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Showing papers in "Renewable & Sustainable Energy Reviews in 2021"


Journal ArticleDOI
TL;DR: Drawing conclusions show that continuous efforts on performance improvements, scale ramp-up, technical prospects and political support are required to enable a cost-competitive hydrogen economy.
Abstract: The global energy transition towards a carbon neutral society requires a profound transformation of electricity generation and consumption, as well as of electric power systems. Hydrogen has an important potential to accelerate the process of scaling up clean and renewable energy, however its integration in power systems remains little studied. This paper reviews the current progress and outlook of hydrogen technologies and their application in power systems for hydrogen production, re-electrification and storage. The characteristics of electrolysers and fuel cells are demonstrated with experimental data and the deployments of hydrogen for energy storage, power-to-gas, co- and tri-generation and transportation are investigated using examples from worldwide projects. The current techno-economic status of these technologies and applications is presented, in which cost, efficiency and durability are identified as the main critical aspects. This is also confirmed by the results of a statistical analysis of the literature. Finally, conclusions show that continuous efforts on performance improvements, scale ramp-up, technical prospects and political support are required to enable a cost-competitive hydrogen economy.

470 citations


Journal ArticleDOI
TL;DR: In this article, the authors explored the application of graphene in energy storage device, absorbers and electrochemical sensors, and found that these good characteristics of graphene must be extended further and improved to make them suitable for other applications.
Abstract: Most applications in energy storage devices revolve around the application of graphene. Graphene is capable of enhancing the performance, functionality as well as durability of many applications, but the commercialization of graphene still requires more research activity being conducted. This investigation explored the application of graphene in energy storage device, absorbers and electrochemical sensors. To expand the utilization of graphene, its present limitations must critically be addressed to improve their current performance. Again, in terms of applications, the advantages of graphene has widened their application in both electroanalytical and electrochemical sensors. These good characteristics of graphene must be extended further and improved to make them suitable for other applications. Critical study of facile synthesis of graphene coupled with detailed investigation into the structure of graphene oxide at the molecular level will equally improve the performance of this novel material. Effects of defects on the performance of graphene oxide was also identified as another key area of research that needs much attention to accelerate the commercialization of this material. With the rapid growth in the application of the graphene in different energy storage/conversion applications, it is essential to summarize and discuss the up-to-date progress in the application of graphene in these fields.

358 citations


Journal ArticleDOI
TL;DR: In this paper, the authors present a global-scale analysis of the major ecological impacts of three main small run-of-river hydropower types: dam-toe, diversion weir, and pondage schemes.
Abstract: The general perception of small run-of-river hydropower plants as renewable energy sources with little or no environmental impacts has led to a global proliferation of this hydropower technology. However, such hydropower schemes may alter the natural flow regime and impair the fluvial ecosystem at different trophic levels. This paper presents a global-scale analysis of the major ecological impacts of three main small run-of-river hydropower types: dam-toe, diversion weir, and pondage schemes. This review's main objective is to provide an extensive overview of how changing the natural flow regime due to hydropower operation may affect various aspects of the fluvial ecosystem. Ultimately, it will inform decision-makers in water resources and ecosystem conservation for better planning and management. This review analyses data on ecological impacts from 33 countries in five regions, considering the last forty years' most relevant publications, a total of 146 peer-reviewed publications. The analysis was focused on impacts in biota, water quality, hydrologic alteration, and geomorphology. The results show, notably, the diversion weir and the pondage hydropower schemes are less eco-friendly; the opposite was concluded for the dam-toe hydropower scheme. Although there was conflicting information from different countries and sources, the most common impacts are: water depletion downstream of the diversion, water quality deterioration, loss of longitudinal connectivity, habitat degradation, and simplification of the biota community composition. A set of potential non-structural and structural mitigation measures was recommended to mitigate several ecological impacts such as connectivity loss, fish injuries, and aquatic habitat degradation. Among mitigation measures, environmental flows are fundamental for fluvial ecosystem conservation. The main research gaps and some of the pressing future research needs were highlighted, as well. Finally, interdisciplinary research progress involving different stakeholders is crucial to harmonize conflicting interests and enable the sustainable development of small run-of-river hydropower plants.

270 citations


Journal ArticleDOI
TL;DR: In this article, the phase change heat transfer in porous phase change materials (ss-PCMs) is discussed and a review of the recent experimental and numerical investigations is presented, which shows that the pore-scale simulation can provide extra flow and heat transfer characteristics in pores, exhibiting great potential for the simulation of mesoporous, microporous and hierarchical porous materials.
Abstract: Latent heat thermal energy storage (LHTES) uses phase change materials (PCMs) to store and release heat, and can effectively address the mismatch between energy supply and demand. However, it suffers from low thermal conductivity and the leakage problem. One of the solutions is integrating porous supports and PCMs to fabricate shape-stabilized phase change materials (ss-PCMs). The phase change heat transfer in porous ss-PCMs is of fundamental importance for determining thermal-fluidic behaviours and evaluating LHTES system performance. This paper reviews the recent experimental and numerical investigations on phase change heat transfer in porous ss-PCMs. Materials, methods, apparatuses and significant outcomes are included in the section of experimental studies and it is found that paraffin and metal foam are the most used PCM and porous support respectively in the current researches. Numerical advances are reviewed from the aspect of different simulation methods. Compared to representative elementary volume (REV)-scale simulation, the pore-scale simulation can provide extra flow and heat transfer characteristics in pores, exhibiting great potential for the simulation of mesoporous, microporous and hierarchical porous materials. Moreover, there exists a research gap between phase change heat transfer and material preparation. Finally, this review outlooks the future research topics of phase change heat transfer in porous ss-PCMs.

