Based on the study of the relationship between structure and feedback of China’s natural gas demand system, this paper establishes a system dynamics model. In order to simulate the total demand and consumption struct...Based on the study of the relationship between structure and feedback of China’s natural gas demand system, this paper establishes a system dynamics model. In order to simulate the total demand and consumption structure of natural gas in China, we set up seven scenarios by changing some of the parameters of the model. The results showed that the total demand of natural gas would increase steadily year by year and reach in the range from 3600 to 4500 billion cubic meters in 2035. Furthermore, in terms of consumption structure, urban gas consumption would still be the largest term, followed by the gas consumption as industrial fuel, gas power generation and natural gas chemical industry. In addition, compared with the population growth, economic development still plays a dominant role in the natural gas demand growth, the impact of urbanization on urban gas consumption is significant, and the promotion of natural gas utilization technology can effectively reduce the total consumption of natural gas.展开更多
Using system analysis theory and methods, a dynamic model of a water resource supply and demand system was built to simulate trends in the supply and demand of water in the Changsha-Zhuzhou-Xiangtan （Chang-Zhu-Tan） ...Using system analysis theory and methods, a dynamic model of a water resource supply and demand system was built to simulate trends in the supply and demand of water in the Changsha-Zhuzhou-Xiangtan （Chang-Zhu-Tan） urban agglomeration for the period 2012 to 2030. Four scenarios were examined; namely, a traditional development model, an economic development model, a water-saving model, and a coordinated development model. （i） The problem of balancing water resource supply and demand is becoming increasingly conspicuous with a growing population and a rapidly developing economy. （ii） By 2030, water demand is set to reach a total of 105.1 × 10^8 m^3, with a water supply of 5.4 × 10^8 m^3. A coordinated development model for water resource supply could meet the growing demands of socio-economic development, and generate huge comprehensive benefits. This will be the best solution for the development and utilization of a water resource supply and demand system in the Chang-Zhu-Tan urban agglomeration. （iii） We should accelerate the construction of water conservation projects, strengthen the management of water conservation, optimize economic structures, enhance our awareness of the importance of protecting water resources, hasten the recycling of waste water and environmental improvement, and promote utilization efficiency, and support the capabilities of water resources to meet our expectations.展开更多
The main objective of this research is to estimate the different types of demand elasticities for the main fresh vegetables consumed in Jordan. The estimated elasticities can be used to measure the impacts of agricult...The main objective of this research is to estimate the different types of demand elasticities for the main fresh vegetables consumed in Jordan. The estimated elasticities can be used to measure the impacts of agricultural policies and can be used to predict future consumption in the context of food security in terms of access, availability, stability, and food quality. The reported demand estimates were obtained through the estimation of a Linear Approximate Almost Ideal Demand Systems （LA/AIDS） for Jordan fresh vegetable crops demand system using the most recent cross-sectional data of household expenditure survey in 2005. A censored regression method for the system of equations was used to analyze fresh vegetables consumption patterns. This method allows for inclusion of a large number of zero consumption for some foods through two-step demand system estimation. All of the own-price demand elasticities have the correct negative signs and statistically significant. According to the expenditure elasticity, tomato, cucumber, and potato are the necessity goods. The mean budget shares indicate that consumers spend 30 percent of their allocated budget to vegetables on tomatoes and potatoes. The green bean elasticity is the highest indicating that demand for beans is highly responsive to any changes in the price. The expenditure elasticities reveal that the demand on all vegetables is expected to grow over the coming few years. High own-price elasticities of all vegetables studied suggests that any changes in the prices of these crops could bring about a significant shift in fruits and vegetable constanption patterns.展开更多
By comparing China's import of major imported agriculture textile material( cotton and wool),the characteristics of import are concluded. On this basis,a restricted version of source differentiated almost ideal de...By comparing China's import of major imported agriculture textile material( cotton and wool),the characteristics of import are concluded. On this basis,a restricted version of source differentiated almost ideal demand system( RSDAIDS) is used to estimate the income and price elasticity of major imported agriculture textile material from the major sources based on the data from 1992 to 2015. The results are shown as follows.( 1) Although the dependency on imported cotton is lower than wool, the fluctuation of cotton import is much more drastic; China's demand for cotton is relatively price elastic with higher expenditure elasticity compared with wool; besides,the existence of complementarity is proved between imported cotton and wool.( 2) According to the import elasticity of cotton,demand for cotton imported from India shows priority over cotton from other sources; demand for cotton imported from America is the most price-sensitive one; substitution among cotton from different sources is weak.( 3) According to the import elasticity of wool,wool imported from Uruguay has bright market prospects. In addition,wool imported from Australia has irreplaceable advantage than that from New Zealand.展开更多
A test of the adding up condition in demand systems is crucial for determining whether a share format is admissible when the number of sample goods is smaller than the number of commodity choices available to consumer...A test of the adding up condition in demand systems is crucial for determining whether a share format is admissible when the number of sample goods is smaller than the number of commodity choices available to consumers. This test requires the estimation of a demand system in a quantity format. It cannot be performed when a demand system is specified in share format. The share specification of any demand system is like a straight jacket: once worn, it forces the error covariance matrix to be singular and the adding up condition to hold whether or not the data generating process warrants it. The empirical verification of the adding up hypothesis uses a five-commodity sample selected from the Canadian Family Expenditure Survey with 4847 observations. Three specifications are considered: AIDS (Almost Ideal Demand System), QUAIDS (Quadratic AIDS) and EASI (Exact Affine Stone Index). The hypothesis is rejected in all three cases with a high level of confidence.展开更多
