In Pakistan,the solar analogue has been addressed but its surface geographical parameterization has given least attention.Inappropriate density of stations and their spatial coverage particularly in difficult peripher...In Pakistan,the solar analogue has been addressed but its surface geographical parameterization has given least attention.Inappropriate density of stations and their spatial coverage particularly in difficult peripheral national territories,little or no solar radiation data,non-satisfactory sunshine hours data,and low quality of ground observed cloud cover data create a situation in which the spatial modeling of Extraterrestrial Solar Radiation(ESR) and its ground parameterization got sufficient scope.The Digital Elevation Model (DEM) input into Geographic Information System (GIS) is a compatible tool to demonstrate the spatial distribution of ESR over the rugged terrains of the study domain.For the first time,distributed modeling of ESR is done over the rugged terrains of Pakistan,based on DEM and ArcGIS..Results clearly depict that the complex landforms profoundly disrupt the zonal distribution of ESR in Pakistan.The screening impact of topography is higher on spatial distribution of ESR in winter and considerably low in summer.The combined effect of topography and latitude is obvious.Hence,the model was further testified by plotting Rb (ratio of ESR quantity over rugged terrain against plane surface) against azimuth at different latitudes with different angled slopes.The results clearly support the strong screening effect of rugged terrain through out the country especially in Himalayas,Karakoram and Hindukush (HKH),western border mountains and Balochistan Plateau.This model can be instrumental as baseline geospatial information for scientific investigations in Pakistan,where substantial fraction of national population is living in mountainous regions.展开更多
Due to the influences of local topographical factors and terrain inter-shielding, calculation of direct solar radiation （DSR） quantity of rugged terrain is very complex. Based on digital elevation model （DEM） data...Due to the influences of local topographical factors and terrain inter-shielding, calculation of direct solar radiation （DSR） quantity of rugged terrain is very complex. Based on digital elevation model （DEM） data and meteorological observations, a distributed model for calculating DSR over rugged terrain is developed. This model gives an all-sided consideration on factors influencing th a resolution of 1 km × 1 km for thDSR. Using the developed model, normals of annual DSR quantity wie Yellow River Basin was generated, with DEM data as the general characterization of terrain. Characteristics of DSR quantity influenced by geographic and topographic factors over rugged terrain were analyzed thoroughly. Results suggest that： influenced by local topographic factors, i.e. azimuth, slope and so on, and annual DSR quantity over mountainous area has a clear spatial difference; annual DSR quantity of sunny slope （or southern slope） of mountains is obviously larger than that of shady slope （or northern slope）. The calculated DSR quantity of the Yellow River Basin is provided in the same way as other kinds of spatial information and can be employed as basic geographic data for relevant studies as well.展开更多
Characterized by special morphologic,geographic,hydrologic,and societal behaviors,the water resources management of the Mediterranean catchment often shows a higher level of complexity including security issues of wat...Characterized by special morphologic,geographic,hydrologic,and societal behaviors,the water resources management of the Mediterranean catchment often shows a higher level of complexity including security issues of water supply,inundation risks,and environment management under the perspective of climate change.To have a comprehensive understanding of the Mediterranean water-cycle system,a deterministic distributed hydrologic modeling approach has been developed and presented in this study based on an application in the Var catchment(2800 km^(2))located at the French Mediterranean region.A 1D and 2D coupled model of MIKE SHE and MIKE 11 has been set up under a series of hypotheses to represent the whole hydrologic and hydrodynamic processes including rainfall-runoff,snow-melting,channel flow,overland flow,and the water exchange between land surface and unsaturated/saturated zones.The developed model was first calibrated with 4 years daily records from 2008 to 2011,then to be validated and further run within hourly time interval to produce detailed representation of the catchment water-cycle from 2012 to 2014.The deterministic distributed modeling approach presented in this study is able to represent its complicated water-cycle and used for supporting the decision‐making process of the water resources management of the catchment.展开更多
Biological invasions,driven mainly by human activities,pose significant threats to global ecosystems and economies,with fungi and fungal-like oomycetes playing a pivotal role.Ink disease,caused by Phytophthora cinnamo...Biological invasions,driven mainly by human activities,pose significant threats to global ecosystems and economies,with fungi and fungal-like oomycetes playing a pivotal role.Ink disease,caused by Phytophthora cinnamomi and P.×cambivora,is a growing concern for sweet chestnut stands(Castanea sativa)in Europe.Since both pathogens are thermophilic organisms,ongoing climate change will likely exacerbate their impact.In this study,we applied species distribution modeling techniques to identify poten-tial substitutive species for sweet chestnut in the light of future climate scenarios SSP126 and SSP370 in southern Switzerland.Using the presence-only machine learning algorithm MaxEnt and leveraging occurrence data from the global dataset GBIF,we delineated the current and projected(2070-2100)distribution of 28 tree species.Several exotic species emerged as valuable alternatives to sweet chestnut,although careful consideration of all potential ecological consequences is required.We also identified several native tree species as promising substitutes,offering ecological benefits and potential adaptability to climatic conditions.Since species diversification fosters forest resilience,we also determined communities of alternative species that can be grown together.Our findings represent a valuable deci-sion tool for forest managers confronted with the challenges posed by ink disease and climate change.Given that,even in absence of disease,sweet chestnut is not a future-proof tree species in the study region,the identified species could offer a pathway toward resilient and sustainable forests within the entire chestnut belt.展开更多
A chance-constrained energy dispatch model based on the distributed stochastic model predictive control(DSMPC)approach for an islanded multi-microgrid system is proposed.An ambiguity set considering the inherent uncer...A chance-constrained energy dispatch model based on the distributed stochastic model predictive control(DSMPC)approach for an islanded multi-microgrid system is proposed.An ambiguity set considering the inherent uncertainties of renewable energy sources(RESs)is constructed without requiring the full distribution knowledge of the uncertainties.The power balance chance constraint is reformulated within the framework of the distributionally robust optimization(DRO)approach.With the exchange of information and energy flow,each microgrid can achieve its local supply-demand balance.Furthermore,the closed-loop stability and recursive feasibility of the proposed algorithm are proved.The comparative results with other DSMPC methods show that a trade-off between robustness and economy can be achieved.展开更多