259 citations


Journal ArticleDOI
Wai Siong Chai1, Yulei Bao1, Jin Pengfei1, Guang Tang1, Lei Zhou1 
TL;DR: In this article, the advantages and mechanisms involved with secondary fuel addition to the ammonia combustion, presenting the role of key reaction differences and the change in key reaction mechanism under different conditions at the level of reaction mechanisms.
Abstract: Combustion of fuels to generate energy is integral to various human activities, both domestic and industrial. However, the predominance of hydrocarbon fuel usage produces emissions containing pollutants that cause multiple environmental complications and risks to human health. Therefore, replacement of conventional fuels to achieve zero carbon emission is of utmost importance. In terms of carbon-free fuel, ammonia offers several advantages over hydrogen. However, its low burning velocity and high fuel NOx emissions inhibit large-scale usage. Hence, hydrogen and methane have been studied in this review as possible secondary fuels to aid ammonia combustion and address the aforementioned issues. This review starts from the suitability of ammonia fuel as energy vector in terms of physicochemical and combustion characteristics, moving through the kinetics and mechanisms of ammonia-based and ammonia-fuel combustion. The impacts and limitations of each system are also addressed, thus providing a comparison on each system. Particularly, this review assesses and discusses the advantages and mechanisms involved with secondary fuel addition to the ammonia combustion, presenting the role of key reaction differences and the change in key reaction mechanism under different conditions at the level of reaction mechanisms. Finally, this review covers future perspectives and challenges on the usage and development of ammonia-based fuels, emphasizing the maturity of ammonia-based and ammonia-fuel combustion kinetics. Herein, this work summarizes the principles of the combustion reactions of ammonia-based and ammonia-fuel systematically and serves as a theoretical reference of ammonia-fuel combustion kinetics for transitioning into future practical applications where ammonia is an important energy vector.

240 citations


Journal ArticleDOI
TL;DR: The technical comparative analysis of the different physical and material based types of HSSs illustrates the paradoxical inherent features, including gravimetric and volumetric storage densities and parameters associated with storage and release processes, among these systems.
Abstract: Hydrogen storage systems (HSSs), are the backbone of feasible hydrogen economy. To provide a reliable renewable energy system, safe, cost effective and compact HSS is due. Physical storage systems involve the compressed gas, liquid and cryo-compressed techniques while material based one involves adsorptive materials, metal hydrides and chemical storage materials. In this paper, the features of a variety of HSSs are impartially discussed. The technical comparative analysis of the different physical and material based types of HSSs illustrates the paradoxical inherent features, including gravimetric and volumetric storage densities and parameters associated with storage and release processes, among these systems. Accordingly, no ideal hydrogen storage technique can be considered the best-fit for all stationary and automotive applications. Therefore, not only a unique HSS solution can properly provide the needs, but a set of complementary HSS solutions which may offer the system designer several options. This set of options can be hardly interpretable in case of the unclear definition of the application needs which may be time variant. Inside this review, the critical insights and recommendations about suitable applications for storage systems are provided. Different standards and codes alongside the corresponding tests are demonstrated for the different storage technologies. Moreover, storage vessels research work is overviewed for the different hydrogen storage technologies. In addition, the failure behaviour, criteria and prediction models are investigated for composite vessels subjected to high pressures and extreme temperatures degrading their mechanical behaviour and failure resistance.

232 citations


Journal ArticleDOI
TL;DR: In this article, the authors present a comparative analysis of the mitigation targets of 327 European cities, as declared in their local climate plans, and analyze whether the type of plan, city size, membership of climate networks, and its regional location are associated with different levels of mitigation ambition.
Abstract: Cities across the globe recognise their role in climate mitigation and are acting to reduce carbon emissions. Knowing whether cities set ambitious climate and energy targets is critical for determining their contribution towards the global 1.5 °C target, partly because it helps to identify areas where further action is necessary. This paper presents a comparative analysis of the mitigation targets of 327 European cities, as declared in their local climate plans. The sample encompasses over 25% of the EU population and includes cities of all sizes across all Member States, plus the UK. The study analyses whether the type of plan, city size, membership of climate networks, and its regional location are associated with different levels of mitigation ambition. Results reveal that 78% of the cities have a GHG emissions reduction target. However, with an average target of 47%, European cities are not on track to reach the Paris Agreement: they need to roughly double their ambitions and efforts. Some cities are ambitious, e.g. 25% of our sample (81) aim to reach carbon neutrality, with the earliest target date being 2020.90% of these cities are members of the Climate Alliance and 75% of the Covenant of Mayors. City size is the strongest predictor for carbon neutrality, whilst climate network(s) membership, combining adaptation and mitigation into a single strategy, and local motivation also play a role. The methods, data, results and analysis of this study can serve as a reference and baseline for tracking climate mitigation ambitions across European and global cities.

