maximum photovoltaic prediction error of the autoregressive integral moving average model was about 80MW, while the photovoltaic prediction error of the improved genetic algorithm support vector machine photovoltaic prediction model was only about 12kW. In addition, the average absolute percentage error of the improved genetic algorithm support vector machine photovoltaic prediction model was only 1.53%, which was only 0.2% higher than the support vector machine prediction model. This study not only improves the stability of the power grid but also provides a practical and feasible method for realizing the large-scale application of clean energy, making a positive contribution to the sustainable development of the energy industry.

Babak Ranjbaran, Yonatan Afework Tesfahunegn, Raúl Bayoán Cal et al.

Vertical-axis wind turbine (VAWT) efficiency depends mainly on the aerodynamic properties of the airfoils used in their blades. During each rotation of the turbine, the blade experiences a range of angles of attack (AOAs) with respect to the relative wind, resulting in a variation of its contribution to the overall performance of the turbine. This paper leverages the capabilities of XFoil for preliminary performance analysis and ANSYS Fluent for detailed Computational Fluid Dynamics (CFD) simulations. The initial selection of airfoils is based on geometric characteristics and their potential for high tangential force coefficients. The asymmetric airfoils were selected by maximizing the average tangential force coefficient within the operational range of the AOAs through simple and computationally inexpensive 2D analysis. We then investigate the performance of the selected asymmetric airfoils in small-scale VAWTs for two rotor configurations, namely for two-bladed and three-bladed turbines. Using CFD, these configurations are compared with a baseline rotor utilizing a symmetric NACA 0018 airfoil. The rotors equipped with the asymmetric airfoils showed an increase in the power coefficient by 7.7% for the two-bladed rotors and 6.8% for the three-bladed rotors at the TSR of 4 and TSR of 3, respectively.

Heth Sethia, Abhishek Priyam

The use of hydrogen fuel cells has greatly increased in recent years. Advanced fuel cells are efficiently addressing the needs of portable power, backup power, and even modular power fuel cells. It has also been used to power cars and other vehicles. Hydrogen fuel cells are now specialized under the name portable power modules to highlight their newly discovered vehicle-mountable outboard engines. This review also targets the other issues of handling and encasing hydrogen fuel in specialized containers. All these gaps that revolve around the modern world are intertwined with one advancing vehicle engine to fix the ever-increasing global warming levels. Challenges faced by cost, storage, and infrastructure barriers are addressed, in addition to technological advancements in catalyst effectiveness, membrane technology, and hydrogen supply logistics. The report ends with a visionary outlook, outlining research avenues to drive the shift to a hydrogen economy.

Sharaf K. Magableh, Oraib Dawaghreh, Xuesong Wang et al.

Traditional monofacial photovoltaic (mPV) systems are commonly adopted and well-documented because of their lower upfront costs in comparison to bifacial photovoltaic (bPV) systems. This study investigates how PV technologies impact energy storage in grid-scale hybrid renewable systems, focusing on optimizing and assessing the performance of mPV and bPV technologies integrated with pumped storage hydropower. Using Ludington City, Michigan as a case study and analyzing realworld data such as solar irradiance, ambient temperature, and utility-scale load profiles, the research highlights the operational and economic benefits of bPV systems. The results reveal that bPV systems can pump approximately 10.38% more water annually to the upper reservoir while achieving a lower levelized cost of energy ($0.0578/kWh for bPV vs. $0.0672/kWh for mPV). This study underscores the outstanding potential of bPV systems in enhancing energy storage and management strategies, contributing to a more sustainable and resilient renewable energy future.

Jun-Shuo Zhang, Tian-Cong Wang, Pei Wang et al.

Fast radio bursts (FRBs) are widely considered to originate from magnetars that power the explosion through releasing magnetic energy. Active repeating FRBs have been seen to produce hundreds of bursts per hour and can stay active for months, thus may provide stringent constraints on the energy budget of FRBs' central engine. Within a time span of 214 days, we detected 11,553 bursts from the hyper-active FRB 20240114A that reached a peak burst rate of 729 hr$^{-1}$. This is the largest burst sample from any single FRB source, exceeding the cumulative total of all published bursts from all known FRBs to date. Assuming typical values of radio efficiency and beaming factor, the estimated total isotropic burst energy of this source exceeds 86% of the dipolar magnetic energy of a typical magnetar. The total released energy from this source exceeds that of other known repeaters by about one and a half orders of magnitude, yielding the most stringent lower limit of $4.7\times10^{32}$ G cm$^3$ for the magnetar's magnetic moment. The source remained active at the end of this observation campaign. Our findings thus require either the FRB's central magnetar engine's possessing exceptionally high emission efficiency or a more powerful compact object than a typical magnetar.