The demand response(DR)market,as a vital complement to the electricity spot market,plays a key role in evoking user-side regulation capability to mitigate system-level supply‒demand imbalances during extreme events.Wh...The demand response(DR)market,as a vital complement to the electricity spot market,plays a key role in evoking user-side regulation capability to mitigate system-level supply‒demand imbalances during extreme events.While the DR market offers the load aggregator(LA)additional profitable opportunities beyond the electricity spot market,it also introduces new trading risks due to the significant uncertainty in users’behaviors.Dispatching energy storage systems(ESSs)is an effective means to enhance the risk management capabilities of LAs;however,coordinating ESS operations with dual-market trading strategies remains an urgent challenge.To this end,this paper proposes a novel systematic risk-aware coordinated trading model for the LA in concurrently participating in the day-ahead electricity spot market and DR market,which incorporates the capacity allocation mechanism of ESS based on market clearing rules to jointly formulate bidding and pricing decisions for the dual market.First,the intrinsic coupling characteristics of the LA participating in the dual market are analyzed,and a joint optimization framework for formulating bidding and pricing strategies that integrates ESS facilities is proposed.Second,an uncertain user response model is developed based on price‒response mechanisms,and actual market settlement rules accounting for under-and over-responses are employed to calculate trading revenues,where possible revenue losses are quantified via conditional value at risk.Third,by imposing these terms and the capacity allocation mechanism of ESS,the risk-aware stochastic coordinated trading model of the LA is built,where the bidding and pricing strategies in the dual model that trade off risk and profit are derived.The simulation results of a case study validate the effectiveness of the proposed trading strategy in controlling trading risk and improving the trading income of the LA.展开更多
Demand Side Management(DSM)is a vital issue in smart grids,given the time-varying user demand for electricity and power generation cost over a day.On the other hand,wireless communications with ubiquitous connectivity...Demand Side Management(DSM)is a vital issue in smart grids,given the time-varying user demand for electricity and power generation cost over a day.On the other hand,wireless communications with ubiquitous connectivity and low latency have emerged as a suitable option for smart grid.The design of any DSM system using a wireless network must consider the wireless link impairments,which is missing in existing literature.In this paper,we propose a DSM system using a Real-Time Pricing(RTP)mechanism and a wireless Neighborhood Area Network(NAN)with data transfer uncertainty.A Zigbee-based Internet of Things(IoT)model is considered for the communication infrastructure of the NAN.A sample NAN employing XBee and Raspberry Pi modules is also implemented in real-world settings to evaluate its reliability in transferring smart grid data over a wireless link.The proposed DSM system determines the optimal price corresponding to the optimum system welfare based on the two-way wireless communications among users,decision-makers,and energy providers.A novel cost function is adopted to reduce the impact of changes in user numbers on electricity prices.Simulation results indicate that the proposed system benefits users and energy providers.Furthermore,experimental results demonstrate that the success rate of data transfer significantly varies over the implemented wireless NAN,which can substantially impact the performance of the proposed DSM system.Further simulations are then carried out to quantify and analyze the impact of wireless communications on the electricity price,user welfare,and provider welfare.展开更多
Accurate prediction of nurse demand plays a crucial role in efficiently planning the healthcare workforce,ensuring appropriate staffing levels,and providing high-quality care to patients.The intricacy and variety of c...Accurate prediction of nurse demand plays a crucial role in efficiently planning the healthcare workforce,ensuring appropriate staffing levels,and providing high-quality care to patients.The intricacy and variety of contemporary healthcare systems and a growing patient populace call for advanced forecasting models.Factors like technological advancements,novel treatment protocols,and the increasing prevalence of chronic illnesses have diminished the efficacy of traditional estimation approaches.Novel forecasting methodologies,including time-series analysis,machine learning,and simulation-based techniques,have been developed to tackle these challenges.Time-series analysis recognizes patterns from past data,whereas machine learning uses extensive datasets to uncover concealed trends.Simulation models are employed to assess diverse scenarios,assisting in proactive adjustments to staffing.These techniques offer distinct advantages,such as the identification of seasonal patterns,the management of large datasets,and the ability to test various assumptions.By integrating these sophisticated models into workforce planning,organizations can optimize staffing,reduce financial waste,and elevate the standard of patient care.As the healthcare field progresses,the utilization of these predictive models will be pivotal for fostering adaptable and resilient workforce management.展开更多
With the advent of the digital economy,there has been a rapid proliferation of small-scale Internet data centers(SIDCs).By leveraging their spatiotemporal load regulation potential through data workload balancing,aggr...With the advent of the digital economy,there has been a rapid proliferation of small-scale Internet data centers(SIDCs).By leveraging their spatiotemporal load regulation potential through data workload balancing,aggregated SIDCs have emerged as promising demand response(DR)resources for future power distribution systems.This paper presents an innovative framework for assessing capacity value(CV)by aggregating SIDCs participating in DR programs(SIDC-DR).Initially,we delineate the concept of CV tailored for aggregated SIDC scenarios and establish a metric for the assessment.Considering the effects of the data load dynamics,equipment constraints,and user behavior,we developed a sophisticated DR model for aggregated SIDCs using a data network aggregation method.Unlike existing studies,the proposed model captures the uncertainties associated with end tenant decisions to opt into an SIDC-DR program by utilizing a novel uncertainty modeling approach called Z-number formulation.This approach accounts for both the uncertainty in user participation intentions and the reliability of basic information during the DR process,enabling high-resolution profiling of the SIDC-DR potential in the CV evaluation.Simulation results from numerical studies conducted on a modified IEEE-33 node distribution system confirmed the effectiveness of the proposed approach and highlighted the potential benefits of SIDC-DR utilization in the efficient operation of future power systems.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
To achieve the goals of sustainable development of the energy system and the construction of a lowcarbon society,this study proposes a multi-energy storage collaborative optimization strategy for industrial park that ...To achieve the goals of sustainable development of the energy system and the construction of a lowcarbon society,this study proposes a multi-energy storage collaborative optimization strategy for industrial park that integrates the laddered carbon trading mechanism with demand response.Firstly,a dual dimensional DR model is constructed based on the characteristics of load elasticity.The alternativeDRenables flexible substitution of energy loads through complementary conversion of electricity/heat/cold multi-energy sources,while the price DR relies on timeof-use electricity price signals to guide load spatiotemporal migration;Secondly,the LCT mechanism is introduced to achieve optimal carbon emission costs through a tiered carbon quota allocation mechanism.On this basis,an optimization decision model is established with the core objective of maximizing the annual net profit of the park.The objective function takes into account energy sales revenue,generator unit costs,and investment and operation costs of multiple types of energy storage facilities.Themodel constraint system covers three key dimensions:dynamic operation constraints of power generation units,including unit output limits,ramping capability,and minimum start-stop time;the physical boundary of an electric/hot/cold multi-energy storage system involves energy storage capacity and charge/discharge efficiency;The multi-energy network coupling balance equation ensures that the energy conversion and transmission process satisfies the law of conservation of energy.Using CPLEX mathematical programming solver for simulation verification,construct an energy storage capacity configuration decision process that includes LCT-DR synergistic effect.The research results show that compared with the traditional single energy storage configuration mode,this strategy effectively enhances the economic feasibility and engineering practicality of industrial park operation by coordinating demand side resource scheduling and finely controlling carbon costs,while maintaining stable system operation.Its methodological framework provides a technical path that combines theoretical rigor and practical operability for the low-carbon transformation of regional integrated energy systems.展开更多
