Supply restrictions and associated price increase of lithium limit the large‐scale application of rechargeable lithium batteries (RLBs) in electric energy storage. Rechargeable sodium batteries ...(RSBs) with the advantage of large abundance and low cost of sodium, are developed to relieve the supply pressure of RLBs. Binders serve as a bridge between active materials and other components to maintain electrode integrity and electrical contact; however, they have not been sufficiently explored in RSBs. In this review, the working mechanism of binders for RSBs is proposed and more desirable features of RSB binders than their RLB counterparts are emphasized. The development history and recent progress of binders for RSBs are outlined. It is highlighted that the matching principles of binders to different electrode materials are proposed. Advanced characterization and simulation techniques are presented to interpret the electrochemical findings and reveal the working mechanism of novel binders in various electrodes of RSBs. Finally, perspectives on the development of effective binders for RSBs are presented.
The development history and recent progress of binders for rechargeable sodium batteries (RSBs) including sodium‐ion batteries and sodium–sulfur batteries are summarized. Critical and constructive insights are given from both underlying mechanistic and practical engineering perspectives to promote further development of advanced binders for high‐performance RSBs
Reduction of carbon dioxide (CO2) emissions will have a positive impact on the environment by preventing adverse effects of global warming. To achieve an eco-environment, the primary source of energy ...needs to shift from fossil fuels to clean renewable energy. Thus, increased utilization of renewable energy overtime reduces air pollution and contributes to securing sustainable energy supply to satisfy future energy needs. The main purpose of this study is to investigate several sustainable hybrid renewable systems for electricity production in Iran. In this regard, critical indicators that have the strongest impact on the environment and energy sustainability are presented in this study. After a comprehensive review of environmental issues, data was collected from the meteorological organization and a techno-economic assessment was performed using HOMER software. It was concluded that the hybrid configuration composed of photovoltaic (PV), wind turbine, diesel generator and battery produced the best outcome with an energy cost of 0.151$/kWh and 15.6% return on investment. In addition, the results showed that with a higher renewable fraction exceeding 72%, this hybrid system can reduce more than 2000 Kg of CO2 emission per household annually. Although excess electricity generation is a challenge in stand-alone systems, by using the fuel cell, an electrolyzer, and a hydrogen tank unit, the amount of energy loss was reduced to less than one-sixth. These results show that selecting useful indicators such as appropriate implementation of policies of new enabling technologies and investments on renewable energy resources, has three potential benefits namely: CO2 reduction, greater sustainable electricity generation and provides an economic justication for stakeholders to invest in the renewable energy sector.
•Technical, economic and environmental optimization is performed for a rural area.•Emphasis is placed on reduce global warming and secure stakeholder investment.•Carbon reduction strategies, international policies and demand status is discussed.•Optimum system is reached to 0.151 $/kWh cost of energy with 15.6% rate of return.•Proposed solution can reduce about 2000 kg of CO2 emission per household annually.
The demand of energy is increasing at an escalating pace and cannot be fulfilled entirely by conventional energy systems, due to their limited supplies. In addition to this they have a radical impact ...on the environment. In comparison to them hybrid energy systems are a suitable combination of renewable and non-renewable energy systems which keeps into account the advantages of both these systems, thus able to achieve reduction in cost of implementation and maintenance of the system, limited emission levels, improvement in reliability of the overall system etc. Designing of hybrid energy system for a locality and its implementation is an uphill task as the input parameters of the sources considered are randomly varying with time and are also independent of the load requirements. The paper encompasses review on various important sectors needed to be considered while designing and implementation of hybrid energy system; this includes configurations, criteria selection, sizing methodologies and control & energy management. This will help the designer to use suitable design constraints required while implementing hybrid energy system for grid connected or in off grid modes as per the requirement of the locality.
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•Extrinsic dielectric properties include dipolar and space charge polarizations.•Intrinsic dielectric properties are electronic/atomic/orientational polarizations.•Contributions of ...electronic and atomic polarizations are limited for high κ.•Dipolar glass polymers are good candidates for high energy and low loss dielectrics.•Multilayer films utilize both interfacial and orientational polarizations.