227 citations


Journal ArticleDOI
TL;DR: In this article, a more novel concept is proposed, microbe-to-plant signal compounds, as the potential approach to address the challenges we are facing, given both the ongoing expansion of world population and development of climate change conditions, it is increasingly imperative to develop and deploy sustainable biomass production methods.
Abstract: Given both the ongoing expansion of world population and development of climate change conditions, it is increasingly imperative to develop and deploy sustainable biomass production methods to allow establishment of a flourishing and sustainable bioeconomy. Green technologies, including biofuels and bioproducts, are among the most effective strategies for decreasing greenhouse gas emissions and global warming, while meeting humanity's energy requirements. Biomass now provides a measure of energy to many countries, however supporting technologies are not widely accepted, largely because of low returns for biomass producers. This paper provides an overview of world biomass production and utilization. It also indicates potential approaches for enhancing biomass production: agronomic practices, associated microorganisms, genome editing, selection of optimal technologies, best combination approaches for feeding global human and animal populations, while, decreasing greenhouse gas emissions and replacing demand for fossil energy with bioenergy. A more novel concept is proposed, microbe-to-plant signal compounds, as the potential approach to address the challenges we are facing. These compounds (e.g., lipo-chitooligosaccharide and thuricin 17) have been shown to increase growth for diverse plant species, particularly when they are growing under stressful conditions, however, their commercial development/utilization is far from complete. This review paper will expand the understanding of using the signal interaction between crop and beneficial microorganisms not only to enhance plant growth but also promote agricultural sustainability and a stronger bioeconomy.

217 citations


Journal ArticleDOI
TL;DR: This work aims to provide a comprehensive scientific publication on the current status and future expectations of fuel cells in the vehicle industry to engineers and researchers interested in this field.
Abstract: The implementations of fuel cells (FCs) in the vehicle industry have gained great attention for the last few decades owing to simple utilization, silent operation, high efficiency and modular structure. Technological advancements show that the use of FCs in electric vehicles (EVs) will increase rapidly and cause a revolution, and will be an alternative to traditional vehicles in the future. Commercial vehicles, projects and research show that work is underway to ensure that FCEVs have sufficient performance advances for their daily transportation needs. However, the lack of a detailed study that will shed light on researchers working in this field is obvious. It aims to provide a comprehensive scientific publication on the current status and future expectations to engineers and researchers interested in this field. In the current study, numerous studies have been examined in detail and added as supplementary to the bibliography. In this context, FCEVs are classified under headings of configurations, systems components, control/management, technical challenges, marketing and future aspects. First of all, FC types and electric motors are discussed in terms of their application areas, characteristic properties and operating conditions. Power converters, which are voltage regulation and motor drive topologies used in FCEVs, are detailed according to the structural frequency of use, structure, and complexity. In the next sections, control issues for converters and technical challenges are branched for FCEVs. In final section, the current status and future aspects are reported using a large number of marketing and target data.

211 citations


Journal ArticleDOI
TL;DR: A comprehensive review of recent, encouraging research achievements in CO2 conversion using NTP is provided in this paper, where the authors discuss the recent progress in different NTP sources in relation to product selectivity, conversion, and energy efficiency.
Abstract: Increasing attention has been drawn to carbon dioxide (CO2) conversion into higher-value platform chemicals and synthetic fuels due to global warming. These reactions require a large amount of thermal energy in order to proceed, which is ascribable to the high stability of the bonds in CO2. Non-thermal plasma (NTP)-catalytic CO2 conversion has emerged as a promising method to significantly reduce the reaction temperature as plasma can activate CO2 at as low as room temperature and atmosphere pressure. However, this technology requires a paradigm shift in process design to enhance plasma-catalytic performance. CO2 conversion using plasma-catalysis has great potential to increase reaction efficiencies due to the synergetic effects between the plasma and catalysts. It is crucial to present the recent progress in CO2 conversion and utilization whilst providing a research prospects framework and direction for future research in both industries and laboratories. Herein, a comprehensive review of recent, encouraging research achievements in CO2 conversion using NTP is provided. The topics reviewed in this work are: i) the recent progress in different NTP sources in relation to product selectivity, conversion, and energy efficiency; ii) plasma-based CO2 reactions and applications; iii) CO2 conversion integrated with CO2 capture; and iv) current challenges and future perspectives. The high market value of the possible products from this process, including chemicals and fuels, make commercialization of the process feasible. Furthermore, the selectivities of these products can be further improved by developing suitable catalysts with effective sensitivities and performances under the intricate conditions needed to make these products. There is an urgent need for further studies to be performed in this emerging field.

192 citations


Journal ArticleDOI
TL;DR: In this article, the state-of-the-art microwave pyrolysis (MP) has emerged as a promising technique to valorize agricultural wastes (AW) into bio-fuels, comprising biochar, bio-oil, and syngas.
Abstract: Microwave pyrolysis (MP) has emerged as a promising technique to valorize agricultural wastes (AW) into biofuels, comprising biochar, bio-oil, and syngas. To fill the research gap, we review the state-of-the-art MP conversion of AW into value-added biofuels, including the influence of feedstock composition, new reactor designs, operating conditions, catalytic applications, and reaction mechanisms. The techno-economic and environmental impacts are discussed together with key implications for future development. Microwave valorization of AW to biofuels represents an economically viable cum environmentally-benign approach by virtue of (i) high availability of AW, (ii) scalable process, (iii) great potentiality for continuous operation, and (iv) thermochemical process with positive energy ratio. For continuous MP, the microwave heating distribution, products yield, and reactor design have not yet fully explored due to the limited understanding on microwave propagation pattern, materials handling, and varying feedstock compositions. The utilization of AW as biofuels feedstock offers several environmental advantages in terms of improved biomass utilization, enhanced carbon sequestration, and lower sulphur emission. The toxicity of bio-oil can be reduced by adding metal oxide catalysts (CaO, CuO, MgO, and NiO) to lessen its content of polycyclic aromatic hydrocarbons. The process of continuous MP can be optimized by coupling shaftless auger and multiple magnetron to improve the quality of the biofuel, and uniformity of microwave heating. It is envisaged that continuous conversion of AW to biofuels is a sustainable, low carbon footprint, and alternative energy generation route, provided that the appropriate catalyst, effective condenser, and self-purging condition are chosen.

