The electrochemical corrosion of ductile pipes(DPs)in drinking water distribution systems(DWDS)has a crucial impact on cement-mortar lining(CML)failure and metal release,potentially leading to drinking water quality d...The electrochemical corrosion of ductile pipes(DPs)in drinking water distribution systems(DWDS)has a crucial impact on cement-mortar lining(CML)failure and metal release,potentially leading to drinking water quality deterioration and posing a risk to public health.An in-situ scanning vibrating electrode technique(SVET)with micron-scale resolution,microscopic scale detection and water quality analysis were used to investigate the corrosion behavior and metal release from DPs throughout the whole CML failure process.Metal pollutants release occurred at three different stages of CML failure process,and there are potential risks of water quality deterioration exceeding the maximum allowable levels set by national standards in the partial failure stage and lining peeling stage.Furthermore,the effects of water chemistry(Cl^(−),SO_(4)^(2−),NO_(3)−,and Ca^(2+))on corrosion scale growth and iron release activity,were investigated during the CML partial failure stage.Results showed that the CML failure process in DPs was accelerated by the autocatalysis of localized corrosion.Cl^(−)was found to damage the uncorroded metal surface,while SO_(4)^(2−)mainly dissolved the corrosion scale surface,increasing iron release.Both the oxidation of NO_(3)−and selective sedimentation of Ca2+were found to enhance the stability of corrosion scales and inhibit iron release.展开更多
The effects of disinfectants and plasmid-based antibiotic resistance genes(ARGs)on the growth of microorganisms and the plasmid-mediated transfer of ARGs in the water and biofilm of the drinkingwater distribution syst...The effects of disinfectants and plasmid-based antibiotic resistance genes(ARGs)on the growth of microorganisms and the plasmid-mediated transfer of ARGs in the water and biofilm of the drinkingwater distribution system under simulated conditionswere explored.The heterotrophic plate count of the water in reactors with 0.1 mg/L NaClO and NH_(2)Cl was higher than in the control groups.Therewas no similar phenomenon in biofilm.In thewater of reactors containing NaClO,the aphA and bla geneswere lower than in the antibiotic resistant bacteria group,while both genes were higher in the water of reactors with NH_(2)Cl than in the control group.Chloramine may promote the transfer of ARGs in the water phase.Both genes in the biofilm of the reactors containing chlorine were lower than the control group.Correlation analysis between ARGs and water quality parameters revealed that the copy numbers of the aphA gene were significantly positively correlated with the copy numbers of the bla gene in water and significantly negatively correlated in biofilm(p<0.05).The results of the sequencing assay showed that bacteria in the biofilm,in the presence of disinfectant,were primarily Gram-negative.1.0 mg/L chlorine decreased the diversity of the community in the biofilm.The relative abundance of some bacteria that may undergo transfer increased in the biofilm of the reactor containing 0.1 mg/L chlorine.展开更多
Resilience studies for water distribution systems(WDS)coupled with other interdependent infrastructure systems attract increasing attention from stakeholders and researchers.However,most existing large-scale WDS model...Resilience studies for water distribution systems(WDS)coupled with other interdependent infrastructure systems attract increasing attention from stakeholders and researchers.However,most existing large-scale WDS models are single infrastructure-based without consideration of other infrastructure systems.This is due to a lack of needed information on systems coupling,the structure of the simulator used,and the computation load involved.To address these gaps,this paper presents a synthetic modeling framework for a real-world WDS as coordinating with other infrastructure systems via a building-mediated clustering approach through consideration of physical distance and node capacity.First,the WDS network topology and operation parameters are inferred via bulk open-source information.A building-mediated clustering approach is designed to systematically derive the interdependence between the WDS and the power system similarly created as a case study.Second,a novel linearization method is developed in formulating the WDS model that can relieve computation load while maintaining accuracy.Finally,a disruption-recovery framework is developed to demonstrate the proposed methodology in modelling WDS resilience.The framework is applied to a neighborhood in Queenstown,Singapore,an area of 20.43 km^(2) and 96,000 population.The near-real-time simulations on the coupled system involving 308 nodes and 384 links showcase the effectiveness and application of the proposed synthetic modeling and formulation.展开更多
This paper introduces an optimized planning approach for integrating photovoltaic as distributed generation (PV-DG) into the radial distribution power systems, utilizing exhaustive load flow (ELF), loss sensitivity fa...This paper introduces an optimized planning approach for integrating photovoltaic as distributed generation (PV-DG) into the radial distribution power systems, utilizing exhaustive load flow (ELF), loss sensitivity factor (LSF), genetic algorithms (GA) methods, and numerical method based on LSF. The methodology aims to determine the optimal allocation and sizing of multiple PV-DG to minimize power loss through time series power flow analysis. An approach utilizing continuous sensitivity analysis is developed and inherently leverages power flow and loss equations to compute LSF of all buses in the system towards employing a dynamic PV-DG model for more accurate results. The algorithm uses a numerical grid search method to optimize PV-DG placement in a power distribution system, focusing on minimizing system losses. It combines iterative analysis, sensitivity assessment, and comprehensive visualization to identify and present the optimal PV-DG configurations. The present-ed algorithms are verified through co-simulation framework combining MATLAB and OpenDSS to carry out analysis for 12-bus radial distribution test system. The proposed numerical method is compared with other algorithms, such as ELF, LSF methods, and Genetic Algorithms (GA). Results show that the proposed numerical method performs well in comparison with LSF and ELF solutions.展开更多
Due to uncertainties in seismic pipeline damage and post-earthquake recovery processes,probabilistic characteristics such as mean value,standard deviation,probability density function,and cumulative distribution funct...Due to uncertainties in seismic pipeline damage and post-earthquake recovery processes,probabilistic characteristics such as mean value,standard deviation,probability density function,and cumulative distribution function provide valuable information.In this study,a simulation-based framework to evaluate these probabilistic characteristics in water distribution systems(WDSs)during post-earthquake recovery is developed.The framework first calculates pipeline failure probabilities using seismic fragility models and then generates damage samples through quasi-Monte Carlo simulations with Sobol’s sequence for faster convergence.System performance is assessed using a hydraulic model,and recovery simulations produce time-varying performance curves,where the dynamic importance of unrepaired damage determines repair sequences.Finally,the probabilistic characteristics of seismic performance indicators,resilience index,resilience loss,and recovery time are evaluated.The framework is applied in two benchmark WDSs with different layouts to investigate the probabilistic characteristics of their seismic performance and resilience.Application results show that the cumulative distribution function reveals the variations in resilience indicators for different exceedance probabilities,and there are dramatic differences among the recovery times corresponding to the system performance recovery targets of 80%,90%,and 100%.展开更多