This paper presents a copula technique to develop time-variant seismic fragility curves for corroded bridges at the system level and considers the realistic time-varying dependence among component seismic demands. Bas...This paper presents a copula technique to develop time-variant seismic fragility curves for corroded bridges at the system level and considers the realistic time-varying dependence among component seismic demands. Based on material deterioration mechanisms and incremental dynamic analysis, the time-evolving seismic demands of components were obtained in the form of marginal probability distributions. The time-varying dependences among bridge components were then captured with the best fitting copula function, which was selected from the commonly used copula classes by the empirical distribution based analysis method. The system time-variant fragility curves at different damage states were developed and the effects of time-varying dependences among components on the bridge system fragility were investigated. The results indicate the time-varying dependence among components significantly affects the time-variant fragility of the bridge system. The copula technique captures the nonlinear dependence among component seismic demands accurately and easily by separating the marginal distributions and the dependence among them.展开更多
The integrated energy system(IES)is an important energy supply method for mitigating the energy crisis.A station-and-network–coordinated planning method for the IES,which considers the integrated demand responses(IDR...The integrated energy system(IES)is an important energy supply method for mitigating the energy crisis.A station-and-network–coordinated planning method for the IES,which considers the integrated demand responses(IDRs)of flexible loads,electric vehicles,and energy storage is proposed in this work.First,based on load substitution at the user side,an energy-station model considering the IDR is established.Then,based on the characteristics of the energy network,a collaborative planning model is established for the energy station and energy network of the IES,considering the comprehensive system investment,operation and maintenance,and clean energy shortage penalty costs,to minimize the total cost.This can help optimize the locations of the power lines and natural gas pipelines and the capacities of the equipment in an energy station.Finally,simulations are performed to demonstrate that the proposed planning method can help delay or reduce the construction of new lines and energy-station equipment,thereby reducing the investment required and improving the planning economics of the IES.展开更多
Cyber physical systems（CPS） recently emerge as a new technology which can provide promising approaches to demand side management（DSM）, an important capability in industrial power systems. Meanwhile, the manufactur...Cyber physical systems（CPS） recently emerge as a new technology which can provide promising approaches to demand side management（DSM）, an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufac^ring center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.展开更多
The ecological water demand (EWD) is the least water amount required to maintain the structure and the function of the special eco-system and the temporal scale of a study on the EWD must be a season's time. Based...The ecological water demand (EWD) is the least water amount required to maintain the structure and the function of the special eco-system and the temporal scale of a study on the EWD must be a season's time. Based on GIS and RS with the source information of hydrological data of 46 hydrological gauges covering 52 years and the digital images of Landsat TM in 1986, 1996 and 2000, the landscape patterns, precipitation and runoff in the East Liaohe River Basin were analyzed. With the result of the above analysis, the spatial and temporal changes of the ecological water demand in the slope systems (EWDSS) of the East Liaohe River Basin (ELRB) were derived. Landscapes in the ELRB are dispersed and strongly disturbed by human actions. The hydrological regime in ELRB has distinct spatial variations. The average annual EWDSS in the ELRB is 504.72 mm (324.08-618.89 mm), and the average EWDSS in the growth season (from May to September) is 88.29% of the year's total EWDSS .The ultimate guaranteeing ratio of the EWDSS in ELRB is 90%. The scarce EWDSS area in the whole year and in the growth season are 60.47% and 74.01% of the entire basin respectively. The trend of scarce EWDSS area is most serious according to the quantity and area of scarce EWDSS regions.展开更多
Global urbanization has led to drastic land use change,interfering the ecosystem services(ES)supply-demand balance,in turn threatening the well-being of humans.However,existing studies mainly stranded at the historica...Global urbanization has led to drastic land use change,interfering the ecosystem services(ES)supply-demand balance,in turn threatening the well-being of humans.However,existing studies mainly stranded at the historical and current analysis,and the effects of urban spatial expansion on the relationship between ES supply and demand in the future are less clear,in particular at an urban agglomeration scale.This study was constructed with a framework of assessing the effects of urban spatial expansion on ES supply-demand mismatching under different future scenarios in the Guanzhong Plain Urban Agglomeration(GPUA)by using the Future Land Use Simulation(FLUS)model and expert-based Land-Use and Land-Cover Change(LUCC)matrix.The results showed that:(1)Urban expansion is significant in the natural development(ND)scenario,mainly manifesting the great transfer of dry land to construction land.(2)The gap between total ES supply and demand is narrowed from 2000 to 2030 and the mismatch between ES supply and demand is mainly reflected in the spatial distribution pattern in the GPUA.The ES budgets were in high surplus in Northern Qinling Mountains and northeast mountain areas,while they were in severe deficit in urban center areas.The budgets deficit under the ND scenario in 2030 is the most severe.(3)The gradient differences of ES budgets of the GPUA between urban centers and suburbs increase from 2000 to 2030 under two scenarios.The deficit region expands largest under ND scenario.The findings revealed that ES declining and supply-demand mismatching were triggered by the drastic land-use change driven by rapid urban expansion.The expansion has brought about an increasing material demand and growing industries,threatening the sustainability of ecosystems.Scenarios setting could contribute to coordinating the relationship between future urban development and ecological protection,and the policy strategies proposed in the study could inform ecological management and urban planning in the regions facing the similar urbanization situation.展开更多