Journal ArticleDOI
TL;DR: In this article, a system that looks at the four dimensions of economy, population, society, and environment, and then, using provincial-level panel data, employs a dynamic spatial panel model to empirically test the ecological effects of new type urbanization.
Abstract: The development of urbanization in China has changed from a traditional form of urbanization that focuses on the rate of growth to a new type of urbanization that stresses improvements in quality. To evaluate this new type of urbanization, this paper constructs a system that looks at the four dimensions of economy, population, society, and environment, and then, using provincial-level panel data, employs a dynamic spatial panel model to empirically test the ecological effects of the new type urbanization. The study finds that the new-type urbanization in China increased gradually from 2003 to 2017, focused on improvements to the ecological environment, and displayed obvious inter-provincial differences. Moreover, China's new-type urbanization has not only effectively reduced pollution emissions and improved energy efficiency but has also been significant in terms of its ecological effect. Moreover, economic urbanization, population urbanization, social urbanization and environmental urbanization exhibit the obvious ecological effects of “pollution reduction and efficiency improvement.” In the process of this new type of urbanization, both the government's “severe constraints” on pollution emissions and the active introduction of foreign capital are further important avenues that lead to achieving “pollution reduction and efficiency improvements.”

Journal ArticleDOI
TL;DR: A comprehensive survey of the existing DL-based approaches, which are developed for power forecasting of wind turbines and solar panels as well as electric power load forecasting, and discusses the datasets used to train and test the differentDL-based prediction models, enabling future researchers to identify appropriate datasets to use in their work.
Abstract: Microgrids have recently emerged as a building block for smart grids combining distributed renewable energy sources (RESs), energy storage devices, and load management methodologies. The intermittent nature of RESs brings several challenges to the smart microgrids, such as reliability, power quality, and balance between supply and demand. Thus, forecasting power generation from RESs, such as wind turbines and solar panels, is becoming essential for the efficient and perpetual operations of the power grid and it also helps in attaining optimal utilization of RESs. Energy demand forecasting is also an integral part of smart microgrids that helps in planning the power generation and energy trading with commercial grid. Machine learning (ML) and deep learning (DL) based models are promising solutions for predicting consumers’ demands and energy generations from RESs. In this context, this manuscript provides a comprehensive survey of the existing DL-based approaches, which are developed for power forecasting of wind turbines and solar panels as well as electric power load forecasting. It also discusses the datasets used to train and test the different DL-based prediction models, enabling future researchers to identify appropriate datasets to use in their work. Even though there are a few related surveys regarding energy management in smart grid applications, they are focused on a specific production application such as either solar or wind. Moreover, none of the surveys review the forecasting schemes for production and load side simultaneously. Finally, previous surveys do not consider the datasets used for forecasting despite their significance in DL-based forecasting approaches. Hence, our survey work is intrinsically different due to its data-centered view, along with presenting DL-based applications for load and energy generation forecasting in both residential and commercial sectors. The comparison of different DL approaches discussed in this manuscript reveals that the efficiency of such forecasting methods is highly dependent on the amount of the historical data and thus a large number of data storage devices and high processing power devices are required to deal with big data. Finally, this study raises several open research problems and opportunities in the area of renewable energy forecasting for smart microgrids.

Journal ArticleDOI
TL;DR: In this article, the authors comprehensively review the anaerobic digestion (AD) process utilising the organic fraction of municipal solid waste (OFMSW) substrate and find that the continuous digestion with thermophilic temperatures is the best condition for high solid AD process.
Abstract: This article aims to comprehensively review the anaerobic digestion (AD) process utilising the organic fraction of municipal solid waste (OFMSW) substrate. The AD of OFMSW has received considerable attention due to its significant energy and nutrient recovery as well as its greenhouse gas (GHG) mitigation potential. AD is a biological process involving treating and stabilising organic matter in the absence of oxygen accomplished by a consortium of microorganisms and occurs under hydrolysis, acidogenesis, acetogenesis, and methanogenesis phases. The hydrolysis phase is recognised as the primary rate-limiting step. Thus, exploring the ways to speed up the hydrolysis process will maximise biogas production. The key factors affecting the digestion efficiency include feedstock quality, pre-treatment process, design and selection of digestion process and process conditions including pH, temperature, carbon to nitrogen (C: N) ratio, organic loading rate and hydraulic retention time. The review reveals that solid-state anaerobic digestion (SSAD) is best suited for OFMSW due to its high solid concentration (>15%) and better process performance. The continuous digestion with thermophilic temperatures was found to be the best condition for high solid AD process. The plug flow and continuous stir tank reactors were the best performing options to control the biological conditions for the digestate post-treatment. Proper selection of the parameters for the whole process is crucial in ensuring process feasibility and economic sustainability of AD of OFMSW. The study revealed that the AD of OFMSW could play a significant role to mitigate waste and waste-related problems.

Journal ArticleDOI
TL;DR: In this article, the application of rice bran oil-based biofuels to diesel engines was completely analyzed and critically discussed based on engine performance, combustion, and emissions characteristics.
Abstract: The drastic rise in global warming and the fossil fuel consumption have resulted in destruction of the ecological balance, reduction of the environmental quality, and demotion of the sustainable development. The utilization of biofuels have been paid much attention to by researchers and policy makers due to its benefits and indisputable contributions to protect the living environment. Free fatty acid-rich rice bran oil which is unsuitable for food purposes could be a good candidate for biofuel production. Accordingly, rice bran oil-based biofuels (straight oil and its biodiesel) as promising alternative fuels to petrodiesel were reviewed in this article from the sources, components, and physicochemical perspectives. In addition, biodiesel production from rice bran oil using various methods and catalysts was thoroughly detailed. The oxidative stability of rice bran biodiesel as a function of the storage time was also discussed. The application of rice bran oil-based biofuels to diesel engines was completely analyzed and critically discussed based on engine performance, combustion, and emissions characteristics. The effects of using rice bran oil-based biofuels on the lubricating oil degradation, deposit formation, wear, and sound intensity of diesel engines were explained in detail. Finally, the economic aspects of using rice bran oil and its biodiesel as fuels were also assessed. As a conclusion, the blend containing 20% rice bran oil biodiesel and 80% petrodiesel fuel, both in volume, could be the most effective composition considering the techno-economic aspects of diesel engines; meanwhile the remaining blends appeared to be improper for the existing diesel engines.