High energy density, high temperature, and low loss polymer dielectrics are highly desirable for electric energy storage applications such as film capacitors in the power electronics of electric vehicles or high-speed trains. Fundamentally, high polarization and low dielectric loss are two conflicting physical properties, because more polarization processes will involve more loss mechanisms. As such, we can only achieve a delicate balance between high dielectric constant and reasonably low loss. This review focuses on achieving low dielectric loss while trying to enhance dielectric constants for dielectric polymers, which can be divided into two categories: extrinsic and intrinsic. For extrinsic dielectric systems, the working mechanisms include dipolar (e.g. nanodielectrics) and space charge (e.g. ion gels) interfacial polarizations. These polarizations do not increase the intrinsic dielectric constants, but cause decreased breakdown strength and increased dielectric loss for polymers. For intrinsic dielectric polymers, the dielectric constant originates from electronic, atomic (or vibrational), and orientational polarizations, which are intrinsic to the polymers themselves. Because of the nature of molecular bonding in organic polymers, the dielectric constant from electronic and atomic polarizations is limited to 2–5 for hydrocarbon-based insulators (i.e., band gap > 4 eV). It is possible to use orientational polarization to enhance intrinsic dielectric constant while keeping reasonably low loss. However, nonlinear ferroelectric switching in ferroelectric polymers must be avoided. Meanwhile, paraelectric polymers often exhibit high electronic conduction due to large chain motion in the paraelectric phase. In this sense, dipolar glassy polymers are more attractive for low loss dielectrics, because frozen chain dynamics enables deep traps to prevent electronic conduction. Both side-chain and main-chain dipolar glass polymers are promising candidates. Furthermore, it is possible to combine intrinsic and extrinsic dielectric properties synergistically in multilayer films to enhance breakdown strength and further reduce dielectric loss for high dielectric constant polar polymers. At last, future research directions are briefly discussed for the ultimate realization of next generation polymer film capacitors.
The aim of the research was to determine the indicators of electricity consumption in every stage of the dairy sewage treatment process in relation to the sewage flow and the load of removed organics ...(BOD5, COD) and nutrients (TN, TP). The research was conducted in a dairy wastewater treatment plant (WWTP) consisting of mechanical treatment, averaging tank, dissolved air flotation (DAF) and biological treatment with sequence batch reactors (SBRs). Energy consumption was measured with the help of transducers. Indicators of unit electricity consumption were determined on the basis of 95 measurement series of energy consumption, sewage flow and removed load. The mean value of total unit energy consumption relating to the flow for the entire WWTP was 2.29 kWh·m−3, while for biological treatment 1.17 kWh·m−3 and 0.05 kWh·m−3 for DAF. The mean values of indicators relating to removed pollutants load for the entire WWTP were: 1.89 kWh·kgrem BOD5−1, 1.30 kWh·kgrem COD−1, 48.61 kWh·kgrem TN−1 and 160.01 kWh·kgrem TP−1. During biological treatment, energy consumption indicators were on average: 1.65 kWh·kgrem BOD5−1 and 1.19 kWh·kgrem COD−1, 52.90 kWh·kgrem TN−1 and 141.26 kWh·kgrem TP−1, while for DAF: 0.12 kWh·kgrem BOD5−1, 0.09 kWh·kgrem COD -1, 3.85 kWh·kgrem TN−1 and 16.17 kWh·kgrem TP−1. It was found that the biological treatment in SBRs was responsible for 54.1% of the total energy consumption of dairy WWTP. Aerobic sewage sludge treatment accounted for 17.0% of total consumption, mechanical treatment 17.1%, deodorization 2.6%, and other (social, lighting etc.) 6.9%, while DAF only 2.3%. The real-time electricity metering system enabled the optimisation of the electricity consumption in the WWTP, taking into account its consumption in unit processes and the removed pollutants load. The application of this system enabled to make corrections that reduced energy consumption while maintaining the required treatment efficiency.
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•Operation of dairy wastewater treatment plants (WWTPs) causes significant electric energy consumption.•Electricity consumption indicators were determined in relation to sewage flow and load removed.•Biological part of WWTP is responsible for 54.1% of total electricity consumption, DAF for 2.3%.•Energy consumption can be optimized thanks to real time electricity metering system in each WWTP.
The production of sustainable hydrogen with water electrolyzers is envisaged as one of the most promising ways to match the continuously growing demand for renewable electricity storage. While so far ...regarded as fast when compared to the oxygen evolution reaction (OER), the hydrogen evolution reaction (HER) regained interest in the last few years owing to its poor kinetics in alkaline electrolytes. Indeed, this slow kinetics not only may hinder the foreseen development of the anionic exchange membrane water electrolyzer (AEMWE), but also raises fundamental questions regarding the parameters governing the reaction. In this perspective, we first briefly review the fundamentals of the HER, emphasizing how studies performed on model electrodes allowed for achieving a good understanding of its mechanism under acidic conditions. Then, we discuss how the use of physical descriptors capturing the sole properties of the catalyst is not sufficient to describe the HER kinetics under alkaline conditions, thus forcing the catalysis community to adopt a more complex picture taking into account the electrolyte structure at the electrochemical interface. This work also outlines new techniques, such as spectroscopies, molecular simulations, or chemical approaches that could be employed to tackle these new fundamental challenges, and potentially guide the future design of practical and cheap catalysts while also being useful to a wider community dealing with electrochemical energy storage devices using aqueous electrolytes.