Toxoplasma gondii(T.gondii)is a globally distributed parasite that can infect a diversity of warm-blooded animals,including swine and humans.Infection in swine poses a considerable threat to food safety and public hea...Toxoplasma gondii(T.gondii)is a globally distributed parasite that can infect a diversity of warm-blooded animals,including swine and humans.Infection in swine poses a considerable threat to food safety and public health.The aim of this meta-analysis was to estimate the seroprevalence of T.gondii infection in the swine population in China from 2000 to 2023 and to examine potential factors associated with infection.A total of 112 studies were included,collectively involving 145,152 swine samples originating from 26 provinces.The pooled seroprevalence was 26.0%(95%CI:23.3%–28.7%).Stratified analysis based on diagnostic methods revealed that studies using the indirect hemagglutination assay(IHA)reported a seroprevalence of 19.7%(95%CI:17.2%–22.2%),whereas those utilizing the enzyme-linked immunosorbent assay(ELISA)reported a higher seroprevalence of 35.5%(95%CI:29.1%–41.8%).Geographical analysis indicated higher seroprevalence in the South Central and Southwest regions,whereas the East and Northwest areas reported the lowest seroprevalence.Chongqing Province reported the highest seroprevalence,reaching 44.9%(95%CI:43.4%–46.0%),followed by Xinjiang,Hainan,and Guizhou,whereas the lowest was observed in Shandong Province(3.5%,95%CI:1.7%–6.1%).These findings provide important epidemiological evidence that can inform strategies for the prevention and control of T.gondii infection in swine populations,with a focus on high-risk populations and geographical areas.This imperative contributes substantially to the improvement of both food safety and public health.展开更多
This paper deals with reduction of losses in electric power distribution system through a dynamic reconfiguration case study of a grid in the city of Mostar,Bosnia and Herzegovina.The proposed solution is based on a n...This paper deals with reduction of losses in electric power distribution system through a dynamic reconfiguration case study of a grid in the city of Mostar,Bosnia and Herzegovina.The proposed solution is based on a nonlinear model predictive control algorithm which determines the optimal switching operations of the distribution system.The goal of the control algorithm is to find the optimal radial network topology which minimizes cumulative active power losses and maximizes voltages across the network while simultaneously satisfying all system constraints.The optimization results are validated through multiple simulations(using real power demand data collected for a few characteristic days during winter and summer)which demonstrate the efficiency and usefulness of the developed control algorithm in reducing the grid losses by up to 14%.展开更多
Nodal pricing is a critical mechanism in electricity markets,utilized to determine the cost of power transmission to various nodes within a distribution network.As power systems evolve to incorporate higher levels of ...Nodal pricing is a critical mechanism in electricity markets,utilized to determine the cost of power transmission to various nodes within a distribution network.As power systems evolve to incorporate higher levels of renewable energy and face increasing demand fluctuations,traditional nodal pricing models often fall short to meet these new challenges.This research introduces a novel enhanced nodal pricing mechanism for distribution networks,integrating advanced optimization techniques and hybrid models to overcome these limitations.The primary objective is to develop a model that not only improves pricing accuracy but also enhances operational efficiency and system reliability.This study leverages cutting-edge hybrid algorithms,combining elements of machine learning with conventional optimization methods,to achieve superior performance.Key findings demonstrate that the proposed hybrid nodal pricing model significantly reduces pricing errors and operational costs compared to conventional methods.Through extensive simulations and comparative analysis,the model exhibits enhanced performance under varying load conditions and increased levels of renewable energy integration.The results indicate a substantial improvement in pricing precision and network stability.This study contributes to the ongoing discourse on optimizing electricity market mechanisms and provides actionable insights for policymakers and utility operators.By addressing the complexities of modern power distribution systems,our research offers a robust solution that enhances the efficiency and reliability of power distribution networks,marking a significant advancement in the field.展开更多
The majority of water utilities,particularly public service providers such as Gidole town,are struggling to deliver a sufficient and consistent supply of water in Ethiopia's developing towns.The primary objective ...The majority of water utilities,particularly public service providers such as Gidole town,are struggling to deliver a sufficient and consistent supply of water in Ethiopia's developing towns.The primary objective of this study was to assess the hydraulic performance of water supply distribution system in Gidole Town,Ethiopia,a representative case of the challenges facing public water utilities in developing towns.The WaterGEMS v8i hydraulic model was utilized to simulate and evaluate the distribution network's performance.The system was configured as a looped network and analyzed against standard permitted pressure and velocity values in the distribution system.The model was effectively calibrated(coefficient of determination(R^(2))=0.969)using measured and observed pressure data.The model simulation run was conducted at peak and low hourly demand with 1.9 and 0.25 hourly factors,respectively.The estimated water demand of the town is 1284.3m^(3)/day(48.4 liters per capita per day),and it would be increased to 3099.77m^(3)/day(66.03 l/c/d)by the 2037 design period.The system experiences significant non-revenue water losses(75,434.11m^(3)/year),accounting for 29.9%of total water production;as a result,the present water supply coverage of the town is only 33.6%.Hydraulic simulations under peak and low demand scenarios revealed nodes with pressures outside the normal range,indicating system-wide inefficiencies.These findings highlight a combined issue of large physical losses and insufficient capacity of the water supply in the town,which is typical of many municipal systems in developing regions.The study concludes that strategic infrastructure rehabilitation,with an emphasis on pressure management and leak reduction,is not only a town necessity but a fundamental requirement for improving water security and financial sustainability for utilities in Ethiopia and similar contexts.The findings and methodology have been forwarded to town's water supply project and institutional development departments for immediate future implementation and provide a replicable framework for evidence-based investment and planning in other struggling municipalities in similar situations.展开更多