Combustion kinetics of the hydrochar was investigated using a multi-Gaussian-distributed activation energy model(DAEM)to ex-pand the knowledge on the combustion mechanisms.The results demonstrated that the kinetic par...Combustion kinetics of the hydrochar was investigated using a multi-Gaussian-distributed activation energy model(DAEM)to ex-pand the knowledge on the combustion mechanisms.The results demonstrated that the kinetic parameters calculated by the multi-Gaussian-DAEM accurately represented the experimental conversion rate curves.Overall,the feedstock combustion could be divided into four stages:the decomposition of hemicellulose,cellulose,lignin,and char combustion.The hydrochar combustion could in turn be divided into three stages:the combustion of cellulose,lignin,and char.The mean activation energy ranges obtained for the cellulose,lignin,and char were 273.7-292.8,315.1-334.5,and 354.4-370 kJ/mol,respectively,with the standard deviations of 2.1-23.1,9.5-27.4,and 12.1-22.9 kJ/mol,re-spectively.The cellulose and lignin contents first increased and then decreased with increasing hydrothermal carbonization(HTC)temperature,while the mass fraction of char gradually increased.展开更多
Lithium ion battery has typical character of distributed parameter system, and can be described precisely by partial differential equations and multi-physics theory because lithium ion battery is a complicated electro...Lithium ion battery has typical character of distributed parameter system, and can be described precisely by partial differential equations and multi-physics theory because lithium ion battery is a complicated electrochemical energy storage system. A novel failure prediction modeling method of lithium ion battery based on distributed parameter estimation and single particle model is proposed in this work. Lithium ion concentration in the anode of lithium ion battery is an unmeasurable distributed variable. Failure prediction system can estimate lithium ion concentration online, track the failure residual which is the difference between the estimated value and the ideal value. The precaution signal will be triggered when the failure residual is beyond the predefined failure precaution threshold, and the failure countdown prediction module will be activated. The remaining time of the severe failure threshold can be estimated by the failure countdown prediction module according to the changing rate of the failure residual. A simulation example verifies that lithium ion concentration in the anode of lithium ion battery can be estimated exactly and effectively by the failure prediction model. The precaution signal can be triggered reliably, and the remaining time of the severe failure can be forecasted accurately by the failure countdown prediction module.展开更多
In this paper,distributed model predictive control(DMPC) for island DC micro-grids(MG) with wind/photovoltaic(PV)/battery power is proposed,which coordinates all distributed generations(DG) to stabilize the bus voltag...In this paper,distributed model predictive control(DMPC) for island DC micro-grids(MG) with wind/photovoltaic(PV)/battery power is proposed,which coordinates all distributed generations(DG) to stabilize the bus voltage together with the insurance of having computational efficiency under a real-time requirement.Based on the feedback of the bus voltage,the deviation of the current is dispatched to each DG according to cost over the prediction horizon.Moreover,to avoid the excessive fluctuation of the battery power,both the discharge-charge switching times and costs are considered in the model predictive control(MPC) optimization problems.A Lyapunov constraint with a time-varying steady-state is designed in each local MPC to guarantee the stabilization of the entire system.The voltage stabilization of the MG is achieved by this strategy with the cooperation of DGs.The numeric results of applying the proposed method to a MG of the Shanghai Power Supply Company shows the effectiveness of the distributed economic MPC.展开更多
The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calcula...The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches.展开更多
The Qilian Mountains, a national key ecological function zone in Western China, play a pivotal role in ecosystem services. However, the distribution of its dominant tree species, Picea crassifolia (Qinghai spruce), ha...The Qilian Mountains, a national key ecological function zone in Western China, play a pivotal role in ecosystem services. However, the distribution of its dominant tree species, Picea crassifolia (Qinghai spruce), has decreased dramatically in the past decades due to climate change and human activity, which may have influenced its ecological functions. To restore its ecological functions, reasonable reforestation is the key measure. Many previous efforts have predicted the potential distribution of Picea crassifolia, which provides guidance on regional reforestation policy. However, all of them were performed at low spatial resolution, thus ignoring the natural characteristics of the patchy distribution of Picea crassifolia. Here, we modeled the distribution of Picea crassifolia with species distribution models at high spatial resolutions. For many models, the area under the receiver operating characteristic curve (AUC) is larger than 0.9, suggesting their excellent precision. The AUC of models at 30 m is higher than that of models at 90 m, and the current potential distribution of Picea crassifolia is more closely aligned with its actual distribution at 30 m, demonstrating that finer data resolution improves model performance. Besides, for models at 90 m resolution, annual precipitation (Bio12) played the paramount influence on the distribution of Picea crassifolia, while the aspect became the most important one at 30 m, indicating the crucial role of finer topographic data in modeling species with patchy distribution. The current distribution of Picea crassifolia was concentrated in the northern and central parts of the study area, and this pattern will be maintained under future scenarios, although some habitat loss in the central parts and gain in the eastern regions is expected owing to increasing temperatures and precipitation. Our findings can guide protective and restoration strategies for the Qilian Mountains, which would benefit regional ecological balance.展开更多
Expanding photovoltaic(PV)resources in rural-grid areas is an essential means to augment the share of solar energy in the energy landscape,aligning with the“carbon peaking and carbon neutrality”objectives.However,ru...Expanding photovoltaic(PV)resources in rural-grid areas is an essential means to augment the share of solar energy in the energy landscape,aligning with the“carbon peaking and carbon neutrality”objectives.However,rural power grids often lack digitalization;thus,the load distribution within these areas is not fully known.This hinders the calculation of the available PV capacity and deduction of node voltages.This study proposes a load-distribution modeling approach based on remote-sensing image recognition in pursuit of a scientific framework for developing distributed PV resources in rural grid areas.First,houses in remote-sensing images are accurately recognized using deep-learning techniques based on the YOLOv5 model.The distribution of the houses is then used to estimate the load distribution in the grid area.Next,equally spaced and clustered distribution models are used to adaptively determine the location of the nodes and load power in the distribution lines.Finally,by calculating the connectivity matrix of the nodes,a minimum spanning tree is extracted,the topology of the network is constructed,and the node parameters of the load-distribution model are calculated.The proposed scheme is implemented in a software package and its efficacy is demonstrated by analyzing typical remote-sensing images of rural grid areas.The results underscore the ability of the proposed approach to effectively discern the distribution-line structure and compute the node parameters,thereby offering vital support for determining PV access capability.展开更多