Journal ArticleDOI
TL;DR: Capacity of the method in extracting a robust IHS for sources and ESSs are validated depending on optimal economic and environmental conditions, and the scheme obtains a robust structure for the IHS.
Abstract: Planning of an islanded hybrid system (IHS) with different sources and storages to supply clean, flexible, and highly reliable energy at consumption sites is of high importance. To this end, this paper presents the design of an IHS with a wind turbine, photovoltaic, diesel generator, and stationary (battery) and mobile (electrical vehicles) energy storage systems (ESS). The proposed method includes a multi-objective optimization to minimize the total cost of construction, maintenance, and operation of sources and ESSs within the IHS and the emission level of the system using two separate objective functions. The problem is subject to operational and planning constraints of sources and ESSs and power. Employing the Pareto optimization technique based on the e-constraint method forms a single-objective optimization problem for the proposed design. The problem involves uncertainties of load, renewable energy, and energy demand of mobile ESSs and has a nonlinear form. Adaptive robust optimization based on a hybrid meta-heuristic algorithm that utilizes a combination of the sine-cosine algorithm (SCA) and crow search algorithm (CSA) is proposed to achieve an optimal robust structure for the suggested scheme. In this scheme, operation model of the mobile storage systems in the IHS considering the uncertainties prediction errors and its model using HMA-based ARO besides adopting the HMA to achieve a unique optimal solution are among the novelties of this research. Eventually, considering the climate data and energy consumption of a region in Rafsanjan, Iran, capabilities of the method in extracting a robust IHS for sources and ESSs are validated depending on optimal economic and environmental conditions. The HMA succeeds to reach an optimal solution with an SD of 0.92% in the final response and this underlines its capability in achieving approximate conditions of unique responsiveness. The proposed scheme with proper planning and operation of sources and storages in the form of a HIS finds optimal values for economic and environmental conditions so that the difference between pollution and cost values from its minimum values at the compromise point is roughly 22%. For 17% uncertainty parameters prediction errors, the scheme obtains a robust structure for the IHS.

Journal ArticleDOI
TL;DR: Overall, exergoenvironmental analysis can offer more detailed information on the environmental consequences of each flow and component of bioenergy production plants, thereby diagnosing the breakthrough points for additional environmental improvements.
Abstract: Bioenergy systems are expected to expand over the coming decades due to their potential to address energy security and environmental pollution challenges. Nevertheless, any renewable energy project can only survive if approved environmentally superior to its conventional counterparts. Life cycle assessment (LCA) is an internationally standardized and validated methodology to evaluate and quantify the environmental impacts of bioenergy systems. However, due to its methodological scope, the LCA method measures only the environmental consequences of the target products of energy systems. The LCA approach can neither allocate the environmental impacts at the component level nor measure the environmental impacts of intermediate products. These challenges can be substantially resolved by systematically integrating the LCA approach with the thermodynamically-rooted exergy, offering a powerful environmental sustainability assessment tool known as “exergoenvironmental analysis“. Due to the unique methodological and conceptual characteristics of exergoenvironmental analysis in revealing the possibilities and trends for improvement, it has recently received increasing attention to mitigate the environmental impacts of bioenergy systems. Therefore, this review is aimed to thoroughly summarize and critically discuss the evaluation of sustainability aspects of bioenergy systems based on exergoenvironmental analysis. The pros and cons of using exergoenvironmental analysis in bioenergy research are also outlined to identify possible future directions for the field. Overall, exergoenvironmental analysis can offer more detailed information on the environmental consequences of each flow and component of bioenergy production plants, thereby diagnosing the breakthrough points for additional environmental improvements.

Journal ArticleDOI
TL;DR: In this article, the authors report the usage and advancement of heteroatom-doped graphene materials in various energy conversion and storage technologies, including supercapacitors, batteries, dye-sensitized solar cells, and hydrogen production from electrocatalytic water splitting.
Abstract: The demand for sustainable energy storage and production is vital and continues to grow with increasing human population. Energy utilization and environmental protection demand urgent attention in the development of energy devices, including the expansion and assessment of earth abundant and inexpensive materails. Recently, two-dimensional (2D) structured graphene has emerged as an outstanding energy material due to its excellent physicochemical properties, for example, high thermal and electrical conductivity, high surface area, strong mechanical strength, and an excellent chemical stability. However, pure graphene has a band gap of zero significantly limiting its application as a material. Among the various approaches used to alter the properties of graphene is doping with a heteroatom, which has been shown to be an efficient process in tailoring the properties of 2D-graphene. Heteroatom-doped graphene has several improved physicochemical properties, making graphene a favorable material for application in various fields. In this review, we report the usage and advancement of heteroatom-doped graphene materials in various energy conversion and storage technologies, including supercapacitors, batteries, dye-sensitized solar cells, and hydrogen production from electrocatalytic water splitting. Furthermore, we have also highlighted the recent developments made to date and systematically discuss physicochemical mechanisms, and the precise advantages obtained by the doping of heteroatoms. Finally, the challenges and future perspectives for heteroatom-doped graphene materials are outlined. The information provided in this review should be useful to any researchers involved in the field of graphene research for wide-ranging applications, and structural-oriented (morphology, structure, size and composition) research.