The relationship between the supply and demand for ecosystem services(ESs)is a key issue for the rational allocation of natural resources and optimisation of sustainable development capacity.This paper investigateed t...The relationship between the supply and demand for ecosystem services(ESs)is a key issue for the rational allocation of natural resources and optimisation of sustainable development capacity.This paper investigateed the dynamic evolution features of supply and demand of four ESs in Lanzhou of China,namely,water supply,food supply,carbon fixation and soil retention services.The crosssectional data of 2005 and 2017 were used for calculating ESs value and its supply and demand through ArcGIS software,InVEST model,elastic coefficient model and coupling coordination model.Results showed that:1)from 2005 to 2017,the supply of water supply services increased,the demand of soil retention services decreased,and the supply and demand of food supply and carbon fixation services increased.The high-value areas of service supply were mainly distributed in the rocky mountain areas in the southeast and northwest with high vegetation coverage,while the high-value areas of demand were mainly distributed in the urban areas and surrounding areas with high population density.2)There were five different types of coupling relations.Water supply service was dominated by a negative coupling type D,which means that the decrease in demand for ESs has had a positive response on the supply of ESs.Negative coupling type C was the main type of food supply and carbon fixation services,which means that the increase in demand for ESs has had a negative response on the supply of ESs.All three services were supplemented by a positive coupling type A,which means that the increase in demand for ESs has had a positive response on the supply of ESs.Soil retention service generally exhibits a positive coupling type B,which means that the decrease in demand for ESs has had a negative response on the supply of ESs.3)Over the past 12 yr,the coordination degree of supply and demand of water supply,food supply and soil retention services decreased,and the coordination degree of carbon fixation service increased.Various types of ES had a low degree of coupling and coordination,showing different characteristics of temporal and spatial evolution.The areas with imbalanced ESs supply and demand were mainly distributed in urban areas dominated by construction land.The research results are valuable to the optimisation of urban and rural ecological environments and the sustainable development of territory space under the framework of ecological civilisation,including similar ecologically vulnerable areas in other developing countries.展开更多
Electric system planning with high variable renewable energy(VRE)penetration levels has attracted great attention world-wide.Electricity production of VRE highly depends on the weather conditions and thus involves lar...Electric system planning with high variable renewable energy(VRE)penetration levels has attracted great attention world-wide.Electricity production of VRE highly depends on the weather conditions and thus involves large variability,uncertainty,and low-capacity credit.This gives rise to significant challenges for power system planning.Currently,many solutions are proposed to address the issue of operational flexibility inadequacy,including flexibility retrofit of thermal units,inter-regional transmission,electricity energy storage,and demand response(DR).Evidently,the performance and the cost of various solutions are different.It is relevant to explore the optimal portfolio to satisfy the flexibility requirement for a renewable dominated system and the role of each flexibility source.In this study,the value of diverse DR flexibilities was examined and a stochastic investment planning model considering DR is proposed.Two types of DRs,namely interrupted DR and transferred DR,were modeled.Chronological load and renewable generation curves with 8760 hours within a whole year were reduced to 4 weekly scenarios to accelerate the optimization.Clustered unit commitment constraints for accommodating variability of renewables were incorporated.Case studies based on IEEE RTS-96 system are reported to demonstrate the effectiveness of the proposed method and the DR potential to avoid energy storage investment.展开更多
Accurate origin–destination(OD)demand prediction is crucial for the efficient operation and management of urban rail transit(URT)systems,particularly during a pandemic.However,this task faces several limitations,incl...Accurate origin–destination(OD)demand prediction is crucial for the efficient operation and management of urban rail transit(URT)systems,particularly during a pandemic.However,this task faces several limitations,including real-time availability,sparsity,and high-dimensionality issues,and the impact of the pandemic.Consequently,this study proposes a unified framework called the physics-guided adaptive graph spatial–temporal attention network(PAG-STAN)for metro OD demand prediction under pandemic conditions.Specifically,PAG-STAN introduces a real-time OD estimation module to estimate real-time complete OD demand matrices.Subsequently,a novel dynamic OD demand matrix compression module is proposed to generate dense real-time OD demand matrices.Thereafter,PAG-STAN leverages various heterogeneous data to learn the evolutionary trend of future OD ridership during the pandemic.Finally,a masked physics-guided loss function(MPG-loss function)incorporates the physical quantity information between the OD demand and inbound flow into the loss function to enhance model interpretability.PAG-STAN demonstrated favorable performance on two real-world metro OD demand datasets under the pandemic and conventional scenarios,highlighting its robustness and sensitivity for metro OD demand prediction.A series of ablation studies were conducted to verify the indispensability of each module in PAG-STAN.展开更多
The spatial relationships between traffic accessibility and supply and demand(S&D)of ecosystem services(ESs)are essential for the formulation of ecological compensation policies and ESs regulation.In this study,an...The spatial relationships between traffic accessibility and supply and demand(S&D)of ecosystem services(ESs)are essential for the formulation of ecological compensation policies and ESs regulation.In this study,an ESs matrix and coupling analysis method were used to assess ESs S&D based on land-use data for 2000,2010,and 2020,and spatial regression models were used to analyze the correlated impacts of traffic accessibility.The results showed that the ESs supply and balance index in the middle reaches of the Yangtze River urban agglomeration(MRYRUA)continuously decreased,while the demand index increased from 2000 to 2020.The Gini coefficients of these indices continued to increase but did not exceed the warning value(0.4).The coupling degree of ESs S&D continued to increase,and its spatial distribution patterns were similar to that of the ESs demand index,with significantly higher values in the plains than in the montane areas,contrasting with those of the ESs supply index.The results of global bivariate Moran’s I analysis showed a significant spatial dependence between traffic accessibility and the degree of coupling between ESs S&D;the spatial regression results showed that an increase in traffic accessibility promoted the coupling degree.The present results provide a new perspective on the relationship between traffic accessibility and the coupling degree of ESs S&D,representing a case study for similar future research in other regions,and a reference for policy creation based on the matching between ESs S&D in the MRYRUA.展开更多
基金financially supported by the National Natural Science Foundation of China (Grant Nos. 71273021 and 7167030506)
文摘Based on the study of the relationship between structure and feedback of China’s natural gas demand system, this paper establishes a system dynamics model. In order to simulate the total demand and consumption structure of natural gas in China, we set up seven scenarios by changing some of the parameters of the model. The results showed that the total demand of natural gas would increase steadily year by year and reach in the range from 3600 to 4500 billion cubic meters in 2035. Furthermore, in terms of consumption structure, urban gas consumption would still be the largest term, followed by the gas consumption as industrial fuel, gas power generation and natural gas chemical industry. In addition, compared with the population growth, economic development still plays a dominant role in the natural gas demand growth, the impact of urbanization on urban gas consumption is significant, and the promotion of natural gas utilization technology can effectively reduce the total consumption of natural gas.