Felix Schmidt, Alexander Roth, Wolf-Peter Schill

Hydrogen-based long-duration electricity storage (LDES) is a key component of renewable energy systems to deal with seasonality and prolonged periods of low wind and solar energy availability. In this paper, we investigate how electrified heating with heat pumps impacts LDES requirements in a fully renewable European energy system, and which role thermal storage can play. Using a large weather dataset of 78 weather years, we find that electrified heating significantly increases LDES needs, as optimal average energy capacities more than quadruple across all weather years compared to a scenario without electrified heating. We attribute 75% of this increase to a leverage effect, as additional electric load amplifies storage needs during times of low renewable availability. The remaining 25% are the result of a compound effect, where exceptional cold spells coincide with periods of renewable scarcity. Furthermore, heat pumps increase the variance in optimal storage capacities between weather years substantially because of demand-side weather variability. Long-duration thermal storage attached to district heating networks can reduce LDES needs by on average 36%. To support and safeguard wide-spread heating electrification, policymakers should expedite the creation of adequate regulatory frameworks for both long-duration storage types to de-risk investments in light of high weather variability.

Huiping Wu, Zhaohan Shen, Wei Yu et al.

Lithium–oxygen (Li–O2) batteries with ultra-high theoretical specific energy (3500 Wh kg−1) have attracted significant attention, but the sluggish electrochemical processes of discharge product Li2O2 lead to poor cycling stability. Redox mediators (RMs) as soluble catalysts are widely used to assist with the electrochemical formation/decomposition of Li2O2. However, the shuttle effect of RMs causes severe deterioration of both RMs and Li metal anodes. Herein, for the first time we synthesize a lithiated zeolite-based protective layer on Li anodes to mitigate the shuttle effect of 2,2,6,6-tetramethylpiperidinyloxy (TEMPO) in Li–O2 batteries. The protective layer successfully blocks the migration of TEMPO toward the Li anode owing to the angstrom-level aperture size of lithiated zeolite. Due to the excellent redox-mediator-sieving capability of the protective layer, the cycle life of the Li−O2 batteries is significantly prolonged more than ten times at a current density of 250 mA g−1 and a limited capacity of 500 mA h g−1. This work demonstrates that the lithiated zeolite-based protective layer capable of molecular sieving is a facile and scalable way to mitigate the shuttle effect of RMs in Li–O2 batteries.

Somil Yadav, Caroline-Hachem Vermette, Md.Nadim Heyat Jilani et al.

Double Skin Façade (DSF) system comprises two glazing layers with a ventilated cavity. Integrating photovoltaic (PV) modules within the outer layer of DSFs offers an efficient method for electricity generation. Current tools for modeling and analyzing DSF systems are complex and resource-intensive, lacking the capability to evaluate the performance of innovative PV-DSF systems during the early design stage. This study develops a mathematical model to evaluate the electrical and thermal performance of PV-DSF systems, considering architectural design elements such as PV color and relative orientation. Based on an energy balance approach, the model is particularly suited for designing PV-DSF systems in heritage buildings, which often have color and relative orientation constraints. The model is applied to assess the performance of PV-DSF systems with conventional clear glass PV and colored front glass PV modules under the climatic conditions of Montreal, Canada. Results indicated that conventional clear glass PV module exhibit higher PV cell temperature than colored PV modules due to greater transmissivity, with peak temperature differences at noon of 5.5 °C, 6.2 °C, and 6.5 °C for orange, blue, and gray PV modules, respectively. On the contrary, the influence of PV's color front glass on room air temperature is non-significant. Furthermore, the optimal orientation for maximum energy yield is not always south-facing; it depends on the hourly distribution of the beam, diffuse solar irradiation, and ambient air temperature. For Montreal, west-facing DSFs produce more electrical and thermal energy on a summer design day because the hourly distribution of beam radiation is skewed towards afternoon hours.