Journal ArticleDOI
TL;DR: This paper comprehensively summarized the advantages and disadvantages of various ESS technologies and presented several evaluation indicators for quantitative analysis, and identifies critical challenges and promising opportunities.
Abstract: The composition of worldwide energy consumption is undergoing tremendous changes due to the consumption of non-renewable fossil energy and emerging global warming issues. Renewable energy is now the focus of energy development to replace traditional fossil energy. Energy storage system (ESS) is playing a vital role in power system operations for smoothing the intermittency of renewable energy generation and enhancing the system stability. We divide ESS technologies into five categories, mainly covering their development history, performance characteristics, and advanced materials. Biomass storage and gas storage are also discussed, which are not considered in most reviews. After detailed research, the rapid development of each technology in recent years is introduced, and some representative research works are surveyed. We comprehensively summarized the advantages and disadvantages of various ESS technologies and presented several evaluation indicators for quantitative analysis. Hybrid ESS is also considered based on the complex market demand. Then, we investigate the applications of various ESS technologies as short-term, medium-term, and long-term storages in power systems, covering the power generation, transmission and distribution, and end-user. Finally, this paper reviews global developing trends, and identifies critical challenges and promising opportunities.

Journal ArticleDOI
TL;DR: A comprehensive review of recent progress and representative works on vibrational and thermal energy harvesters which play the dominant role in hybrid energy harvesting, and a variety of hybrid systems, including mechanisms, configurations, output performance and advantages are presented.
Abstract: The last decade has witnessed significant advances in energy harvesting technology for the realization of self-charging electronics and self-powered wireless sensor nodes (WSNs). To conquer the energy-insufficiency issue of a single energy harvester, hybrid energy harvesting systems have been proposed in recent years. Hybrid harvesting includes not only scavenging energy from multiple sources, but also converting energy into electricity by multiple types of transduction mechanisms. A reasonable hybridization of multiple energy conversion mechanisms not only improves the space utilization efficiency but can also boost the power output significantly. Given the continuously growing trend of hybrid energy harvesting technology, herein we present a comprehensive review of recent progress and representative works, especially focusing on vibrational and thermal energy harvesters which play the dominant role in hybrid energy harvesting. The working principles and typical configurations for piezoelectric, electromagnetic, triboelectric, thermoelectric and pyroelectric transduction effects are briefly introduced. On this basis, a variety of hybrid energy harvesting systems, including mechanisms, configurations, output performance and advantages, are elaborated. Comparisons and perspectives on the effectiveness of hybrid vibrational and thermal harvesters are provided. A variety of potential application prospects of the hybrid systems are discussed, including infrastructure health monitoring, industry condition monitoring, smart transportation, human healthcare monitoring, marine monitoring systems, and aerospace engineering, towards the future Internet-of-Things (IoT) era.

Journal ArticleDOI
TL;DR: In this article, the response of microalgae to different stresses and their effects on the quality and quantity of high-value products was investigated, and the prospects for future research dealing with wastewater treatment and biofuel production on downstream processing was also suggested.
Abstract: Rapidly growing industrialization and depletion of non-renewable fossil fuel has led to finding alternative viable renewable resources to meet the growing energy demand with less carbon dioxide generation. The modern world energy strategy is based on cost-effective and green alternatives and microalgae cultivation have potential to meet these criteria. Microalgae has been identified as a promising and sustainable alternative for treating wastewaters along the production of valuable products. Microalgae with a short life span, high growth rate and high CO2 utilization efficiency is one of viable techniques of renewable resources to produce biomass using nutrients in wastewater. At current, the technology and cost are the main factors that limit the application at industrial scale, which needs an ideal downstream process to minimize the production cost. The simultaneous use of microalgae for wastewater treatment and biofuel production has made these challenges practicable and economically viable. Microalgae efficiency for ammonia, phosphorus and heavy metal removal along with biofuel and bio-fertilizer production is reviewed. It is also aimed to focus on recent advances in cultivation of microalgae in wastewater, the response of microalgae to different stresses and their effects on the quality and quantity of high-value products was investigated. The prospects for future research dealing with wastewater treatment and biofuel production on downstream processing is also suggested.

Journal ArticleDOI
TL;DR: This is the first extensive review of the application of digital twin technology in smart electric vehicles, systematically classified into specific domains within the smart vehicle system such as autonomous navigation control, advanced driver assistance systems, vehicle health monitoring, battery management systems, Vehicle power electronics, and electrical power drive systems.
Abstract: Worldwide, transportation accounts for 18% of global carbon dioxide emissions (as of 2019). In order to battle the impending threat of climate change, consumers and industry must adopt sustainable transport that complies with the United Nations Sustainable Development Goals of increased energy efficiency and reduced greenhouse gas emissions. To fulfil these objectives, a new class of vehicles has recently emerged, smart electric vehicles, which is forecasted to reduce carbon dioxide emissions up to 43% as compared to diesel engine vehicles. However, to bring these vehicles to the mainstream, supporting architecture is needed to optimize them in a sustainable manner. One such novel architecture is Digital Twin Technology, which is a virtual mapping technology, extending from it, capable of investigating the lifecycle of multisystem bodies in a digital environment. In recent years, digital twin technology is becoming an underpinning area of research globally. As a result, novel individual research covering digital twin implementation on various aspects of smart vehicles has transpired in research and industrial studies, consequently allowing digital twin technology to evolve over the years. This work aims to bridge the gap between individual research to provide a comprehensive review from a technically-informed and academically neutral standpoint. Conceptual groundwork of digital twin technology is built systematically for the reader, to allow insight into its inception and evolution. The study sifts the digital twin domain for contributions in smart vehicle systems, exploring its potential and contemporaneous challenges to realization. The study then proceeds to review recent research and commercial projects for innovation within this domain. To the knowledge of the authors, this is the first extensive review of the application of digital twin technology in smart electric vehicles. The review has been systematically classified into specific domains within the smart vehicle system such as autonomous navigation control, advanced driver assistance systems, vehicle health monitoring, battery management systems, vehicle power electronics, and electrical power drive systems. An in-depth discussion of each vehicle subsystem is undertaken to present this review as an eclectic panorama of the smart vehicle system. This review further facilitates appreciation of the role of digital twin technology within each classification from a holistic technical perspective. Finally, the work ends with an inspection of the techno-socio-economic impact of digital twin technology that will revolutionize mainstream vehicle technology and the obstacles for further development.