As urban areas expand and water demand intensifies,the need for efficient and reliable water distribution systems becomes increasingly critical.A widely used infrastructure management approach involves partitioning wa...As urban areas expand and water demand intensifies,the need for efficient and reliable water distribution systems becomes increasingly critical.A widely used infrastructure management approach involves partitioning water distribution networks(WDNs)into district metered areas(DMAs).However,suboptimal designs of DMA partitioning can lead to inefficiencies and increased costs.This study presents a core-peripheryinformed approach for DMA design that explicitly utilises the natural division between a densely connected core and a sparsely connected periphery.Incorporating this structural framework enhances network resilience,improves water pressure stability,and optimises boundary device placement.The proposed core-periphery-informed DMA design integrates hydraulic and topological analyses to identify central and peripheral network areas,applies a community structure detection algorithm conditioned by these areas,and uses an optimisation model to determine the optimal placement of boundary devices,enhancing network resilience and reducing costs.When applied to the Modena WDN in Italy,this approach demonstrates improved pressure stability and significant cost reductions compared to traditional methods.Overall,the findings highlight the practical benefits of the core-periphery-based DMA design,offering a scalable and data-driven solution for urban water distribution systems.展开更多
Gas turbine rotors are complex dynamic systems with high-dimensional,discrete,and multi-source nonlinear coupling characteristics.Significant amounts of resources and time are spent during the process of solving dynam...Gas turbine rotors are complex dynamic systems with high-dimensional,discrete,and multi-source nonlinear coupling characteristics.Significant amounts of resources and time are spent during the process of solving dynamic characteristics.Therefore,it is necessary to design a lowdimensional model that can well reflect the dynamic characteristics of high-dimensional system.To build such a low-dimensional model,this study developed a dimensionality reduction method considering global order energy distribution by modifying the proper orthogonal decomposition theory.First,sensitivity analysis of key dimensionality reduction parameters to the energy distribution was conducted.Then a high-dimensional rotor-bearing system considering the nonlinear stiffness and oil film force was reduced,and the accuracy and the reusability of the low-dimensional model under different operating conditions were examined.Finally,the response results of a multi-disk rotor-bearing test bench were reduced using the proposed method,and spectrum results were then compared experimentally.Numerical and experimental results demonstrate that,during the dimensionality reduction process,the solution period of dynamic response results has the most significant influence on the accuracy of energy preservation.The transient signal in the transformation matrix mainly affects the high-order energy distribution of the rotor system.The larger the proportion of steady-state signals is,the closer the energy tends to accumulate towards lower orders.The low-dimensional rotor model accurately reflects the frequency response characteristics of the original high-dimensional system with an accuracy of up to 98%.The proposed dimensionality reduction method exhibits significant application potential in the dynamic analysis of highdimensional systems coupled with strong nonlinearities under variable operating conditions.展开更多
With the continuous expansion of the power system scale and the increasing complexity of operational mode,the interaction between transmission and distribution systems is becoming more and more significant,placing hig...With the continuous expansion of the power system scale and the increasing complexity of operational mode,the interaction between transmission and distribution systems is becoming more and more significant,placing higher requirements on the accuracy and efficiency of the power system state estimation to address the challenge of balancing computational efficiency and estimation accuracy in traditional coupled transmission and distribution state estimation methods,this paper proposes a collaborative state estimation method based on distribution systems state clustering and load model parameter identification.To resolve the scalability issue of coupled transmission and distribution power systems,clustering is first carried out based on the distribution system states.As the data and models of the transmission system and distribution systems are not shared.For the transmission system,equating the power transmitted from the transmission system to the distribution system is the same as equating the distribution system.Further,the power transmitted from the transmission system to different types of distribution systems is equivalent to different polynomial equivalent load models.Then,a parameter identification method is proposed to obtain the parameters of the equivalent load model.Finally,a transmission and distribution collaborative state estimation model is constructed based on the equivalent load model.The results of the numerical analysis show that compared with the traditional master-slave splitting method,the proposed method significantly enhances computational efficiency while maintaining high estimation accuracy.展开更多
Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,th...Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,the public network communication system is easily damaged after disasters,causing the operation center to lose control of the distribution network.In this paper,we considered using satellites to transmit the distribution network data and focus on the resource scheduling problem of the satellite emergency communication system for the distribution network.Specifically,this paper first formulates the satellite beam-pointing problem and the accesschannel joint resource allocation problem.Then,this paper proposes the Priority-based Beam-pointing and Access-Channel joint optimization algorithm(PBAC),which uses convex optimization theory to solve the satellite beam pointing problem,and adopts the block coordinate descent method,Lagrangian dual method,and a greedy algorithm to solve the access-channel joint resource allocation problem,thereby obtaining the optimal resource scheduling scheme for the satellite network.Finally,this paper conducts comparative experiments with existing methods to verify the effec-tiveness of the proposed methods.The results show that the total weighted transmitted data of the proposed algorithm is increased by about 19.29∼26.29%compared with other algorithms.展开更多
Background:Building upon our previous work that developed a folate receptor-mediated,euphaorbia factor L1-loaded PLGA microsphere system integrating active and magnetic targeting for theranostics,further investigation...Background:Building upon our previous work that developed a folate receptor-mediated,euphaorbia factor L1-loaded PLGA microsphere system integrating active and magnetic targeting for theranostics,further investigation into its in vivo pharmacokinetics and tissue distribution is warranted despite its demonstrated biocompatibility and safety.Methods:A UPLC-MS/MS method was established to determine the concentration of euphorbia sterol in rat plasma and mouse tissue homogenates,healthy male SD rats and KM mice were administered in groups,drug concentrations at different time points were determined,pharmacokinetic parameters were analyzed by DAS software,and data were processed by SAS software.Results:The proposed method met the requirements of biological sample detection.The plasma pharmacokinetics of rats showed that the drug concentration in the microsphere group was lower than that in the injection group,and the parameters such as mean residence time(MRT(0–t)),half-life(T1/2z)and apparent volume of distribution(Vz)were significantly different from those in the solution group.The distribution of mouse tissues showed that the drug concentrations in the liver and lung tissues of the microsphere preparation group were higher than those in the injection group,and the drug concentrations in the lung and liver tissues were more distributed.Conclusion:The targeted drug delivery system changed the pharmacokinetic behavior and tissue distribution of euphorbia sterol,slowed down plasma elimination,prolonged the half-life,and improved the targeting of drugs in lung and liver tissues and the magnetic targeting effect of lungs.展开更多