This perspective provides a new look into how electrolyte structure at the interface controls the kinetics of water reduction.
The exploitation of highly efficient carbon dioxide reduction (CO2RR) electrocatalyst for methane (CH4) electrosynthesis has attracted great attention for the intermittent renewable electricity ...storage but remains challenging. Here, N‐heterocyclic carbene (NHC)‐ligated copper single atom site (Cu SAS) embedded in metal–organic framework is reported (2Bn‐Cu@UiO‐67), which can achieve an outstanding Faradaic efficiency (FE) of 81 % for the CO2 reduction to CH4 at −1.5 V vs. RHE with a current density of 420 mA cm−2. The CH4 FE of our catalyst remains above 70 % within a wide potential range and achieves an unprecedented turnover frequency (TOF) of 16.3 s−1. The σ donation of NHC enriches the surface electron density of Cu SAS and promotes the preferential adsorption of CHO* intermediates. The porosity of the catalyst facilitates the diffusion of CO2 to 2Bn‐Cu, significantly increasing the availability of each catalytic center.
A catalyst with N‐heterocyclic carbene‐ligated Cu SAS as the active site, accompanied by many micro‐nano reactors, synergistically promotes the electrochemical synthesis of methane.
Renewable energy becomes a key contributor to our modern society, but their integration to power grid poses significant technical challenges. Power quality is an important aspect of renewable energy ...integration. The major power quality concerns are: 1) Voltage and frequency fluctuations, which are caused by noncontrollable variability of renewable energy resources. The intermittent nature of renewable energy resources due to ever-changing weather conditions leads to voltage and frequency fluctuations at the interconnected power grid. 2) Harmonics, which are introduced by power electronic devices utilized in renewable energy generation. When penetration level of renewable energy is high, the influence of harmonics could be significant. In this paper, an extensive literature review is conducted on emerging power quality challenges due to renewable energy integration. This paper consists of two sections: 1) Power quality problem definition. Wind turbines and solar photovoltaic systems and their power quality issues are summarized. 2) Existing approaches to improve power quality. Various methods are reviewed, and the control-technology-based power quality improvement is the major focus of this paper. The future research directions for emerging power quality challenges for renewable energy integration are recommended.
Electrochemical double-layer capacitors (EDLCs) are devices allowing the storage or production of electricity. They function through the adsorption of ions from an electrolyte on high-surface-area ...electrodes and are characterized by short charging/discharging times and long cycle-life compared to batteries. Microscopic simulations are now widely used to characterize the structural, dynamical, and adsorption properties of these devices, complementing electrochemical experiments and in situ spectroscopic analyses. In this review, we discuss the main families of simulation methods that have been developed and their application to the main family of EDLCs, which include nanoporous carbon electrodes. We focus on the adsorption of organic ions for electricity storage applications as well as aqueous systems in the context of blue energy harvesting and desalination. We finally provide perspectives for further improvement of the predictive power of simulations, in particular for future devices with complex electrode compositions.
The rapid increase in human population and development in technology have sharply raised power consumption in today's world. Since electricity is consumed simultaneously as it is generated at the ...power plant, it is important to accurately predict the energy consumption in advance for stable power supply. In this paper, we propose a CNN-LSTM neural network that can extract spatial and temporal features to effectively predict the housing energy consumption. Experiments have shown that the CNN-LSTM neural network, which combines convolutional neural network (CNN) and long short-term memory (LSTM), can extract complex features of energy consumption. The CNN layer can extract the features between several variables affecting energy consumption, and the LSTM layer is appropriate for modeling temporal information of irregular trends in time series components. The proposed CNN-LSTM method achieves almost perfect prediction performance for electric energy consumption that was previously difficult to predict. Also, it records the smallest value of root mean square error compared to the conventional forecasting methods for the dataset on individual household power consumption. The empirical analysis of the variables confirms what affects to forecast the power consumption most.
•We propose a novel deep learning model to stably predict electric energy consumption.•We analyze the model with the large data collected in an actual residential house.•We achieve the highest performance in high resolution compared with the previous works.•We explain the variables of appliances that influence the prediction performance.
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