基金National Social Science Foundation of China, No. 15BJY051 Social Science Foundation of Hunan Province, No. 13YBA016 Science ＆ Technology Research Project of the Department of Land and Resource of Hunan Province, No.2014-13
文摘Using system analysis theory and methods, a dynamic model of a water resource supply and demand system was built to simulate trends in the supply and demand of water in the Changsha-Zhuzhou-Xiangtan （Chang-Zhu-Tan） urban agglomeration for the period 2012 to 2030. Four scenarios were examined; namely, a traditional development model, an economic development model, a water-saving model, and a coordinated development model. （i） The problem of balancing water resource supply and demand is becoming increasingly conspicuous with a growing population and a rapidly developing economy. （ii） By 2030, water demand is set to reach a total of 105.1 × 10^8 m^3, with a water supply of 5.4 × 10^8 m^3. A coordinated development model for water resource supply could meet the growing demands of socio-economic development, and generate huge comprehensive benefits. This will be the best solution for the development and utilization of a water resource supply and demand system in the Chang-Zhu-Tan urban agglomeration. （iii） We should accelerate the construction of water conservation projects, strengthen the management of water conservation, optimize economic structures, enhance our awareness of the importance of protecting water resources, hasten the recycling of waste water and environmental improvement, and promote utilization efficiency, and support the capabilities of water resources to meet our expectations.
文摘The main objective of this research is to estimate the different types of demand elasticities for the main fresh vegetables consumed in Jordan. The estimated elasticities can be used to measure the impacts of agricultural policies and can be used to predict future consumption in the context of food security in terms of access, availability, stability, and food quality. The reported demand estimates were obtained through the estimation of a Linear Approximate Almost Ideal Demand Systems （LA/AIDS） for Jordan fresh vegetable crops demand system using the most recent cross-sectional data of household expenditure survey in 2005. A censored regression method for the system of equations was used to analyze fresh vegetables consumption patterns. This method allows for inclusion of a large number of zero consumption for some foods through two-step demand system estimation. All of the own-price demand elasticities have the correct negative signs and statistically significant. According to the expenditure elasticity, tomato, cucumber, and potato are the necessity goods. The mean budget shares indicate that consumers spend 30 percent of their allocated budget to vegetables on tomatoes and potatoes. The green bean elasticity is the highest indicating that demand for beans is highly responsive to any changes in the price. The expenditure elasticities reveal that the demand on all vegetables is expected to grow over the coming few years. High own-price elasticities of all vegetables studied suggests that any changes in the prices of these crops could bring about a significant shift in fruits and vegetable constanption patterns.
基金Industrial Research of National Wool and Csahmere Industry Technology System,China(No.CARS-40-20)
文摘By comparing China's import of major imported agriculture textile material( cotton and wool),the characteristics of import are concluded. On this basis,a restricted version of source differentiated almost ideal demand system( RSDAIDS) is used to estimate the income and price elasticity of major imported agriculture textile material from the major sources based on the data from 1992 to 2015. The results are shown as follows.( 1) Although the dependency on imported cotton is lower than wool, the fluctuation of cotton import is much more drastic; China's demand for cotton is relatively price elastic with higher expenditure elasticity compared with wool; besides,the existence of complementarity is proved between imported cotton and wool.( 2) According to the import elasticity of cotton,demand for cotton imported from India shows priority over cotton from other sources; demand for cotton imported from America is the most price-sensitive one; substitution among cotton from different sources is weak.( 3) According to the import elasticity of wool,wool imported from Uruguay has bright market prospects. In addition,wool imported from Australia has irreplaceable advantage than that from New Zealand.
文摘A test of the adding up condition in demand systems is crucial for determining whether a share format is admissible when the number of sample goods is smaller than the number of commodity choices available to consumers. This test requires the estimation of a demand system in a quantity format. It cannot be performed when a demand system is specified in share format. The share specification of any demand system is like a straight jacket: once worn, it forces the error covariance matrix to be singular and the adding up condition to hold whether or not the data generating process warrants it. The empirical verification of the adding up hypothesis uses a five-commodity sample selected from the Canadian Family Expenditure Survey with 4847 observations. Three specifications are considered: AIDS (Almost Ideal Demand System), QUAIDS (Quadratic AIDS) and EASI (Exact Affine Stone Index). The hypothesis is rejected in all three cases with a high level of confidence.
基金supported by National Natural Science Foundation of China(52407126).