In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory...In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the aim to put in light the main f eatures of the proposed approach. Moreover, it is important to underline that in different operating scenarios the proposed reinforcement learning scheme is capable of significantly reducing traffic congestion phenomena when compared with well-reputed competitors.展开更多
A distributed model predictive control(DMPC)method based on robust control barrier function(RCBF)is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed env...A distributed model predictive control(DMPC)method based on robust control barrier function(RCBF)is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed environment.The first step is to analyze the safety requirements of the system during safe formation and categorize them into collision avoidance and distance connectivity maintenance.RCBF constraints are designed based on collision avoidance and connectivity maintenance requirements,and security constraints are achieved through a combination.Then,the specified safety constraints are integrated with the objective of forming a multi-autonomous mobile robot formation.To ensure safe control,the optimization problem is integrated with the DMPC method.Finally,the RCBF-DMPC algorithm is proposed to ensure iterative feasibility and stability while meeting the constraints and expected objectives.Simulation experiments illustrate that the designed algorithm can achieve cooperative formation and ensure system security.展开更多
The cooperative output regulation problem has been studied by two approaches:the distributed observer(DO)approach and the distributed internal model(DIM)approach,respectively.Each of these two approaches has its own m...The cooperative output regulation problem has been studied by two approaches:the distributed observer(DO)approach and the distributed internal model(DIM)approach,respectively.Each of these two approaches has its own merits and weaknesses.Recently,we presented an overview on the cooperative output regulation problem by the DO approach.This paper further surveys the cooperative output regulation problem by the DIM approach.We first summarize the constructions and the roles of two different versions of the internal models:the distributed p-copy internal model and the distributed canonical internal model.Then,we describe an integrated framework that combines the DO approach and the DIM approach.Extensions and variants of the DIM and their applications will also be highlighted.展开更多
A distributed capacitance model for monolithic inductors is developed to predict the equivalently parasitical capacitances of the inductor.The ratio of the self-resonant frequency (f SR) of the differential-driven sym...A distributed capacitance model for monolithic inductors is developed to predict the equivalently parasitical capacitances of the inductor.The ratio of the self-resonant frequency (f SR) of the differential-driven symmetric inductor to the f SR of the single-ended driven inductor is firstly predicted and explained.Compared with a single-ended configuration,experimental data demonstrate that the differential inductor offers a 127% greater maximum quality factor and a broader range of operating frequencies.Two differential inductors with low parasitical capacitance are developed and validated.展开更多
Medicinal plant diversity(MPD)is an indispensable part of global plant diversity,serving as the foundation for human survival by offering remedies and preventive measures against diseases.However,factors such as overe...Medicinal plant diversity(MPD)is an indispensable part of global plant diversity,serving as the foundation for human survival by offering remedies and preventive measures against diseases.However,factors such as overexploitation,competition from invasive alien species,and climate change,threaten the habitats of medicinal plants,necessitating a comprehensive understanding of their spatial distribution and suitable habitats.We leveraged a decade of field survey data on medicinal plant distribution in the Yinshan Mountains,combined with spatial analysis,species distribution modeling,and the Carnegie Ames Stanford Approach(CASA)to explore the MPD spatial distribution and suitable habitats.Spatial analysis revealed that the central and eastern parts of Yinshan Mountains were the primary MPD hotspots,with no cold spots evident at various spatial scales.As the spatial scale decreased,previous non-significant regions transformed into hotspots,with instances where large-scale hotspots became insignificant.These findings offer valuable guidance for safeguarding and nurturing MPD across diverse spatial scales.In future climate change scenarios within the shared socioeconomic pathways(SSP),the habitat suitability for MPD in the Yinshan Mountains predominantly remains concentrated in the central and eastern regions.Notably,areas with high net primary productivity(NPP)values and abundant vegetation coverage align closely with MPD habitat suitability areas,potentially contributing to the region's rich MPD.展开更多
Reptile fauna should be considered a conservation objective,especially in respect of the impacts of climate change on their distribution and range’s dynamics.Investigating the environmental drivers of reptile species...Reptile fauna should be considered a conservation objective,especially in respect of the impacts of climate change on their distribution and range’s dynamics.Investigating the environmental drivers of reptile species richness and identifying their suitable habitats is a fundamental prerequisite to setting efficient long-term conservation measures.This study focused on geographical patterns and estimations of species richness for herpetofauna widely spread Z.vivipara,N.natrix,V.berus,A.colchica,and protected in Latvia C.austriaca,E.orbicularis,L.agilis inhabiting northern(model territory Latvia)and southern(model territory Ukraine)part of their European range.The ultimate goal was to designate a conservation network that will meet long-term goals for survival of the target species in the context of climate change.We used stacked species distribution models for creating maps depicting the distribution of species richness under current and future(by 2050)climates for marginal reptilepopulations.Using cluster analysis,we showed that this herpeto-complex can be divided into“widespread species”and“forest species”.For all forest species we predicted a climate-driven reduction in their distribution range both North(Latvia)and South(Ukraine).The most vulnerable populations of“forest species”tend to be located in the South of their range,as a consequence of northward shifts by 2050.By 2050 the greatest reduction in range is predicted for currently widely spread Z.vivipara(by 1.4 times)and V.berus(by 2.2 times).In terms of designing an effective protected-area network,these results permit to identify priority conservation areas where the full ensemble of selected reptile species can be found,and confirms the relevance of abioticmulti-factor GIS-modelling for achieving this goal.展开更多
