Applied Energy最新文献

{"title":"The future of offshore wind power production: Wake and climate impacts","authors":"Simon C. Warder,&nbsp;Matthew D. Piggott","doi":"10.1016/j.apenergy.2024.124956","DOIUrl":"10.1016/j.apenergy.2024.124956","url":null,"abstract":"<div><div>Rapid deployment of offshore wind is expected within the coming decades to help meet climate goals. With offshore wind turbine lifetimes of 25–30 years, and new offshore leases spanning 60 years, it is vital to consider long-term changes in potential wind power resource at the farm planning stage. Such changes may arise from multiple sources, including climate change, and increasing wake-induced power losses. In this work, we investigate and compare these two sources of long-term change in wind power, for a case study consisting of 21 wind farms within the German Bight. Consistent with previous studies, we find a small but significant reduction in wind resource due to climate change by the end of the 21st century under the high-emission RCP8.5 scenario, compared with a historical period, with a mean power reduction (over an ensemble of seven climate models) of 2.1%. To assess the impact of wake-induced losses due to increasingly dense farm build-out, we model wakes within the German Bight region using an engineering wake model, under various stages of (planned) build-out corresponding to the years 2010–2027. By identifying clusters of wind farms, we decompose wake effects into long-range (inter-cluster), medium-range (intra-cluster) and short-range (intra-farm) effects. Inter-cluster wake-induced losses increase from 0 for the 2010 scenario to 2.5% for the 2027 scenario, with intra-cluster losses also increasing from 0 to 4.3%. Intra-farm losses are relatively constant, at around 13%. While the evolution of wake effects therefore outweighs the climate effect, and impacts over a shorter timescale, both factors are significant. We also find evidence of an interaction between the climate and wake effects. Both climate change and evolving wake effects must therefore be considered within resource assessment and wind farm planning.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 124956"},"PeriodicalIF":10.1,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determination of trade-offs between 2G bioethanol production yields and pretreatment costs for industrially steam exploded woody biomass","authors":"Edwige Audibert ,&nbsp;Juliette Floret ,&nbsp;Adriana Quintero ,&nbsp;Frédéric Martel ,&nbsp;Caroline Rémond ,&nbsp;Gabriel Paës","doi":"10.1016/j.apenergy.2024.125028","DOIUrl":"10.1016/j.apenergy.2024.125028","url":null,"abstract":"<div><div>Lignocellulosic biomass, including wood, can be transformed into bioethanol using steam explosion as pretreatment to improve saccharification and fermentation steps. Pretreatment is however the most expensive part of the process in terms of CAPEX and OPEX and requires to be optimized. In order to evaluate the link between pretreatment efficiency and cost, three contrasted wood species (oak, poplar and spruce) were pretreated with continuous steam explosion at pilot-scale following full factorial designs. Response surfaces obtained were combined with an economic assessment to determine trade-offs aiming at maximizing both fermentable sugars released during the enzymatic hydrolysis step and bioethanol yield during the fermentation step as well as minimizing costs of pretreatment in an industrial context. Results showed that bioethanol yields were highly dependent on wood species and that high severities of pretreatment were not the most relevant to apply. Optimal conditions of pretreatment corresponding to 70 % and 48 % of bioethanol producible from oak and poplar, respectively, were defined. The desirability function that has been modelled thus helps designing adapted pretreatment conditions regarding bioethanol production and process cost.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 125028"},"PeriodicalIF":10.1,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Smart energy management: Process structure-based hybrid neural networks for optimal scheduling and economic predictive control in integrated systems","authors":"Long Wu ,&nbsp;Xunyuan Yin ,&nbsp;Lei Pan ,&nbsp;Jinfeng Liu","doi":"10.1016/j.apenergy.2024.124965","DOIUrl":"10.1016/j.apenergy.2024.124965","url":null,"abstract":"<div><div>Integrated energy systems (IESs) are complex prosumers consisting of diverse operating units spanning multiple domains. The tight integration of these units results in varied dynamic characteristics and intricate nonlinear process interactions, making detailed dynamic modeling and successful operational optimization challenging. To address these concerns, we propose a process structure-based hybrid time-series neural network (NN) surrogate to predict the dynamic performance of IESs across multiple time scales. This neural network-based modeling approach develops time-series multi-layer perceptrons (MLPs) for the operating units and integrates them with prior process knowledge about system structure and fundamental dynamics. This integration forms three hybrid NNs – long-term, slow, and fast MLPs – that predict the entire system dynamics across multiple time scales. Leveraging these MLPs, we design an NN-based scheduler and an NN-based economic model predictive