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TL;DR: This survey shows that MPC is at the beginning of the application in microgrids and that it emerges as a competitive alternative to conventional methods in voltage regulation, frequency control, power flow management and economic operation optimization.
Abstract: The development of microgrids is an advantageous option for integrating rapidly growing renewable energies. However, the stochastic nature of renewable energies and variable power demand have created many challenges like unstable voltage/frequency and complicated power management and interaction with the utility grid. Recently, predictive control with its fast transient response and flexibility to accommodate different constraints has presented huge potentials in microgrid applications. This paper provides a comprehensive review of model predictive control (MPC) in individual and interconnected microgrids, including both converter-level and grid-level control strategies applied to three layers of the hierarchical control architecture. This survey shows that MPC is at the beginning of the application in microgrids and that it emerges as a competitive alternative to conventional methods in voltage regulation, frequency control, power flow management and economic operation optimization. Also, some of the most important trends in MPC development have been highlighted and discussed as future perspectives.

Journal ArticleDOI
TL;DR: The state-of-the-art research on OWT maintenance is reviewed, covering strategy selection, schedule optimization, onsite operations, repair, assessment criteria, recycling, and environmental concerns.
Abstract: Operations and maintenance of offshore wind turbines (OWTs) play an important role in the development of offshore wind farms. Compared with operations, maintenance is a critical element in the levelized cost of energy, given the practical constraints imposed by offshore operations and the relatively high costs. The effects of maintenance on the life cycle of an offshore wind farm are highly complex and uncertain. The selection of maintenance strategies influences the overall efficiency, profit margin, safety, and sustainability of offshore wind farms. For an offshore wind project, after a maintenance strategy is selected, schedule planning will be considered, which is an optimization problem. Onsite maintenance will involve complex marine operations whose efficiency and safety depend on practical factors. Moreover, negative environmental impacts due to offshore maintenance deserve attention. To address these issues, this paper reviews the state-of-the-art research on OWT maintenance, covering strategy selection, schedule optimization, onsite operations, repair, assessment criteria, recycling, and environmental concerns. Many methods are summarized and compared. Limitations in the research and shortcomings in industrial development of OWT operations and maintenance are described. Finally, promising areas are identified with regard to future studies of maintenance strategies.

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TL;DR: In this article, the authors investigated the impact of biomass energy consumption, education, and technological innovation on environmental quality by controlling for the role of economic growth and financial development in the function of environmental quality.
Abstract: Rising concern regarding traditional non-renewable energy consumption has led policymakers to explore the potential of economical renewable energy sources. In this regard, biomass energy has received considerable attention because previous studies have found mixed results regarding the effect of biomass energy on environmental quality. Together with modern technology, biomass energy may significantly influence environmental quality. This study investigates the impact of biomass energy consumption, education, and technological innovation on environmental quality by controlling for the role of economic growth and financial development in the function of environmental quality. Second-generation econometric methods were used to solve the issues of heterogeneity and cross-sectional dependence in the study variables. The Westerlund and Edgerton (2008) cointegration technique confirmed the existence of a long-run equilibrium among the variables in the presence of structural breaks. The panel quantile regression results indicate that biomass energy use and technological innovation reduce environmental quality. Similarly, economic growth increases carbon emissions in the environment. Education and financial development contribute to reduce carbon emissions.

Journal ArticleDOI
TL;DR: A multilayer design architecture for advanced battery management, which consists of three progressive layers, which aims at providing a comprehensive understanding of battery, and the application layer ensures a safe and efficient battery system through sufficient management.
Abstract: Lithium-ion batteries are promising energy storage devices for electric vehicles and renewable energy systems. However, due to complex electrochemical processes, potential safety issues, and inherent poor durability of lithium-ion batteries, it is essential to monitor and manage batteries safely and efficiently. This study reviews the development of battery management systems during the past periods and introduces a multilayer design architecture for advanced battery management, which consists of three progressive layers. The foundation layer focuses on the system physical basis and theoretical principle, the algorithm layer aims at providing a comprehensive understanding of battery, and the application layer ensures a safe and efficient battery system through sufficient management. A comprehensive overview of each layer is presented from both academic and engineering perspectives. Future trends in research and development of next-generation battery management are discussed. Based on data and intelligence, the next-generation battery management will achieve better safety, performance, and interconnectivity.