文摘The demand response(DR)market,as a vital complement to the electricity spot market,plays a key role in evoking user-side regulation capability to mitigate system-level supply‒demand imbalances during extreme events.While the DR market offers the load aggregator(LA)additional profitable opportunities beyond the electricity spot market,it also introduces new trading risks due to the significant uncertainty in users’behaviors.Dispatching energy storage systems(ESSs)is an effective means to enhance the risk management capabilities of LAs;however,coordinating ESS operations with dual-market trading strategies remains an urgent challenge.To this end,this paper proposes a novel systematic risk-aware coordinated trading model for the LA in concurrently participating in the day-ahead electricity spot market and DR market,which incorporates the capacity allocation mechanism of ESS based on market clearing rules to jointly formulate bidding and pricing decisions for the dual market.First,the intrinsic coupling characteristics of the LA participating in the dual market are analyzed,and a joint optimization framework for formulating bidding and pricing strategies that integrates ESS facilities is proposed.Second,an uncertain user response model is developed based on price‒response mechanisms,and actual market settlement rules accounting for under-and over-responses are employed to calculate trading revenues,where possible revenue losses are quantified via conditional value at risk.Third,by imposing these terms and the capacity allocation mechanism of ESS,the risk-aware stochastic coordinated trading model of the LA is built,where the bidding and pricing strategies in the dual model that trade off risk and profit are derived.The simulation results of a case study validate the effectiveness of the proposed trading strategy in controlling trading risk and improving the trading income of the LA.
文摘Demand Side Management(DSM)is a vital issue in smart grids,given the time-varying user demand for electricity and power generation cost over a day.On the other hand,wireless communications with ubiquitous connectivity and low latency have emerged as a suitable option for smart grid.The design of any DSM system using a wireless network must consider the wireless link impairments,which is missing in existing literature.In this paper,we propose a DSM system using a Real-Time Pricing(RTP)mechanism and a wireless Neighborhood Area Network(NAN)with data transfer uncertainty.A Zigbee-based Internet of Things(IoT)model is considered for the communication infrastructure of the NAN.A sample NAN employing XBee and Raspberry Pi modules is also implemented in real-world settings to evaluate its reliability in transferring smart grid data over a wireless link.The proposed DSM system determines the optimal price corresponding to the optimum system welfare based on the two-way wireless communications among users,decision-makers,and energy providers.A novel cost function is adopted to reduce the impact of changes in user numbers on electricity prices.Simulation results indicate that the proposed system benefits users and energy providers.Furthermore,experimental results demonstrate that the success rate of data transfer significantly varies over the implemented wireless NAN,which can substantially impact the performance of the proposed DSM system.Further simulations are then carried out to quantify and analyze the impact of wireless communications on the electricity price,user welfare,and provider welfare.
文摘Accurate prediction of nurse demand plays a crucial role in efficiently planning the healthcare workforce,ensuring appropriate staffing levels,and providing high-quality care to patients.The intricacy and variety of contemporary healthcare systems and a growing patient populace call for advanced forecasting models.Factors like technological advancements,novel treatment protocols,and the increasing prevalence of chronic illnesses have diminished the efficacy of traditional estimation approaches.Novel forecasting methodologies,including time-series analysis,machine learning,and simulation-based techniques,have been developed to tackle these challenges.Time-series analysis recognizes patterns from past data,whereas machine learning uses extensive datasets to uncover concealed trends.Simulation models are employed to assess diverse scenarios,assisting in proactive adjustments to staffing.These techniques offer distinct advantages,such as the identification of seasonal patterns,the management of large datasets,and the ability to test various assumptions.By integrating these sophisticated models into workforce planning,organizations can optimize staffing,reduce financial waste,and elevate the standard of patient care.As the healthcare field progresses,the utilization of these predictive models will be pivotal for fostering adaptable and resilient workforce management.
基金supported in part by the National Natural Science Foundation of China under Grant 52177082in part by the Beijing Nova Program under Grant 20220484007.
文摘With the advent of the digital economy,there has been a rapid proliferation of small-scale Internet data centers(SIDCs).By leveraging their spatiotemporal load regulation potential through data workload balancing,aggregated SIDCs have emerged as promising demand response(DR)resources for future power distribution systems.This paper presents an innovative framework for assessing capacity value(CV)by aggregating SIDCs participating in DR programs(SIDC-DR).Initially,we delineate the concept of CV tailored for aggregated SIDC scenarios and establish a metric for the assessment.Considering the effects of the data load dynamics,equipment constraints,and user behavior,we developed a sophisticated DR model for aggregated SIDCs using a data network aggregation method.Unlike existing studies,the proposed model captures the uncertainties associated with end tenant decisions to opt into an SIDC-DR program by utilizing a novel uncertainty modeling approach called Z-number formulation.This approach accounts for both the uncertainty in user participation intentions and the reliability of basic information during the DR process,enabling high-resolution profiling of the SIDC-DR potential in the CV evaluation.Simulation results from numerical studies conducted on a modified IEEE-33 node distribution system confirmed the effectiveness of the proposed approach and highlighted the potential benefits of SIDC-DR utilization in the efficient operation of future power systems.
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funded by Science and Technology Projects from State Grid Corporation of China,(Research on Adaptive Balance Optimization and Simulation Technology of Industrial community Energy System with High Proportion of Distributed Energy,No.:5100-202355752A-3-4-SY).