control (NEMPC) framework to meet global operational requirements: rapid electrical power responsiveness to operators’ requests, adequate cooling supply to customers, and increased system profitability, while addressing the dynamic time-scale multiplicity present in IESs. The proposed day-ahead scheduler is formulated using the ReLU network-based MLP, which effectively represents IES performance under a broad range of conditions from a long-term perspective. The scheduler is then exactly recast into a mixed-integer linear programming problem for efficient evaluation. The real-time NEMPC, based on slow and fast MLPs, comprises two sequential distributed control agents: a slow NEMPC for the cooling-dominant subsystem with slower transient responses and a fast NEMPC for the power-dominant subsystem with faster responses. These agents collaborate in the decision-making process to achieve dynamic synergy in real time while reducing computational costs. Extensive simulations demonstrate that the developed scheduler and NEMPC schemes outperform their respective benchmark scheduler and controller by about 25% and 40%. Together, they enhance overall system performance by over 70% compared to benchmark approaches.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 124965"},"PeriodicalIF":10.1,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lightweight energy harvesting backpack achieved with a slingshot-inspired flexible accelerator","authors":"Hongyuan Zhao,&nbsp;Kangqi Fan,&nbsp;Shizhong Zhao,&nbsp;Shuxin Wu,&nbsp;Xuan Zhang,&nbsp;Zehao Hou","doi":"10.1016/j.apenergy.2024.124993","DOIUrl":"10.1016/j.apenergy.2024.124993","url":null,"abstract":"<div><div>The energy harvesting backpack (EHB) has been recognized as a sustainable power source for wearable electronics, but its daily applications have been hindered by the rigid and heavy frame and accelerator structure. Therefore, a flexible and lightweight design strategy for EHBs is proposed based on a slingshot-inspired flexible accelerator (FA). The proposed FA accomplishes the speed acceleration for harvester actuation by rapidly releasing accumulated elastic potential energy. Then, a 1.9 kg electromagnetic EHB with the FA (FA-EEHB) is modeled, tested, and applied to wearable electronics. Actuated by 3.0 Hz ultralow-frequency vibrations, the FA-EEHB with a 2.0 kg payload can generate 215.1 mW output power, which is over eight times the 26.6 mW output of an EHB without FA. With a small payload of 1.0 kg, the FA-EEHB can work well over a large traveling speed range from 4 km/h to 9 km/h. The application experiment of the FA-EEHB was conducted at 5 km/h traveling speed with a 2.0 kg payload to demonstrate the ability to continuously power a lamp, charge a smartphone, and sustain a tracking and positioning system. This study provides a distinctive strategy for the flexible and lightweight design of EHBs with small payloads.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"379 ","pages":"Article 124993"},"PeriodicalIF":10.1,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reversing climate policy stereotypes: Evidence from an energy-dependent region and China's major economic circles","authors":"Jinbo Zhang ,&nbsp;Haoyun Meng ,&nbsp;Liu Chen ,&nbsp;Yang Zhang ,&nbsp;Zhenghui Fu ,&nbsp;Yulei Xie ,&nbsp;Huaicheng Guo","doi":"10.1016/j.apenergy.2024.125026","DOIUrl":"10.1016/j.apenergy.2024.125026","url":null,"abstract":"<div><div>Achieving decarbonization and industrial transformation in typical energy-dependent regions is a crucial step in mitigating regional climate change. This study constructed a factorial carbon policy equilibrium effect model (FCEE) that integrated input–output analysis, a computable general equilibrium model, factorial analysis, multi-regional input–output, and ecological network analysis. This work explored the internal impact of a composite carbon tax policy that considered the endogenous driving forces of the socioeconomic system on Shanxi Province, a typical energy-dependent region in China, as well as the cascading external effects on China's major economic circles. A significant interaction was found between carbon tax policy, production efficiency progress, and emission efficiency progress, confirming advantage of the composite policy in terms of the environmental–economic benefits. In contrast to common stereotypes, the composite climate policy will promote the clean transformation of the energy structure and gross domestic product growth, and water scarcity in Shanxi Province will be alleviated under the energy–water nexus mechanism. Relying on complex cross-regional networks, China's economic inequality will be indirectly eased. The economic driving forces of the Yangtze River, Chengdu-Chongqing economic circles, and Shanxi Province will be strengthened, promoting system stability and sustainability. It is recommended that Shanxi Province implement a moderate carbon tax policy while improving production efficiency; the intensity of emissions technology reform can be flexibly adjusted according to actual needs. This study provides evidence to support the implementation of climate policy, which is of great significance for other similar regions looking to solve the dilemma of sustainable development.