Journal ArticleDOI
TL;DR: All machine learning algorithms tested in this study can be used in the prediction of daily global solar radiation data with a high accuracy; however, the ANN algorithm is the best fitting algorithm among all algorithms.
Abstract: The prediction of global solar radiation for the regions is of great importance in terms of giving directions of solar energy conversion systems (design, modeling, and operation), selection of proper regions, and even future investment policies of the decision-makers. With this viewpoint, the objective of this paper is to predict daily global solar radiation data of four provinces (Kirklareli, Tokat, Nevsehir and Karaman) which have different solar radiation distribution in Turkey. In the study, four different machine learning algorithms (support vector machine (SVM), artificial neural network (ANN), kernel and nearest-neighbor (k-NN), and deep learning (DL)) are used. In the training of these algorithms, daily minimum and maximum ambient temperature, cloud cover, daily extraterrestrial solar radiation, day length and solar radiation of these provinces are used. The data is supplied from the Turkish State Meteorological Service and cover the last two years (01.01.2018–31.12.2019). To decide on the success of these algorithms, seven different statistical metrics (R2, RMSE, rRMSE, MBE, MABE, t-stat, and MAPE) are discussed in the study. The results shows that R2, MABE, and RMSE values of all algorithms are ranging from 0.855 to 0.936, from 1.870 to 2.328 MJ/m2, from 2.273 to 2.820 MJ/m2, respectively. At all cases, k-NN exhibited the worst result in terms of R2, RMSE, and MABE metrics. Of all the models, DL was the only model that exceeded the t-critic value. In conclusion, the present paper is reporting that all machine learning algorithms tested in this study can be used in the prediction of daily global solar radiation data with a high accuracy; however, the ANN algorithm is the best fitting algorithm among all algorithms. Then it is followed by DL, SVM and k-NN, respectively.

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TL;DR: In this paper, the authors provide a review of existing benefits and costs of different types of green roofs and green walls, including building scale benefits, urban scale benefits and life cycle costs, focusing on the identification of results variability and assessment of their average quantification.
Abstract: Greening the urban environment can be an important strategy to tackle the problems of urban densification and meet the United Nations Sustainable Development Goals. Green infrastructures, like green roofs and green walls, have multiple associated environmental, social and economic benefits that improve buildings performance and the urban environment. Yet, the implementation of green roofs and green walls is still limited, as these systems often have additional costs when compared to conventional solutions. Recent studies have been comparing these greening systems to other solutions, balancing the long-term benefits and costs. Also, there is significant research on green roofs and green walls benefits. Although, green roofs and green walls economic analyses don't include all benefits due to measuring difficulties. The associated uncertainty regarding the quantification of the benefit makes it difficult to compare the research outcomes. This paper aims to provide a research review of existing benefits and costs of different types of green roofs and green walls. These were divided between building scale benefits, urban scale benefits and life cycle costs, focusing on the identification of results variability and assessment of their average quantification. The analysis shows that in general, there are few data regarding intangible benefits, as the promotion of quality of life and well-being. Also, there are still few studies quantifying green walls benefits and costs. High variability in data is mostly related to the different characteristics of systems, buildings envelope, surrounding environment and local weather conditions.

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TL;DR: It is observed that the accurate energy demand forecast provided by k CNN-LSTM due to its ability to learn the spatio-temporal dependencies in the energy consumption data makes it a suitable deep learning model for energy consumption forecast problems.
Abstract: Increasing global building energy demand, with the related economic and environmental impact, upsurges the need for the design of reliable energy demand forecast models. This work presents k CNN-LSTM, a deep learning framework that operates on the energy consumption data recorded at predefined intervals to provide accurate building energy consumption forecasts. k CNN-LSTM employs (i) k − means clustering – to perform cluster analysis to understand the energy consumption pattern/trend; (ii) Convolutional Neural Networks (CNN) – to extract complex features with non-linear interactions that affect energy consumption; and (iii) Long Short Term Memory (LSTM) neural networks – to handle long-term dependencies through modeling temporal information in the time series data. The efficiency and applicability of k CNN-LSTM were demonstrated using a real time building energy consumption data acquired from a four-storeyed building in IIT-Bombay, India. The performance of k CNN-LSTM was compared with the k -means variant of the state-of-the-art energy demand forecast models in terms of well-known quality metrics. It is also observed that the accurate energy demand forecast provided by k CNN-LSTM due to its ability to learn the spatio-temporal dependencies in the energy consumption data makes it a suitable deep learning model for energy consumption forecast problems.

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TL;DR: In this article, a review of post-combustion capture techniques, including thermal or pressure swing principles, adsorption or absorption, and electrical swing or membrane separation processes, is presented.
Abstract: CCS, Carbon Capture and Storage, is considered a promising technology to abate CO2 emissions from point sources. The present review deals with the principle of post-combustion capture techniques, including thermal or pressure swing principles, adsorption or absorption, and electrical swing or membrane separation processes. Opportunities and challenges are assessed. In the first section of absorption processes, several commercial technologies are compared and complemented by the aqueous or chilled ammonia (NH3) process, and a dual or strong alkali absorption. The second section deals with adsorption where fixed beds, circulating fluidized beds and counter-current bed configurations will be discussed, with particular focus on the different adsorbents ranging from zeolites or activated carbon, to more complex amine-functionalized adsorbents, nanotubes or metal organic frameworks (MOFs), and alkali-promoted oxides. Thirdly, membrane processes will be analysed. The review will finally summarize challenges and opportunities. Several research groups confirmed that absorption is the most mature post-combustion capture process: among the assessment of post-combustion CCS, 57% apply absorption, 14% rely on adsorption, 8% use membranes, and 21% apply mineralization or bio-fixation. This conclusion was in-line with expectations since absorption gas separation has been largely applied in various petrochemical industries. All other systems need further development prior to large scale application.