Runoff observation uncertainty is a key unsolved issue in the hydrology community.Existing studies mainly focused on observation uncertainty sources and their impacts on simulation performance,but the impacts on chang...Runoff observation uncertainty is a key unsolved issue in the hydrology community.Existing studies mainly focused on observation uncertainty sources and their impacts on simulation performance,but the impacts on changes of flow regime characteristics remained rare.This study detects temporal changes in 16 flow regime metrics from five main components(i.e.,magnitude,frequency of events,variability,duration,and timing),and evaluates the effects of observation uncertainty on trends of flow regime metrics by adopting a normal distribution error model and using uncertainty width,significant change rate of slopes,coefficient of variation,and degree of deviation.The daily runoff series from 1971 to 2020 at five hydrological stations(i.e.,Huangheyan,Tangnaihai,and Lanzhou in the Yellow River Source Region,Xianyang in the Weihe River Catchment,and Heishiguan in the Yiluo River Catchment)in the water conservation zone of Yellow River are collected for our study.Results showed that:(1)Flow regimes showed significant increases in the low flow magnitude,and significant decreases in the high and average flow magnitude,variability and duration at all the five stations.The magnitude,variability and duration metrics decreased significantly,and the frequency metrics increased significantly at Heishiguan.The low flow magnitude and timing metrics increased significantly,while the high flow magnitude,frequency and variability metrics decreased significantly at Xianyang.The low flow magnitude and high flow timing metrics increased significantly,while the low flow frequency,high flow magnitude and variability metrics decreased significantly in the Yellow River Source Region.(2)Observation uncertainty remarkably impacted the changes of 28.75% of total flow regime metrics at all the stations.The trends of 11.25% of total metrics changed from significance to insignificance,while those of 17.5% of total metrics changed from insignificance to significance.For the rest metrics,the trends remained the same,i.e.,significant(18.75%)and insignificant(52.50%)trends.(3)Observation uncertainty had the greatest impacts on the frequency metrics,especially at Xianyang,followed by duration,variability,timing and magnitude metrics.展开更多
Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic...Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic,and hydrogeological models are operationally exploited.This holistic approach was adopted for the development of the AquaVar DSS,used for water resource management in the French Mediterranean Var watershed.The year 2019 marked the initial use of the DSS in its operational environment.Over the next 5 years,multiple hydrological events allowed to test the performance of the DSS.The results show that the tool is capable of simulating peak flows associated with two extreme rainfall events(storms Alex and Aline).For a moderate flood,the real-time functionality was able to simulate forecast discharges 26 h before the flood peak,with a maximum local error of 30%.Finally,simulations for the drought period 2022-2023 highlighted the essential need for DSS to evolve in line with changing climatic conditions,which give rise to unprecedented hydrological processes.The lessons learned from these first 5 years of AquaVar use under operational conditions are synthesized,addressing various topics such as DSS modularity,evolution,data positioning,technology,and governance.展开更多
The use ofrenewable energyisan important way toachieve sustainable agriculturalandeconomic development.However,there are differences in accessto renewable energy between the Global North and Global South.This study ut...The use ofrenewable energyisan important way toachieve sustainable agriculturalandeconomic development.However,there are differences in accessto renewable energy between the Global North and Global South.This study utilisedan autoregressive distributed lag-error correctionmodel and thedata spanning from 1991to 2021 to comparatively analyse the dynamic relationship amongrenewable energy consumption,the value of agricultural production,gross domestic product(GDP),economic diversificationindex,urban population,the total water extraction for agricultural withdrawal,and trade balancein the Netherlands and South Africa.In the shortrun,renewable energy consumption was increased by the value of agricultural productionbut decreased by GDPin South Africa.In the longrun,renewable energy consumption and GDP increased the value of agricultural production,while the value of agricultural production also increased GDP in South Africa.However,in the Netherlands,there was no short-and long-run relationship betweenrenewable energy consumption and agricultural and economic development.The results revealedthat there was a short-and long-run relationship in South Africa.Moreover,in the Netherlands,the adjustment speed was-1.46 forrenewable energy consumption with an error correction of 0.68 a(8.22 months).In South Africa,the adjustment speedwas-1.28 forrenewable energy consumption with an error correction of 0.78 a(9.38 months).Therefore,compared to South Africa,renewable energy consumptionin the Netherlands takes less time to return to balance after a shock.Thesefindings signify different trajectories on sectoral and economic transition initiatives spurred usingrenewable energy between the Netherlands and South Africa.Policy relating to initiatives such as“agro-energy communities”in Global South countries such as South Africa should be emphasised to promote the use of renewable energy in the agricultural sector.展开更多
文摘In Pakistan,the solar analogue has been addressed but its surface geographical parameterization has given least attention.Inappropriate density of stations and their spatial coverage particularly in difficult peripheral national territories,little or no solar radiation data,non-satisfactory sunshine hours data,and low quality of ground observed cloud cover data create a situation in which the spatial modeling of Extraterrestrial Solar Radiation(ESR) and its ground parameterization got sufficient scope.The Digital Elevation Model (DEM) input into Geographic Information System (GIS) is a compatible tool to demonstrate the spatial distribution of ESR over the rugged terrains of the study domain.For the first time,distributed modeling of ESR is done over the rugged terrains of Pakistan,based on DEM and ArcGIS..Results clearly depict that the complex landforms profoundly disrupt the zonal distribution of ESR in Pakistan.The screening impact of topography is higher on spatial distribution of ESR in winter and considerably low in summer.The combined effect of topography and latitude is obvious.Hence,the model was further testified by plotting Rb (ratio of ESR quantity over rugged terrain against plane surface) against azimuth at different latitudes with different angled slopes.The results clearly support the strong screening effect of rugged terrain through out the country especially in Himalayas,Karakoram and Hindukush (HKH),western border mountains and Balochistan Plateau.This model can be instrumental as baseline geospatial information for scientific investigations in Pakistan,where substantial fraction of national population is living in mountainous regions.