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 125026"},"PeriodicalIF":10.1,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metal-organic framework nanocomposites: Engineering and morphological advances for photocatalytic CO2 conversion into fuel","authors":"Manzoore Elahi M. Soudagar ,&nbsp;Deepali Marghade ,&nbsp;Sagar Shelare ,&nbsp;D. Karunanidhi ,&nbsp;Chander Prakash ,&nbsp;T.M. Yunus Khan ,&nbsp;Weiping Cao","doi":"10.1016/j.apenergy.2024.124977","DOIUrl":"10.1016/j.apenergy.2024.124977","url":null,"abstract":"<div><div>Global industrialization and fossil fuel consumption have elevated CO₂ levels and caused global warming, causing catastrophes worldwide. Given this reality, removing CO₂ from the atmosphere and transforming acquired CO₂ into value-added resources like fuels and chemical feedstock is imperative to build a circular economy. The use of MOFs and their derivatives in CO₂ photocatalytic conversion is eco-friendly and could alleviate future fuel shortages. Modern photocatalysts MOFs, consist of hybrid organic ligand, and inorganic nodal metals with customizable morphology. MOF flexible rational design allows several active sites to be added to a framework, generating a complex photocatalytic system. The first half critically studied morphology, photocatalytic reduction mechanism, pristine MOF applications, and MOF modification/functionalization for photocatalytic reduction of CO₂. Their catalytic performance is currently insufficient for industrial usage because to poor light-harvesting and electron-hole separation. Researchers created MOF nanocomposites with many benefits by adding guest compounds. Morphological alterations, sensitization with polymers, plasmonic metals, and heterojunction generation with type I, type II, type III, and <em>Z</em>-scheme for MOF nanocomposites represent the current status of this large and significant research topic in the second half of paper. We presented the progress in photocatalytic CO₂ reduction into fuels and chemical feedstock using MOF nanocomposites. This review discussed MOF nanocomposites' photocatalytic merits and cons and stimulate the advancement of more efficient and broadly applicable photocatalysts. The broad range of work assembled in this review will be very valuable to a wide spectrum of research on worldwide CO₂ abatement.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"379 ","pages":"Article 124977"},"PeriodicalIF":10.1,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributed voltage control for multi-feeder distribution networks considering transmission network voltage fluctuation based on robust deep reinforcement learning","authors":"Zhi Wu ,&nbsp;Yiqi Li ,&nbsp;Xiao Zhang ,&nbsp;Shu Zheng ,&nbsp;Jingtao Zhao","doi":"10.1016/j.apenergy.2024.124984","DOIUrl":"10.1016/j.apenergy.2024.124984","url":null,"abstract":"<div><div>In the multi-feeder distribution network, the power balance between photovoltaics generations and load demands across regions is more complex. To solve the above problems, this paper proposes a multi-agent distributed voltage control strategy based on robust deep reinforcement learning to reduce voltage deviation. The whole multi-feeder distribution network is divided into a main agent and several sub-agents, and a multi-agent distributed voltage control model considering the transmission network voltage fluctuations and the corresponding power fluctuations is established. Based on the information uploaded by sub-agents, the main agent models the uncertainty of the transmission network voltage fluctuations and the corresponding power fluctuations as a disturbance to the state, and a RDRL method is employed to determine the tap position of on-load tap changer. Furtherly, each sub-agent uses the second-order cone relaxation technique to adjust the reactive power outputs of the inverters on each feeder. The effectiveness of the proposed method has been verified in two real-world multi-feeder systems. The results show that the proposed method can achieve millisecond-level decision-making, with a voltage deviation only 1.28 % higher than the global optimal results, achieving near-optimal control. The proposed method also demonstrates robustness in handling transmission network uncertainties and partial measurement loss.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"379 ","pages":"Article 124984"},"PeriodicalIF":10.1,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective hierarchical energy management strategy for fuel cell/battery hybrid power ships","authors":"Hanyou Liu ,&nbsp;Ailong Fan ,&nbsp;Yongping Li ,&nbsp;Richard Bucknall ,&nbsp;Nikola Vladimir","doi":"10.1016/j.apenergy.2024.124981","DOIUrl":"10.1016/j.apenergy.2024.124981","url":null,"abstract":"<div><div>The energy management strategy and the local controller in the ship energy management system are interconnected, impacting the performance of the hybrid propulsion system. To achieve the efficient operation of the hydrogen fuel cell (FC) and battery hybrid power system, based on the modelling and analysis of the hybrid power system, a nonlinear model predictive control (NMPC) based energy management strategy is proposed, and a dynamic virtual impedance droop controller and a classical proportional-integral (PI) controller are designed as local controllers. By simulating the designed random load conditions, pulse load conditions, and actual sailing conditions