This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy dema...This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.展开更多
Rational distribution network planning optimizes power flow distribution,reduces grid stress,enhances voltage quality,promotes renewable energy utilization,and reduces costs.This study establishes a distribution netwo...Rational distribution network planning optimizes power flow distribution,reduces grid stress,enhances voltage quality,promotes renewable energy utilization,and reduces costs.This study establishes a distribution network planning model incorporating distributed wind turbines(DWT),distributed photovoltaics(DPV),and energy storage systems(ESS).K-means++is employed to partition the distribution network based on electrical distance.Considering the spatiotemporal correlation of distributed generation(DG)outputs in the same region,a joint output model of DWT and DPV is developed using the Frank-Copula.Due to the model’s high dimensionality,multiple constraints,and mixed-integer characteristics,bilevel programming theory is utilized to structure the model.The model is solved using a mixed-integer particle swarmoptimization algorithm(MIPSO)to determine the optimal location and capacity of DG and ESS integrated into the distribution network to achieve the best economic benefits and operation quality.The proposed bilevel planning method for distribution networks is validated through simulations on the modified IEEE 33-bus system.The results demonstrate significant improvements,with the proposedmethod reducing the annual comprehensive cost by 41.65%and 13.98%,respectively,compared to scenarios without DG and ESS or with only DG integration.Furthermore,it reduces the daily average voltage deviation by 24.35%and 10.24%and daily network losses by 55.72%and 35.71%.展开更多
The literature on multi-attribute optimization for renewable energy source(RES)placement in deregulated power markets is extensive and diverse in methodology.This study focuses on the most relevant publications direct...The literature on multi-attribute optimization for renewable energy source(RES)placement in deregulated power markets is extensive and diverse in methodology.This study focuses on the most relevant publications directly addressing the research problem at hand.Similarly,while the body of work on optimal location and sizing of renewable energy generators(REGs)in balanced distribution systems is substantial,only the most pertinent sources are cited,aligning closely with the study’s objective function.A comprehensive literature review reveals several key research areas:RES integration,RES-related optimization techniques,strategic placement of wind and solar generation,and RES promotion in deregulated powermarkets,particularly within transmission systems.Furthermore,the optimal location and sizing of REGs in both balanced and unbalanced distribution systems have been extensively studied.RESs demonstrate significant potential for standalone applications in remote areas lacking conventional transmission and distribution infrastructure.Also presents a thorough review of current modeling and optimization approaches for RES-based distribution system location and sizing.Additionally,it examines the optimal positioning,sizing,and performance of hybrid and standalone renewable energy systems.This paper provides a comprehensive review of current modeling and optimization approaches for the location and sizing of Renewable Energy Sources(RESs)in distribution systems,focusing on both balanced and unbalanced networks.展开更多
Addressing climate change and facilitating the large-scale integration of renewable energy sources(RESs)have driven the development of hydrogen-coupled integrated energy systems(HIES),which enhance energy sustainabili...Addressing climate change and facilitating the large-scale integration of renewable energy sources(RESs)have driven the development of hydrogen-coupled integrated energy systems(HIES),which enhance energy sustainability through coordinated electricity,thermal,natural gas,and hydrogen utilization.This study proposes a two-stage distributionally robust optimization(DRO)-based scheduling method to improve the economic efficiency and reduce carbon emissions of HIES.The framework incorporates a ladder-type carbon trading mechanism to regulate emissions and implements a demand response(DR)program to adjustflexible multi-energy loads,thereby prioritizing RES consumption.Uncertainties from RES generation and load demand are addressed through an ambiguity set,enabling robust decision-making.The column-and-constraint generation(C&CG)algorithm efficiently solves the two-stage DRO model.Case studies demonstrate that the proposed method reduces operational costs by 3.56%,increases photovoltaic consumption rates by 5.44%,and significantly lowers carbon emissions compared to conventional approaches.Furthermore,the DRO framework achieves a superior balance between conservativeness and robustness over conventional stochastic and robust optimization methods,highlighting its potential to advance cost-effective,low-carbon energy systems while ensuring grid stability under uncertainty.展开更多
Nitrogen(N)and phosphorus(P)are essential nutrients and can significantly impact primary productivity of the ecosystem causing water environmental problems.However,their cycling mechanisms are not well understood in a...Nitrogen(N)and phosphorus(P)are essential nutrients and can significantly impact primary productivity of the ecosystem causing water environmental problems.However,their cycling mechanisms are not well understood in alpine mountains with climate change.Hence,94 samples of river water were collected from 2018 to 2020 in the headwaters of the Shule River Basin to assess the nutrients spatiotemporal distribution and combined ap-proach of water quality index to assess water quality and potential sources.The findings depict that high nutrient concentrations were found to coincide with snowmelt and glacial meltwater and rainfall recharge periods,while total flux peaked from June to September due to increased runoff.Notably,total nitrogen(TN)concentrations were significantly higher near the town,primarily attributed to the replenishment of nitrate(NO_(3)^(‒)-N)from live-stock manure.The high total P(TP)was near the glacier,which was attributed to the transportation of glacial sediments into the river,and pH was another critical factor.N was the primary nutrient limiting factor for the growth of phytoplankton in river water.Although the migration and transport of nutrients have altered with climate change,river water quality is good in alpine mountains based on an overall evaluation.These findings contribute to enriching nutrient datasets and highlight the importance of water resource management and water quality assessment in sensitive and fragile alpine mountains.展开更多
Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the...Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the coordination with virtual power plants(VPPs).The proposed strategy improves systemflexibility and responsiveness by optimizing the power adjustment of flexible resources.In the proposed strategy,theGaussian Process Regression(GPR)is firstly employed to determine the adjustable range of aggregated power within the VPP,facilitating an assessment of its potential contribution to power supply support.Then,an optimal dispatch model based on a leader-follower game is developed to maximize the benefits of the VPP and flexible resources while guaranteeing the power balance at the same time.To solve the proposed optimal dispatch model efficiently,the constraints of the problem are reformulated and resolved using the Karush-Kuhn-Tucker(KKT)optimality conditions and linear programming duality theorem.The effectiveness of the strategy is illustrated through a detailed case study.展开更多
基金supported by the National Natural Science Foundation of China(Nos.51808158,52170101,and 52200116)Tianjin Natural Science Foundation(No.23JCYBJC00640).