文摘Due to the influences of local topographical factors and terrain inter-shielding, calculation of direct solar radiation （DSR） quantity of rugged terrain is very complex. Based on digital elevation model （DEM） data and meteorological observations, a distributed model for calculating DSR over rugged terrain is developed. This model gives an all-sided consideration on factors influencing th a resolution of 1 km × 1 km for thDSR. Using the developed model, normals of annual DSR quantity wie Yellow River Basin was generated, with DEM data as the general characterization of terrain. Characteristics of DSR quantity influenced by geographic and topographic factors over rugged terrain were analyzed thoroughly. Results suggest that： influenced by local topographic factors, i.e. azimuth, slope and so on, and annual DSR quantity over mountainous area has a clear spatial difference; annual DSR quantity of sunny slope （or southern slope） of mountains is obviously larger than that of shady slope （or northern slope）. The calculated DSR quantity of the Yellow River Basin is provided in the same way as other kinds of spatial information and can be employed as basic geographic data for relevant studies as well.
基金supported by the National Key R&D Program of China(No.2023YFC3006702)the Natural Science Foundation of Beijing Municipality(IS23117).
文摘Characterized by special morphologic,geographic,hydrologic,and societal behaviors,the water resources management of the Mediterranean catchment often shows a higher level of complexity including security issues of water supply,inundation risks,and environment management under the perspective of climate change.To have a comprehensive understanding of the Mediterranean water-cycle system,a deterministic distributed hydrologic modeling approach has been developed and presented in this study based on an application in the Var catchment(2800 km^(2))located at the French Mediterranean region.A 1D and 2D coupled model of MIKE SHE and MIKE 11 has been set up under a series of hypotheses to represent the whole hydrologic and hydrodynamic processes including rainfall-runoff,snow-melting,channel flow,overland flow,and the water exchange between land surface and unsaturated/saturated zones.The developed model was first calibrated with 4 years daily records from 2008 to 2011,then to be validated and further run within hourly time interval to produce detailed representation of the catchment water-cycle from 2012 to 2014.The deterministic distributed modeling approach presented in this study is able to represent its complicated water-cycle and used for supporting the decision‐making process of the water resources management of the catchment.
基金supported by the Pilot program“Adaptation to climate change”of the Swiss Federal Office for the Environment(FOEN,project E03)by the Interreg V A Italy Switzerland Cooperation Program 20142020(project MONGEFITOFOR).
文摘Biological invasions,driven mainly by human activities,pose significant threats to global ecosystems and economies,with fungi and fungal-like oomycetes playing a pivotal role.Ink disease,caused by Phytophthora cinnamomi and P.×cambivora,is a growing concern for sweet chestnut stands(Castanea sativa)in Europe.Since both pathogens are thermophilic organisms,ongoing climate change will likely exacerbate their impact.In this study,we applied species distribution modeling techniques to identify poten-tial substitutive species for sweet chestnut in the light of future climate scenarios SSP126 and SSP370 in southern Switzerland.Using the presence-only machine learning algorithm MaxEnt and leveraging occurrence data from the global dataset GBIF,we delineated the current and projected(2070-2100)distribution of 28 tree species.Several exotic species emerged as valuable alternatives to sweet chestnut,although careful consideration of all potential ecological consequences is required.We also identified several native tree species as promising substitutes,offering ecological benefits and potential adaptability to climatic conditions.Since species diversification fosters forest resilience,we also determined communities of alternative species that can be grown together.Our findings represent a valuable deci-sion tool for forest managers confronted with the challenges posed by ink disease and climate change.Given that,even in absence of disease,sweet chestnut is not a future-proof tree species in the study region,the identified species could offer a pathway toward resilient and sustainable forests within the entire chestnut belt.