文摘To achieve the goals of sustainable development of the energy system and the construction of a lowcarbon society,this study proposes a multi-energy storage collaborative optimization strategy for industrial park that integrates the laddered carbon trading mechanism with demand response.Firstly,a dual dimensional DR model is constructed based on the characteristics of load elasticity.The alternativeDRenables flexible substitution of energy loads through complementary conversion of electricity/heat/cold multi-energy sources,while the price DR relies on timeof-use electricity price signals to guide load spatiotemporal migration;Secondly,the LCT mechanism is introduced to achieve optimal carbon emission costs through a tiered carbon quota allocation mechanism.On this basis,an optimization decision model is established with the core objective of maximizing the annual net profit of the park.The objective function takes into account energy sales revenue,generator unit costs,and investment and operation costs of multiple types of energy storage facilities.Themodel constraint system covers three key dimensions:dynamic operation constraints of power generation units,including unit output limits,ramping capability,and minimum start-stop time;the physical boundary of an electric/hot/cold multi-energy storage system involves energy storage capacity and charge/discharge efficiency;The multi-energy network coupling balance equation ensures that the energy conversion and transmission process satisfies the law of conservation of energy.Using CPLEX mathematical programming solver for simulation verification,construct an energy storage capacity configuration decision process that includes LCT-DR synergistic effect.The research results show that compared with the traditional single energy storage configuration mode,this strategy effectively enhances the economic feasibility and engineering practicality of industrial park operation by coordinating demand side resource scheduling and finely controlling carbon costs,while maintaining stable system operation.Its methodological framework provides a technical path that combines theoretical rigor and practical operability for the low-carbon transformation of regional integrated energy systems.
基金Natural Science Foundation of China under Grant No.51808376
文摘This paper presents a copula technique to develop time-variant seismic fragility curves for corroded bridges at the system level and considers the realistic time-varying dependence among component seismic demands. Based on material deterioration mechanisms and incremental dynamic analysis, the time-evolving seismic demands of components were obtained in the form of marginal probability distributions. The time-varying dependences among bridge components were then captured with the best fitting copula function, which was selected from the commonly used copula classes by the empirical distribution based analysis method. The system time-variant fragility curves at different damage states were developed and the effects of time-varying dependences among components on the bridge system fragility were investigated. The results indicate the time-varying dependence among components significantly affects the time-variant fragility of the bridge system. The copula technique captures the nonlinear dependence among component seismic demands accurately and easily by separating the marginal distributions and the dependence among them.
基金supported in part by the National Key R&D Program of China(2018YFB0905000)the Science and Technology Project of the State Grid Corporation of China(SGTJDK00DWJS1800232)
文摘The integrated energy system(IES)is an important energy supply method for mitigating the energy crisis.A station-and-network–coordinated planning method for the IES,which considers the integrated demand responses(IDRs)of flexible loads,electric vehicles,and energy storage is proposed in this work.First,based on load substitution at the user side,an energy-station model considering the IDR is established.Then,based on the characteristics of the energy network,a collaborative planning model is established for the energy station and energy network of the IES,considering the comprehensive system investment,operation and maintenance,and clean energy shortage penalty costs,to minimize the total cost.This can help optimize the locations of the power lines and natural gas pipelines and the capacities of the equipment in an energy station.Finally,simulations are performed to demonstrate that the proposed planning method can help delay or reduce the construction of new lines and energy-station equipment,thereby reducing the investment required and improving the planning economics of the IES.
基金Supported by National Natural Science Foundation of China(Grant No.61272428)PhD Programs Foundation of Ministry of Education of China(Grant No.20120002110067)
文摘Cyber physical systems（CPS） recently emerge as a new technology which can provide promising approaches to demand side management（DSM）, an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufac^ring center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.
基金Key Resource and Environment Projects of CAS,No.KZ952-J1-067
文摘The ecological water demand (EWD) is the least water amount required to maintain the structure and the function of the special eco-system and the temporal scale of a study on the EWD must be a season's time. Based on GIS and RS with the source information of hydrological data of 46 hydrological gauges covering 52 years and the digital images of Landsat TM in 1986, 1996 and 2000, the landscape patterns, precipitation and runoff in the East Liaohe River Basin were analyzed. With the result of the above analysis, the spatial and temporal changes of the ecological water demand in the slope systems (EWDSS) of the East Liaohe River Basin (ELRB) were derived. Landscapes in the ELRB are dispersed and strongly disturbed by human actions. The hydrological regime in ELRB has distinct spatial variations. The average annual EWDSS in the ELRB is 504.72 mm (324.08-618.89 mm), and the average EWDSS in the growth season (from May to September) is 88.29% of the year's total EWDSS .The ultimate guaranteeing ratio of the EWDSS in ELRB is 90%. The scarce EWDSS area in the whole year and in the growth season are 60.47% and 74.01% of the entire basin respectively. The trend of scarce EWDSS area is most serious according to the quantity and area of scarce EWDSS regions.
基金National Natural Science Foundation of China,No.41871187Natural Science Basic Research Plan in Shaanxi Province of China,No.2020JQ415。
文摘Global urbanization has led to drastic land use change,interfering the ecosystem services(ES)supply-demand balance,in turn threatening the well-being of humans.However,existing studies mainly stranded at the historical and current analysis,and the effects of urban spatial expansion on the relationship between ES supply and demand in the future are less clear,in particular at an urban agglomeration scale.This study was constructed with a framework of assessing the effects of urban spatial expansion on ES supply-demand mismatching under different future scenarios in the Guanzhong Plain Urban Agglomeration(GPUA)by using the Future Land Use Simulation(FLUS)model and expert-based Land-Use and Land-Cover Change(LUCC)matrix.The results showed that:(1)Urban expansion is significant in the natural development(ND)scenario,mainly manifesting the great transfer of dry land to construction land.(2)The gap between total ES supply and demand is narrowed from 2000 to 2030 and the mismatch between ES supply and demand is mainly reflected in the spatial distribution pattern in the GPUA.The ES budgets were in high surplus in Northern Qinling Mountains and northeast mountain areas,while they were in severe deficit in urban center areas.The budgets deficit under the ND scenario in 2030 is the most severe.(3)The gradient differences of ES budgets of the GPUA between urban centers and suburbs increase from 2000 to 2030 under two scenarios.The deficit region expands largest under ND scenario.The findings revealed that ES declining and supply-demand mismatching were triggered by the drastic land-use change driven by rapid urban expansion.The expansion has brought about an increasing material demand and growing industries,threatening the sustainability of ecosystems.Scenarios setting could contribute to coordinating the relationship between future urban development and ecological protection,and the policy strategies proposed in the study could inform ecological management and urban planning in the regions facing the similar urbanization situation.