文摘The electrochemical corrosion of ductile pipes(DPs)in drinking water distribution systems(DWDS)has a crucial impact on cement-mortar lining(CML)failure and metal release,potentially leading to drinking water quality deterioration and posing a risk to public health.An in-situ scanning vibrating electrode technique(SVET)with micron-scale resolution,microscopic scale detection and water quality analysis were used to investigate the corrosion behavior and metal release from DPs throughout the whole CML failure process.Metal pollutants release occurred at three different stages of CML failure process,and there are potential risks of water quality deterioration exceeding the maximum allowable levels set by national standards in the partial failure stage and lining peeling stage.Furthermore,the effects of water chemistry(Cl^(−),SO_(4)^(2−),NO_(3)−,and Ca^(2+))on corrosion scale growth and iron release activity,were investigated during the CML partial failure stage.Results showed that the CML failure process in DPs was accelerated by the autocatalysis of localized corrosion.Cl^(−)was found to damage the uncorroded metal surface,while SO_(4)^(2−)mainly dissolved the corrosion scale surface,increasing iron release.Both the oxidation of NO_(3)−and selective sedimentation of Ca2+were found to enhance the stability of corrosion scales and inhibit iron release.
基金supported by the Natural Science Foundation of China(No.52070145,51778453).
文摘The effects of disinfectants and plasmid-based antibiotic resistance genes(ARGs)on the growth of microorganisms and the plasmid-mediated transfer of ARGs in the water and biofilm of the drinkingwater distribution system under simulated conditionswere explored.The heterotrophic plate count of the water in reactors with 0.1 mg/L NaClO and NH_(2)Cl was higher than in the control groups.Therewas no similar phenomenon in biofilm.In thewater of reactors containing NaClO,the aphA and bla geneswere lower than in the antibiotic resistant bacteria group,while both genes were higher in the water of reactors with NH_(2)Cl than in the control group.Chloramine may promote the transfer of ARGs in the water phase.Both genes in the biofilm of the reactors containing chlorine were lower than the control group.Correlation analysis between ARGs and water quality parameters revealed that the copy numbers of the aphA gene were significantly positively correlated with the copy numbers of the bla gene in water and significantly negatively correlated in biofilm(p<0.05).The results of the sequencing assay showed that bacteria in the biofilm,in the presence of disinfectant,were primarily Gram-negative.1.0 mg/L chlorine decreased the diversity of the community in the biofilm.The relative abundance of some bacteria that may undergo transfer increased in the biofilm of the reactor containing 0.1 mg/L chlorine.
文摘Resilience studies for water distribution systems(WDS)coupled with other interdependent infrastructure systems attract increasing attention from stakeholders and researchers.However,most existing large-scale WDS models are single infrastructure-based without consideration of other infrastructure systems.This is due to a lack of needed information on systems coupling,the structure of the simulator used,and the computation load involved.To address these gaps,this paper presents a synthetic modeling framework for a real-world WDS as coordinating with other infrastructure systems via a building-mediated clustering approach through consideration of physical distance and node capacity.First,the WDS network topology and operation parameters are inferred via bulk open-source information.A building-mediated clustering approach is designed to systematically derive the interdependence between the WDS and the power system similarly created as a case study.Second,a novel linearization method is developed in formulating the WDS model that can relieve computation load while maintaining accuracy.Finally,a disruption-recovery framework is developed to demonstrate the proposed methodology in modelling WDS resilience.The framework is applied to a neighborhood in Queenstown,Singapore,an area of 20.43 km^(2) and 96,000 population.The near-real-time simulations on the coupled system involving 308 nodes and 384 links showcase the effectiveness and application of the proposed synthetic modeling and formulation.
文摘This paper introduces an optimized planning approach for integrating photovoltaic as distributed generation (PV-DG) into the radial distribution power systems, utilizing exhaustive load flow (ELF), loss sensitivity factor (LSF), genetic algorithms (GA) methods, and numerical method based on LSF. The methodology aims to determine the optimal allocation and sizing of multiple PV-DG to minimize power loss through time series power flow analysis. An approach utilizing continuous sensitivity analysis is developed and inherently leverages power flow and loss equations to compute LSF of all buses in the system towards employing a dynamic PV-DG model for more accurate results. The algorithm uses a numerical grid search method to optimize PV-DG placement in a power distribution system, focusing on minimizing system losses. It combines iterative analysis, sensitivity assessment, and comprehensive visualization to identify and present the optimal PV-DG configurations. The present-ed algorithms are verified through co-simulation framework combining MATLAB and OpenDSS to carry out analysis for 12-bus radial distribution test system. The proposed numerical method is compared with other algorithms, such as ELF, LSF methods, and Genetic Algorithms (GA). Results show that the proposed numerical method performs well in comparison with LSF and ELF solutions.
基金National Key R&D Program of China under Grant No.2022YFC3003600National Natural Science Foundation of China(NSFC)under Grant No.51978023。
文摘Due to uncertainties in seismic pipeline damage and post-earthquake recovery processes,probabilistic characteristics such as mean value,standard deviation,probability density function,and cumulative distribution function provide valuable information.In this study,a simulation-based framework to evaluate these probabilistic characteristics in water distribution systems(WDSs)during post-earthquake recovery is developed.The framework first calculates pipeline failure probabilities using seismic fragility models and then generates damage samples through quasi-Monte Carlo simulations with Sobol’s sequence for faster convergence.System performance is assessed using a hydraulic model,and recovery simulations produce time-varying performance curves,where the dynamic importance of unrepaired damage determines repair sequences.Finally,the probabilistic characteristics of seismic performance indicators,resilience index,resilience loss,and recovery time are evaluated.The framework is applied in two benchmark WDSs with different layouts to investigate the probabilistic characteristics of their seismic performance and resilience.Application results show that the cumulative distribution function reveals the variations in resilience indicators for different exceedance probabilities,and there are dramatic differences among the recovery times corresponding to the system performance recovery targets of 80%,90%,and 100%.