基金Supported by the National Natural Science Foundation of China(No.U24B20156)the National Defense Basic Scientific Research Program of China(No.JCKY2021204B051)the National Laboratory of Space Intelligent Control of China(Nos.HTKJ2023KL502005 and HTKJ2024KL502007)。
文摘A chance-constrained energy dispatch model based on the distributed stochastic model predictive control(DSMPC)approach for an islanded multi-microgrid system is proposed.An ambiguity set considering the inherent uncertainties of renewable energy sources(RESs)is constructed without requiring the full distribution knowledge of the uncertainties.The power balance chance constraint is reformulated within the framework of the distributionally robust optimization(DRO)approach.With the exchange of information and energy flow,each microgrid can achieve its local supply-demand balance.Furthermore,the closed-loop stability and recursive feasibility of the proposed algorithm are proved.The comparative results with other DSMPC methods show that a trade-off between robustness and economy can be achieved.
基金the National Nat-ural Science Foundation of China(Nos.52074029,51804026)the USTB-NTUT Joint Research Program(No.06310063)Chuan Wang would like to acknowledge the funding support from Vinnova(dnr:2017-01327).
文摘Combustion kinetics of the hydrochar was investigated using a multi-Gaussian-distributed activation energy model(DAEM)to ex-pand the knowledge on the combustion mechanisms.The results demonstrated that the kinetic parameters calculated by the multi-Gaussian-DAEM accurately represented the experimental conversion rate curves.Overall,the feedstock combustion could be divided into four stages:the decomposition of hemicellulose,cellulose,lignin,and char combustion.The hydrochar combustion could in turn be divided into three stages:the combustion of cellulose,lignin,and char.The mean activation energy ranges obtained for the cellulose,lignin,and char were 273.7-292.8,315.1-334.5,and 354.4-370 kJ/mol,respectively,with the standard deviations of 2.1-23.1,9.5-27.4,and 12.1-22.9 kJ/mol,re-spectively.The cellulose and lignin contents first increased and then decreased with increasing hydrothermal carbonization(HTC)temperature,while the mass fraction of char gradually increased.
基金This work was supported by the Fundamental Research Funds for the Central Universities （No.2017JBM003）, the National Natural Science Foundation of China （No.61575053, No.61504008）, and the Specialized Research Fund for the Doctoral Program of Higher Education of China （No.20130009120042）.
文摘Lithium ion battery has typical character of distributed parameter system, and can be described precisely by partial differential equations and multi-physics theory because lithium ion battery is a complicated electrochemical energy storage system. A novel failure prediction modeling method of lithium ion battery based on distributed parameter estimation and single particle model is proposed in this work. Lithium ion concentration in the anode of lithium ion battery is an unmeasurable distributed variable. Failure prediction system can estimate lithium ion concentration online, track the failure residual which is the difference between the estimated value and the ideal value. The precaution signal will be triggered when the failure residual is beyond the predefined failure precaution threshold, and the failure countdown prediction module will be activated. The remaining time of the severe failure threshold can be estimated by the failure countdown prediction module according to the changing rate of the failure residual. A simulation example verifies that lithium ion concentration in the anode of lithium ion battery can be estimated exactly and effectively by the failure prediction model. The precaution signal can be triggered reliably, and the remaining time of the severe failure can be forecasted accurately by the failure countdown prediction module.
基金supported by the National Key R&D Program of China (2018AAA0101701)the National Natural Science Foundation of China (62073220,61833012)。
文摘In this paper,distributed model predictive control(DMPC) for island DC micro-grids(MG) with wind/photovoltaic(PV)/battery power is proposed,which coordinates all distributed generations(DG) to stabilize the bus voltage together with the insurance of having computational efficiency under a real-time requirement.Based on the feedback of the bus voltage,the deviation of the current is dispatched to each DG according to cost over the prediction horizon.Moreover,to avoid the excessive fluctuation of the battery power,both the discharge-charge switching times and costs are considered in the model predictive control(MPC) optimization problems.A Lyapunov constraint with a time-varying steady-state is designed in each local MPC to guarantee the stabilization of the entire system.The voltage stabilization of the MG is achieved by this strategy with the cooperation of DGs.The numeric results of applying the proposed method to a MG of the Shanghai Power Supply Company shows the effectiveness of the distributed economic MPC.
基金supported by the National Natural Science Foundation of China(52372310)the State Key Laboratory of Advanced Rail Autonomous Operation(RAO2023ZZ001)+1 种基金the Fundamental Research Funds for the Central Universities(2022JBQY001)Beijing Laboratory of Urban Rail Transit.
文摘The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches.
基金supported by the National Natural Science Foundation of China(No.42071057).
文摘The Qilian Mountains, a national key ecological function zone in Western China, play a pivotal role in ecosystem services. However, the distribution of its dominant tree species, Picea crassifolia (Qinghai spruce), has decreased dramatically in the past decades due to climate change and human activity, which may have influenced its ecological functions. To restore its ecological functions, reasonable reforestation is the key measure. Many previous efforts have predicted the potential distribution of Picea crassifolia, which provides guidance on regional reforestation policy. However, all of them were performed at low spatial resolution, thus ignoring the natural characteristics of the patchy distribution of Picea crassifolia. Here, we modeled the distribution of Picea crassifolia with species distribution models at high spatial resolutions. For many models, the area under the receiver operating characteristic curve (AUC) is larger than 0.9, suggesting their excellent precision. The AUC of models at 30 m is higher than that of models at 90 m, and the current potential distribution of Picea crassifolia is more closely aligned with its actual distribution at 30 m, demonstrating that finer data resolution improves model performance. Besides, for models at 90 m resolution, annual precipitation (Bio12) played the paramount influence on the distribution of Picea crassifolia, while the aspect became the most important one at 30 m, indicating the crucial role of finer topographic data in modeling species with patchy distribution. The current distribution of Picea crassifolia was concentrated in the northern and central parts of the study area, and this pattern will be maintained under future scenarios, although some habitat loss in the central parts and gain in the eastern regions is expected owing to increasing temperatures and precipitation. Our findings can guide protective and restoration strategies for the Qilian Mountains, which would benefit regional ecological balance.