基金Under the auspices of National Natural Science Foundation of China(No.41861034)。
文摘The relationship between the supply and demand for ecosystem services(ESs)is a key issue for the rational allocation of natural resources and optimisation of sustainable development capacity.This paper investigateed the dynamic evolution features of supply and demand of four ESs in Lanzhou of China,namely,water supply,food supply,carbon fixation and soil retention services.The crosssectional data of 2005 and 2017 were used for calculating ESs value and its supply and demand through ArcGIS software,InVEST model,elastic coefficient model and coupling coordination model.Results showed that:1)from 2005 to 2017,the supply of water supply services increased,the demand of soil retention services decreased,and the supply and demand of food supply and carbon fixation services increased.The high-value areas of service supply were mainly distributed in the rocky mountain areas in the southeast and northwest with high vegetation coverage,while the high-value areas of demand were mainly distributed in the urban areas and surrounding areas with high population density.2)There were five different types of coupling relations.Water supply service was dominated by a negative coupling type D,which means that the decrease in demand for ESs has had a positive response on the supply of ESs.Negative coupling type C was the main type of food supply and carbon fixation services,which means that the increase in demand for ESs has had a negative response on the supply of ESs.All three services were supplemented by a positive coupling type A,which means that the increase in demand for ESs has had a positive response on the supply of ESs.Soil retention service generally exhibits a positive coupling type B,which means that the decrease in demand for ESs has had a negative response on the supply of ESs.3)Over the past 12 yr,the coordination degree of supply and demand of water supply,food supply and soil retention services decreased,and the coordination degree of carbon fixation service increased.Various types of ES had a low degree of coupling and coordination,showing different characteristics of temporal and spatial evolution.The areas with imbalanced ESs supply and demand were mainly distributed in urban areas dominated by construction land.The research results are valuable to the optimisation of urban and rural ecological environments and the sustainable development of territory space under the framework of ecological civilisation,including similar ecologically vulnerable areas in other developing countries.
基金jointly supported by Youth Program of National Natural Science Foundation of China(No.51907100)Technical Program of Global Energy Interconnection Group Co.,Ltd(No.1100/2020-75001B)
文摘Electric system planning with high variable renewable energy(VRE)penetration levels has attracted great attention world-wide.Electricity production of VRE highly depends on the weather conditions and thus involves large variability,uncertainty,and low-capacity credit.This gives rise to significant challenges for power system planning.Currently,many solutions are proposed to address the issue of operational flexibility inadequacy,including flexibility retrofit of thermal units,inter-regional transmission,electricity energy storage,and demand response(DR).Evidently,the performance and the cost of various solutions are different.It is relevant to explore the optimal portfolio to satisfy the flexibility requirement for a renewable dominated system and the role of each flexibility source.In this study,the value of diverse DR flexibilities was examined and a stochastic investment planning model considering DR is proposed.Two types of DRs,namely interrupted DR and transferred DR,were modeled.Chronological load and renewable generation curves with 8760 hours within a whole year were reduced to 4 weekly scenarios to accelerate the optimization.Clustered unit commitment constraints for accommodating variability of renewables were incorporated.Case studies based on IEEE RTS-96 system are reported to demonstrate the effectiveness of the proposed method and the DR potential to avoid energy storage investment.
基金supported by the National Natural Science Foundation of China(72288101,72201029,and 72322022).
文摘Accurate origin–destination(OD)demand prediction is crucial for the efficient operation and management of urban rail transit(URT)systems,particularly during a pandemic.However,this task faces several limitations,including real-time availability,sparsity,and high-dimensionality issues,and the impact of the pandemic.Consequently,this study proposes a unified framework called the physics-guided adaptive graph spatial–temporal attention network(PAG-STAN)for metro OD demand prediction under pandemic conditions.Specifically,PAG-STAN introduces a real-time OD estimation module to estimate real-time complete OD demand matrices.Subsequently,a novel dynamic OD demand matrix compression module is proposed to generate dense real-time OD demand matrices.Thereafter,PAG-STAN leverages various heterogeneous data to learn the evolutionary trend of future OD ridership during the pandemic.Finally,a masked physics-guided loss function(MPG-loss function)incorporates the physical quantity information between the OD demand and inbound flow into the loss function to enhance model interpretability.PAG-STAN demonstrated favorable performance on two real-world metro OD demand datasets under the pandemic and conventional scenarios,highlighting its robustness and sensitivity for metro OD demand prediction.A series of ablation studies were conducted to verify the indispensability of each module in PAG-STAN.
基金National Natural Science Foundation of China,No.42001187,No.41701629。
文摘The spatial relationships between traffic accessibility and supply and demand(S&D)of ecosystem services(ESs)are essential for the formulation of ecological compensation policies and ESs regulation.In this study,an ESs matrix and coupling analysis method were used to assess ESs S&D based on land-use data for 2000,2010,and 2020,and spatial regression models were used to analyze the correlated impacts of traffic accessibility.The results showed that the ESs supply and balance index in the middle reaches of the Yangtze River urban agglomeration(MRYRUA)continuously decreased,while the demand index increased from 2000 to 2020.The Gini coefficients of these indices continued to increase but did not exceed the warning value(0.4).The coupling degree of ESs S&D continued to increase,and its spatial distribution patterns were similar to that of the ESs demand index,with significantly higher values in the plains than in the montane areas,contrasting with those of the ESs supply index.The results of global bivariate Moran’s I analysis showed a significant spatial dependence between traffic accessibility and the degree of coupling between ESs S&D;the spatial regression results showed that an increase in traffic accessibility promoted the coupling degree.The present results provide a new perspective on the relationship between traffic accessibility and the coupling degree of ESs S&D,representing a case study for similar future research in other regions,and a reference for policy creation based on the matching between ESs S&D in the MRYRUA.