基金supported by the National Key Research and Development Program of China(2022YFE0114400).
文摘Toxoplasma gondii(T.gondii)is a globally distributed parasite that can infect a diversity of warm-blooded animals,including swine and humans.Infection in swine poses a considerable threat to food safety and public health.The aim of this meta-analysis was to estimate the seroprevalence of T.gondii infection in the swine population in China from 2000 to 2023 and to examine potential factors associated with infection.A total of 112 studies were included,collectively involving 145,152 swine samples originating from 26 provinces.The pooled seroprevalence was 26.0%(95%CI:23.3%–28.7%).Stratified analysis based on diagnostic methods revealed that studies using the indirect hemagglutination assay(IHA)reported a seroprevalence of 19.7%(95%CI:17.2%–22.2%),whereas those utilizing the enzyme-linked immunosorbent assay(ELISA)reported a higher seroprevalence of 35.5%(95%CI:29.1%–41.8%).Geographical analysis indicated higher seroprevalence in the South Central and Southwest regions,whereas the East and Northwest areas reported the lowest seroprevalence.Chongqing Province reported the highest seroprevalence,reaching 44.9%(95%CI:43.4%–46.0%),followed by Xinjiang,Hainan,and Guizhou,whereas the lowest was observed in Shandong Province(3.5%,95%CI:1.7%–6.1%).These findings provide important epidemiological evidence that can inform strategies for the prevention and control of T.gondii infection in swine populations,with a focus on high-risk populations and geographical areas.This imperative contributes substantially to the improvement of both food safety and public health.
基金supported in part by the European Regional Development Fund under Grant KK.01.1.1.01.0009(DATACROSS).
文摘This paper deals with reduction of losses in electric power distribution system through a dynamic reconfiguration case study of a grid in the city of Mostar,Bosnia and Herzegovina.The proposed solution is based on a nonlinear model predictive control algorithm which determines the optimal switching operations of the distribution system.The goal of the control algorithm is to find the optimal radial network topology which minimizes cumulative active power losses and maximizes voltages across the network while simultaneously satisfying all system constraints.The optimization results are validated through multiple simulations(using real power demand data collected for a few characteristic days during winter and summer)which demonstrate the efficiency and usefulness of the developed control algorithm in reducing the grid losses by up to 14%.
文摘Nodal pricing is a critical mechanism in electricity markets,utilized to determine the cost of power transmission to various nodes within a distribution network.As power systems evolve to incorporate higher levels of renewable energy and face increasing demand fluctuations,traditional nodal pricing models often fall short to meet these new challenges.This research introduces a novel enhanced nodal pricing mechanism for distribution networks,integrating advanced optimization techniques and hybrid models to overcome these limitations.The primary objective is to develop a model that not only improves pricing accuracy but also enhances operational efficiency and system reliability.This study leverages cutting-edge hybrid algorithms,combining elements of machine learning with conventional optimization methods,to achieve superior performance.Key findings demonstrate that the proposed hybrid nodal pricing model significantly reduces pricing errors and operational costs compared to conventional methods.Through extensive simulations and comparative analysis,the model exhibits enhanced performance under varying load conditions and increased levels of renewable energy integration.The results indicate a substantial improvement in pricing precision and network stability.This study contributes to the ongoing discourse on optimizing electricity market mechanisms and provides actionable insights for policymakers and utility operators.By addressing the complexities of modern power distribution systems,our research offers a robust solution that enhances the efficiency and reliability of power distribution networks,marking a significant advancement in the field.
文摘The majority of water utilities,particularly public service providers such as Gidole town,are struggling to deliver a sufficient and consistent supply of water in Ethiopia's developing towns.The primary objective of this study was to assess the hydraulic performance of water supply distribution system in Gidole Town,Ethiopia,a representative case of the challenges facing public water utilities in developing towns.The WaterGEMS v8i hydraulic model was utilized to simulate and evaluate the distribution network's performance.The system was configured as a looped network and analyzed against standard permitted pressure and velocity values in the distribution system.The model was effectively calibrated(coefficient of determination(R^(2))=0.969)using measured and observed pressure data.The model simulation run was conducted at peak and low hourly demand with 1.9 and 0.25 hourly factors,respectively.The estimated water demand of the town is 1284.3m^(3)/day(48.4 liters per capita per day),and it would be increased to 3099.77m^(3)/day(66.03 l/c/d)by the 2037 design period.The system experiences significant non-revenue water losses(75,434.11m^(3)/year),accounting for 29.9%of total water production;as a result,the present water supply coverage of the town is only 33.6%.Hydraulic simulations under peak and low demand scenarios revealed nodes with pressures outside the normal range,indicating system-wide inefficiencies.These findings highlight a combined issue of large physical losses and insufficient capacity of the water supply in the town,which is typical of many municipal systems in developing regions.The study concludes that strategic infrastructure rehabilitation,with an emphasis on pressure management and leak reduction,is not only a town necessity but a fundamental requirement for improving water security and financial sustainability for utilities in Ethiopia and similar contexts.The findings and methodology have been forwarded to town's water supply project and institutional development departments for immediate future implementation and provide a replicable framework for evidence-based investment and planning in other struggling municipalities in similar situations.
文摘As urban areas expand and water demand intensifies,the need for efficient and reliable water distribution systems becomes increasingly critical.A widely used infrastructure management approach involves partitioning water distribution networks(WDNs)into district metered areas(DMAs).However,suboptimal designs of DMA partitioning can lead to inefficiencies and increased costs.This study presents a core-peripheryinformed approach for DMA design that explicitly utilises the natural division between a densely connected core and a sparsely connected periphery.Incorporating this structural framework enhances network resilience,improves water pressure stability,and optimises boundary device placement.The proposed core-periphery-informed DMA design integrates hydraulic and topological analyses to identify central and peripheral network areas,applies a community structure detection algorithm conditioned by these areas,and uses an optimisation model to determine the optimal placement of boundary devices,enhancing network resilience and reducing costs.When applied to the Modena WDN in Italy,this approach demonstrates improved pressure stability and significant cost reductions compared to traditional methods.Overall,the findings highlight the practical benefits of the core-periphery-based DMA design,offering a scalable and data-driven solution for urban water distribution systems.