基金supported by the State Grid Science&Technology Project of China(5400-202224153A-1-1-ZN).
文摘Expanding photovoltaic(PV)resources in rural-grid areas is an essential means to augment the share of solar energy in the energy landscape,aligning with the“carbon peaking and carbon neutrality”objectives.However,rural power grids often lack digitalization;thus,the load distribution within these areas is not fully known.This hinders the calculation of the available PV capacity and deduction of node voltages.This study proposes a load-distribution modeling approach based on remote-sensing image recognition in pursuit of a scientific framework for developing distributed PV resources in rural grid areas.First,houses in remote-sensing images are accurately recognized using deep-learning techniques based on the YOLOv5 model.The distribution of the houses is then used to estimate the load distribution in the grid area.Next,equally spaced and clustered distribution models are used to adaptively determine the location of the nodes and load power in the distribution lines.Finally,by calculating the connectivity matrix of the nodes,a minimum spanning tree is extracted,the topology of the network is constructed,and the node parameters of the load-distribution model are calculated.The proposed scheme is implemented in a software package and its efficacy is demonstrated by analyzing typical remote-sensing images of rural grid areas.The results underscore the ability of the proposed approach to effectively discern the distribution-line structure and compute the node parameters,thereby offering vital support for determining PV access capability.
文摘In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the aim to put in light the main f eatures of the proposed approach. Moreover, it is important to underline that in different operating scenarios the proposed reinforcement learning scheme is capable of significantly reducing traffic congestion phenomena when compared with well-reputed competitors.
基金National Natural Science Foundation of China(Nos.62173303 and 62273307)Natural Science Foundation of Zhejiang Province(No.LQ24F030023)。
文摘A distributed model predictive control(DMPC)method based on robust control barrier function(RCBF)is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed environment.The first step is to analyze the safety requirements of the system during safe formation and categorize them into collision avoidance and distance connectivity maintenance.RCBF constraints are designed based on collision avoidance and connectivity maintenance requirements,and security constraints are achieved through a combination.Then,the specified safety constraints are integrated with the objective of forming a multi-autonomous mobile robot formation.To ensure safe control,the optimization problem is integrated with the DMPC method.Finally,the RCBF-DMPC algorithm is proposed to ensure iterative feasibility and stability while meeting the constraints and expected objectives.Simulation experiments illustrate that the designed algorithm can achieve cooperative formation and ensure system security.
基金supported by the National Natural Science Foundation of China(Nos.62173092,62173149)the Hong Kong Region Research Grants Council(No.14201621).
文摘The cooperative output regulation problem has been studied by two approaches:the distributed observer(DO)approach and the distributed internal model(DIM)approach,respectively.Each of these two approaches has its own merits and weaknesses.Recently,we presented an overview on the cooperative output regulation problem by the DO approach.This paper further surveys the cooperative output regulation problem by the DIM approach.We first summarize the constructions and the roles of two different versions of the internal models:the distributed p-copy internal model and the distributed canonical internal model.Then,we describe an integrated framework that combines the DO approach and the DIM approach.Extensions and variants of the DIM and their applications will also be highlighted.
文摘A distributed capacitance model for monolithic inductors is developed to predict the equivalently parasitical capacitances of the inductor.The ratio of the self-resonant frequency (f SR) of the differential-driven symmetric inductor to the f SR of the single-ended driven inductor is firstly predicted and explained.Compared with a single-ended configuration,experimental data demonstrate that the differential inductor offers a 127% greater maximum quality factor and a broader range of operating frequencies.Two differential inductors with low parasitical capacitance are developed and validated.
基金The National Key Research and Development Program of China,No.2021YFE0190100Inner Mongolia Autonomous Region Mongolian Medicine Standardization Project,No.2023-[MB023]The Earmarked Fund for CARS,No.CARS-21。
文摘Medicinal plant diversity(MPD)is an indispensable part of global plant diversity,serving as the foundation for human survival by offering remedies and preventive measures against diseases.However,factors such as overexploitation,competition from invasive alien species,and climate change,threaten the habitats of medicinal plants,necessitating a comprehensive understanding of their spatial distribution and suitable habitats.We leveraged a decade of field survey data on medicinal plant distribution in the Yinshan Mountains,combined with spatial analysis,species distribution modeling,and the Carnegie Ames Stanford Approach(CASA)to explore the MPD spatial distribution and suitable habitats.Spatial analysis revealed that the central and eastern parts of Yinshan Mountains were the primary MPD hotspots,with no cold spots evident at various spatial scales.As the spatial scale decreased,previous non-significant regions transformed into hotspots,with instances where large-scale hotspots became insignificant.These findings offer valuable guidance for safeguarding and nurturing MPD across diverse spatial scales.In future climate change scenarios within the shared socioeconomic pathways(SSP),the habitat suitability for MPD in the Yinshan Mountains predominantly remains concentrated in the central and eastern regions.Notably,areas with high net primary productivity(NPP)values and abundant vegetation coverage align closely with MPD habitat suitability areas,potentially contributing to the region's rich MPD.