using hardware-in-the-loop (HiLs) technology, six different energy management strategies and their comprehensive performance with local controllers are compared and analysed. Comparing performance in terms of energy consumption, operating pressure, control accuracy, real-time performance, and robustness, it has been proven that the energy management strategy based on NMPC, coupled with a PI controller, is superior to other strategies overall. It can balance hydrogen consumption and the stable operation of the hybrid power system. Compared to existing energy management strategies, the proposed NMPC+PI strategy can reduce hydrogen consumption by 7.00 % and 40.29 %, and FC operating pressure by 44.96 % and 49.88 %, respectively, under both designed navigation conditions and actual navigation conditions.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"379 ","pages":"Article 124981"},"PeriodicalIF":10.1,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A cellular automata modelling approach for grain growth topological evolution process of ternary cathode materials combined with deep neural networks","authors":"Tianyi Li ,&nbsp;Ning Chen ,&nbsp;Chunhua Yang ,&nbsp;Hongzhen Liu ,&nbsp;Biao Qi ,&nbsp;Weihua Gui ,&nbsp;Zhixing Wang ,&nbsp;Jiexi Wang","doi":"10.1016/j.apenergy.2024.124980","DOIUrl":"10.1016/j.apenergy.2024.124980","url":null,"abstract":"<div><div>Ternary cathode materials are pivotal in high-performance battery technologies, with grain size influencing their electrochemical performance. However, the absence of real-time grain size inspection during material preparation poses challenges in maintaining the consistent quality of ternary cathode materials. To address this, this paper proposes a novel method employing cell automata to model the topological evolution of grain growth in these materials, integrated with deep neural networks (DNN). The grain growth process is divided into two stages: heating and constant temperature. In the heating stage, varying heating rates and plateau temperatures serve as DNN inputs, yielding the primary grain distribution for the cell automata model in the constant temperature stage. Based on cell automata, the grain growth model links the grain growth rate to the grain size distribution in the constant temperature stage. A surface energy constraint rule, based on local curvature and grain boundary surface tension, governs growth rates. The grain boundary growth ratio is also used to create a grain ID transition variable, dictating grain ID conversion in the model. This approach accurately simulates the dynamic evolution of polycrystalline grain size and morphology. Simulation results show that this method effectively models grain growth in ternary cathode materials, offering insights for optimising the sintering process and improving material quality.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"379 ","pages":"Article 124980"},"PeriodicalIF":10.1,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling and energy management of hangar thermo-electrical microgrid for electric plane charging considering multiple zones and resources","authors":"Pablo Verdugo,&nbsp;Claudio Cañizares,&nbsp;Mehrdad Pirnia","doi":"10.1016/j.apenergy.2024.124951","DOIUrl":"10.1016/j.apenergy.2024.124951","url":null,"abstract":"<div><div>Achieving net zero goals by 2050 is driving an energy transition towards clean electrical energy. Consequently, many initiatives have been proposed aiming to reduce carbon emissions in the building and transportation sectors, focusing, for instance, on the implementation of efficient heating and cooling systems based on heat pumps and the use of electric planes. Microgrids can effectively integrate thermal and electrical energy resources and loads to satisfy customer demands while providing technical, economic, and environmental benefits. Thus, this paper proposes the implementation of a model of a hangar microgrid and its Energy Management System to optimize the dispatch of resources of such thermo-electrical airport grid, using a Model Predictive Control approach to address uncertainties, and including a detailed building thermal model, heat pump modeling for the heating and cooling systems, and battery degradation. The proposed mathematical model of the Energy Management System is applied to a model of a microgrid being developed for a hangar at the Waterloo Wellington Flight Centre in Ontario, Canada, taking into account the specific characteristics of the microgrid’s components, the expected energy consumption of the equipment and the electric plane used for pilot training based on field measurements, and multi-room temperature control requirements, seeking to ensure a reliable and cost-effective operation, while considering the occupants’ comfort in different spaces. The results indicate that the proposed Energy Management System model, featuring multi-room temperature control through multiple thermal resources, can achieve significant savings in operational costs and CO2 emissions compared to a scenario where the microgrid is not deployed and another where a single-room building thermal model with a single heat pump is included.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"379 ","pages":"Article 124951"},"PeriodicalIF":10.1,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}