基金supported by the China Postdoctoral Science Foundation(No.2024M764171)the Postdoctoral Research Start-up Funds,China(No.AUGA5710027424)+1 种基金the National Natural Science Foundation of China(No.U2341237)the Development and construction funds for the School of Mechatronics Engineering of HIT,China(No.CBQQ8880103624)。
文摘Gas turbine rotors are complex dynamic systems with high-dimensional,discrete,and multi-source nonlinear coupling characteristics.Significant amounts of resources and time are spent during the process of solving dynamic characteristics.Therefore,it is necessary to design a lowdimensional model that can well reflect the dynamic characteristics of high-dimensional system.To build such a low-dimensional model,this study developed a dimensionality reduction method considering global order energy distribution by modifying the proper orthogonal decomposition theory.First,sensitivity analysis of key dimensionality reduction parameters to the energy distribution was conducted.Then a high-dimensional rotor-bearing system considering the nonlinear stiffness and oil film force was reduced,and the accuracy and the reusability of the low-dimensional model under different operating conditions were examined.Finally,the response results of a multi-disk rotor-bearing test bench were reduced using the proposed method,and spectrum results were then compared experimentally.Numerical and experimental results demonstrate that,during the dimensionality reduction process,the solution period of dynamic response results has the most significant influence on the accuracy of energy preservation.The transient signal in the transformation matrix mainly affects the high-order energy distribution of the rotor system.The larger the proportion of steady-state signals is,the closer the energy tends to accumulate towards lower orders.The low-dimensional rotor model accurately reflects the frequency response characteristics of the original high-dimensional system with an accuracy of up to 98%.The proposed dimensionality reduction method exhibits significant application potential in the dynamic analysis of highdimensional systems coupled with strong nonlinearities under variable operating conditions.
基金State Grid Jiangsu Electric Power Co.,Ltd.Technology Project(J2023121).
文摘With the continuous expansion of the power system scale and the increasing complexity of operational mode,the interaction between transmission and distribution systems is becoming more and more significant,placing higher requirements on the accuracy and efficiency of the power system state estimation to address the challenge of balancing computational efficiency and estimation accuracy in traditional coupled transmission and distribution state estimation methods,this paper proposes a collaborative state estimation method based on distribution systems state clustering and load model parameter identification.To resolve the scalability issue of coupled transmission and distribution power systems,clustering is first carried out based on the distribution system states.As the data and models of the transmission system and distribution systems are not shared.For the transmission system,equating the power transmitted from the transmission system to the distribution system is the same as equating the distribution system.Further,the power transmitted from the transmission system to different types of distribution systems is equivalent to different polynomial equivalent load models.Then,a parameter identification method is proposed to obtain the parameters of the equivalent load model.Finally,a transmission and distribution collaborative state estimation model is constructed based on the equivalent load model.The results of the numerical analysis show that compared with the traditional master-slave splitting method,the proposed method significantly enhances computational efficiency while maintaining high estimation accuracy.
基金supported by the Science and Technology Project of the State Grid Corporation of China(5400-202255158A-1-1-ZN).
文摘Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,the public network communication system is easily damaged after disasters,causing the operation center to lose control of the distribution network.In this paper,we considered using satellites to transmit the distribution network data and focus on the resource scheduling problem of the satellite emergency communication system for the distribution network.Specifically,this paper first formulates the satellite beam-pointing problem and the accesschannel joint resource allocation problem.Then,this paper proposes the Priority-based Beam-pointing and Access-Channel joint optimization algorithm(PBAC),which uses convex optimization theory to solve the satellite beam pointing problem,and adopts the block coordinate descent method,Lagrangian dual method,and a greedy algorithm to solve the access-channel joint resource allocation problem,thereby obtaining the optimal resource scheduling scheme for the satellite network.Finally,this paper conducts comparative experiments with existing methods to verify the effec-tiveness of the proposed methods.The results show that the total weighted transmitted data of the proposed algorithm is increased by about 19.29∼26.29%compared with other algorithms.
基金sponsored by the Fundamental Research Funds forthe Central Universities(No.2024-JYB-JBZD-047)High Level Key Discipline Construction of Traditional Chinese Medicine(zyyzdxk-2023272).
文摘Background:Building upon our previous work that developed a folate receptor-mediated,euphaorbia factor L1-loaded PLGA microsphere system integrating active and magnetic targeting for theranostics,further investigation into its in vivo pharmacokinetics and tissue distribution is warranted despite its demonstrated biocompatibility and safety.Methods:A UPLC-MS/MS method was established to determine the concentration of euphorbia sterol in rat plasma and mouse tissue homogenates,healthy male SD rats and KM mice were administered in groups,drug concentrations at different time points were determined,pharmacokinetic parameters were analyzed by DAS software,and data were processed by SAS software.Results:The proposed method met the requirements of biological sample detection.The plasma pharmacokinetics of rats showed that the drug concentration in the microsphere group was lower than that in the injection group,and the parameters such as mean residence time(MRT(0–t)),half-life(T1/2z)and apparent volume of distribution(Vz)were significantly different from those in the solution group.The distribution of mouse tissues showed that the drug concentrations in the liver and lung tissues of the microsphere preparation group were higher than those in the injection group,and the drug concentrations in the lung and liver tissues were more distributed.Conclusion:The targeted drug delivery system changed the pharmacokinetic behavior and tissue distribution of euphorbia sterol,slowed down plasma elimination,prolonged the half-life,and improved the targeting of drugs in lung and liver tissues and the magnetic targeting effect of lungs.
基金supported by the Scientific and Technological Research Council of Turkey(TUBITAK)under Grant No.124E002(1001-Project).