文摘Reptile fauna should be considered a conservation objective,especially in respect of the impacts of climate change on their distribution and range’s dynamics.Investigating the environmental drivers of reptile species richness and identifying their suitable habitats is a fundamental prerequisite to setting efficient long-term conservation measures.This study focused on geographical patterns and estimations of species richness for herpetofauna widely spread Z.vivipara,N.natrix,V.berus,A.colchica,and protected in Latvia C.austriaca,E.orbicularis,L.agilis inhabiting northern(model territory Latvia)and southern(model territory Ukraine)part of their European range.The ultimate goal was to designate a conservation network that will meet long-term goals for survival of the target species in the context of climate change.We used stacked species distribution models for creating maps depicting the distribution of species richness under current and future(by 2050)climates for marginal reptilepopulations.Using cluster analysis,we showed that this herpeto-complex can be divided into“widespread species”and“forest species”.For all forest species we predicted a climate-driven reduction in their distribution range both North(Latvia)and South(Ukraine).The most vulnerable populations of“forest species”tend to be located in the South of their range,as a consequence of northward shifts by 2050.By 2050 the greatest reduction in range is predicted for currently widely spread Z.vivipara(by 1.4 times)and V.berus(by 2.2 times).In terms of designing an effective protected-area network,these results permit to identify priority conservation areas where the full ensemble of selected reptile species can be found,and confirms the relevance of abioticmulti-factor GIS-modelling for achieving this goal.
基金National Key Research and Development Program of China,No.2021YFC3201102National Natural Science Foundation of China,No.42071041,No.42171047。
文摘Runoff observation uncertainty is a key unsolved issue in the hydrology community.Existing studies mainly focused on observation uncertainty sources and their impacts on simulation performance,but the impacts on changes of flow regime characteristics remained rare.This study detects temporal changes in 16 flow regime metrics from five main components(i.e.,magnitude,frequency of events,variability,duration,and timing),and evaluates the effects of observation uncertainty on trends of flow regime metrics by adopting a normal distribution error model and using uncertainty width,significant change rate of slopes,coefficient of variation,and degree of deviation.The daily runoff series from 1971 to 2020 at five hydrological stations(i.e.,Huangheyan,Tangnaihai,and Lanzhou in the Yellow River Source Region,Xianyang in the Weihe River Catchment,and Heishiguan in the Yiluo River Catchment)in the water conservation zone of Yellow River are collected for our study.Results showed that:(1)Flow regimes showed significant increases in the low flow magnitude,and significant decreases in the high and average flow magnitude,variability and duration at all the five stations.The magnitude,variability and duration metrics decreased significantly,and the frequency metrics increased significantly at Heishiguan.The low flow magnitude and timing metrics increased significantly,while the high flow magnitude,frequency and variability metrics decreased significantly at Xianyang.The low flow magnitude and high flow timing metrics increased significantly,while the low flow frequency,high flow magnitude and variability metrics decreased significantly in the Yellow River Source Region.(2)Observation uncertainty remarkably impacted the changes of 28.75% of total flow regime metrics at all the stations.The trends of 11.25% of total metrics changed from significance to insignificance,while those of 17.5% of total metrics changed from insignificance to significance.For the rest metrics,the trends remained the same,i.e.,significant(18.75%)and insignificant(52.50%)trends.(3)Observation uncertainty had the greatest impacts on the frequency metrics,especially at Xianyang,followed by duration,variability,timing and magnitude metrics.
文摘Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic,and hydrogeological models are operationally exploited.This holistic approach was adopted for the development of the AquaVar DSS,used for water resource management in the French Mediterranean Var watershed.The year 2019 marked the initial use of the DSS in its operational environment.Over the next 5 years,multiple hydrological events allowed to test the performance of the DSS.The results show that the tool is capable of simulating peak flows associated with two extreme rainfall events(storms Alex and Aline).For a moderate flood,the real-time functionality was able to simulate forecast discharges 26 h before the flood peak,with a maximum local error of 30%.Finally,simulations for the drought period 2022-2023 highlighted the essential need for DSS to evolve in line with changing climatic conditions,which give rise to unprecedented hydrological processes.The lessons learned from these first 5 years of AquaVar use under operational conditions are synthesized,addressing various topics such as DSS modularity,evolution,data positioning,technology,and governance.
基金research supported wholly by the National Research Foundation (NRF) of South Africathe Dutch Research Council (NWO) Project (UID 129352)
文摘The use ofrenewable energyisan important way toachieve sustainable agriculturalandeconomic development.However,there are differences in accessto renewable energy between the Global North and Global South.This study utilisedan autoregressive distributed lag-error correctionmodel and thedata spanning from 1991to 2021 to comparatively analyse the dynamic relationship amongrenewable energy consumption,the value of agricultural production,gross domestic product(GDP),economic diversificationindex,urban population,the total water extraction for agricultural withdrawal,and trade balancein the Netherlands and South Africa.In the shortrun,renewable energy consumption was increased by the value of agricultural productionbut decreased by GDPin South Africa.In the longrun,renewable energy consumption and GDP increased the value of agricultural production,while the value of agricultural production also increased GDP in South Africa.However,in the Netherlands,there was no short-and long-run relationship betweenrenewable energy consumption and agricultural and economic development.The results revealedthat there was a short-and long-run relationship in South Africa.Moreover,in the Netherlands,the adjustment speed was-1.46 forrenewable energy consumption with an error correction of 0.68 a(8.22 months).In South Africa,the adjustment speedwas-1.28 forrenewable energy consumption with an error correction of 0.78 a(9.38 months).Therefore,compared to South Africa,renewable energy consumptionin the Netherlands takes less time to return to balance after a shock.Thesefindings signify different trajectories on sectoral and economic transition initiatives spurred usingrenewable energy between the Netherlands and South Africa.Policy relating to initiatives such as“agro-energy communities”in Global South countries such as South Africa should be emphasised to promote the use of renewable energy in the agricultural sector.