文摘This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.
基金This research was funded by“Chunhui Program”Collaborative Scientific Research Project of the Ministry of Education of the People’s Republic of China(Project No.HZKY20220242)the S&T Program of Hebei(Project No.225676163GH).
文摘Rational distribution network planning optimizes power flow distribution,reduces grid stress,enhances voltage quality,promotes renewable energy utilization,and reduces costs.This study establishes a distribution network planning model incorporating distributed wind turbines(DWT),distributed photovoltaics(DPV),and energy storage systems(ESS).K-means++is employed to partition the distribution network based on electrical distance.Considering the spatiotemporal correlation of distributed generation(DG)outputs in the same region,a joint output model of DWT and DPV is developed using the Frank-Copula.Due to the model’s high dimensionality,multiple constraints,and mixed-integer characteristics,bilevel programming theory is utilized to structure the model.The model is solved using a mixed-integer particle swarmoptimization algorithm(MIPSO)to determine the optimal location and capacity of DG and ESS integrated into the distribution network to achieve the best economic benefits and operation quality.The proposed bilevel planning method for distribution networks is validated through simulations on the modified IEEE 33-bus system.The results demonstrate significant improvements,with the proposedmethod reducing the annual comprehensive cost by 41.65%and 13.98%,respectively,compared to scenarios without DG and ESS or with only DG integration.Furthermore,it reduces the daily average voltage deviation by 24.35%and 10.24%and daily network losses by 55.72%and 35.71%.
文摘The literature on multi-attribute optimization for renewable energy source(RES)placement in deregulated power markets is extensive and diverse in methodology.This study focuses on the most relevant publications directly addressing the research problem at hand.Similarly,while the body of work on optimal location and sizing of renewable energy generators(REGs)in balanced distribution systems is substantial,only the most pertinent sources are cited,aligning closely with the study’s objective function.A comprehensive literature review reveals several key research areas:RES integration,RES-related optimization techniques,strategic placement of wind and solar generation,and RES promotion in deregulated powermarkets,particularly within transmission systems.Furthermore,the optimal location and sizing of REGs in both balanced and unbalanced distribution systems have been extensively studied.RESs demonstrate significant potential for standalone applications in remote areas lacking conventional transmission and distribution infrastructure.Also presents a thorough review of current modeling and optimization approaches for RES-based distribution system location and sizing.Additionally,it examines the optimal positioning,sizing,and performance of hybrid and standalone renewable energy systems.This paper provides a comprehensive review of current modeling and optimization approaches for the location and sizing of Renewable Energy Sources(RESs)in distribution systems,focusing on both balanced and unbalanced networks.
基金supported by National Key Research and Development Program(2024YFE0115600).
文摘Addressing climate change and facilitating the large-scale integration of renewable energy sources(RESs)have driven the development of hydrogen-coupled integrated energy systems(HIES),which enhance energy sustainability through coordinated electricity,thermal,natural gas,and hydrogen utilization.This study proposes a two-stage distributionally robust optimization(DRO)-based scheduling method to improve the economic efficiency and reduce carbon emissions of HIES.The framework incorporates a ladder-type carbon trading mechanism to regulate emissions and implements a demand response(DR)program to adjustflexible multi-energy loads,thereby prioritizing RES consumption.Uncertainties from RES generation and load demand are addressed through an ambiguity set,enabling robust decision-making.The column-and-constraint generation(C&CG)algorithm efficiently solves the two-stage DRO model.Case studies demonstrate that the proposed method reduces operational costs by 3.56%,increases photovoltaic consumption rates by 5.44%,and significantly lowers carbon emissions compared to conventional approaches.Furthermore,the DRO framework achieves a superior balance between conservativeness and robustness over conventional stochastic and robust optimization methods,highlighting its potential to advance cost-effective,low-carbon energy systems while ensuring grid stability under uncertainty.
基金supported by the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(No.2019QZKK0208)the National Natural Science Foundation of China(Nos.42171148 and 42330512)the Key R&D Project from the Science and Technology Department of Tibet(No.XZ202501ZY0030).
文摘Nitrogen(N)and phosphorus(P)are essential nutrients and can significantly impact primary productivity of the ecosystem causing water environmental problems.However,their cycling mechanisms are not well understood in alpine mountains with climate change.Hence,94 samples of river water were collected from 2018 to 2020 in the headwaters of the Shule River Basin to assess the nutrients spatiotemporal distribution and combined ap-proach of water quality index to assess water quality and potential sources.The findings depict that high nutrient concentrations were found to coincide with snowmelt and glacial meltwater and rainfall recharge periods,while total flux peaked from June to September due to increased runoff.Notably,total nitrogen(TN)concentrations were significantly higher near the town,primarily attributed to the replenishment of nitrate(NO_(3)^(‒)-N)from live-stock manure.The high total P(TP)was near the glacier,which was attributed to the transportation of glacial sediments into the river,and pH was another critical factor.N was the primary nutrient limiting factor for the growth of phytoplankton in river water.Although the migration and transport of nutrients have altered with climate change,river water quality is good in alpine mountains based on an overall evaluation.These findings contribute to enriching nutrient datasets and highlight the importance of water resource management and water quality assessment in sensitive and fragile alpine mountains.
基金supported by the Science and Technology Project of Sichuan Electric Power Company“Power Supply Guarantee Strategy for Urban Distribution Networks Considering Coordination with Virtual Power Plant during Extreme Weather Event”(No.521920230003).
文摘Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the coordination with virtual power plants(VPPs).The proposed strategy improves systemflexibility and responsiveness by optimizing the power adjustment of flexible resources.In the proposed strategy,theGaussian Process Regression(GPR)is firstly employed to determine the adjustable range of aggregated power within the VPP,facilitating an assessment of its potential contribution to power supply support.Then,an optimal dispatch model based on a leader-follower game is developed to maximize the benefits of the VPP and flexible resources while guaranteeing the power balance at the same time.To solve the proposed optimal dispatch model efficiently,the constraints of the problem are reformulated and resolved using the Karush-Kuhn-Tucker(KKT)optimality conditions and linear programming duality theorem.The effectiveness of the strategy is illustrated through a detailed case study.
