To address the issues of limited demand response data,low generalization of demand response potential evaluation,and poor demand response effect,the article proposes a demand response potential feature extraction and ...To address the issues of limited demand response data,low generalization of demand response potential evaluation,and poor demand response effect,the article proposes a demand response potential feature extraction and prediction model based on data mining and a demand response potential assessment model for adjustable loads in demand response scenarios based on subjective and objective weight analysis.Firstly,based on the demand response process and demand response behavior,obtain demand response characteristics that characterize the process and behavior.Secondly,establish a feature extraction and prediction model based on data mining,including similar day clustering,time series decomposition,redundancy processing,and data prediction.The predicted values of each demand response feature on the response day are obtained.Thirdly,the predicted data of various characteristics on the response day are used as demand response potential evaluation indicators to represent different demand response scenarios and adjustable loads,and a demand response potential evaluation model based on subjective and objective weight allocation is established to calculate the demand response potential of different adjustable loads in different demand response scenarios.Finally,the effectiveness of the method proposed in the article is verified through examples,providing a reference for load aggregators to formulate demand response schemes.展开更多
This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing factors.Th...This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing factors.The model integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)and Convolutional Long Short Term Memory Neural Network(ConvLSTM)to predict short-term taxi travel demand.The CEEMDAN decomposition method effectively decomposes time series data into a set of modal components,capturing sequence characteristics at different time scales and frequencies.Based on the sample entropy value of components,secondary processing of more complex sequence components after decomposition is employed to reduce the cumulative prediction error of component sequences and improve prediction efficiency.On this basis,considering the correlation between the spatiotemporal trends of short-term taxi traffic,a ConvLSTM neural network model with Long Short Term Memory(LSTM)time series processing ability and Convolutional Neural Networks(CNN)spatial feature processing ability is constructed to predict the travel demand for urban taxis.The combined prediction model is tested on a taxi travel demand dataset in a certain area of Beijing.The results show that the CEEMDAN-ConvLSTM prediction model outperforms the LSTM,Autoregressive Integrated Moving Average model(ARIMA),CNN,and ConvLSTM benchmark models in terms of Symmetric Mean Absolute Percentage Error(SMAPE),Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and R2 metrics.Notably,the SMAPE metric exhibits a remarkable decline of 21.03%with the utilization of our proposed model.These results confirm that our study provides a highly accurate and valid model for taxi travel demand forecasting.展开更多
It is a challenge to polish the interior surface of an additively manufactured component with complex structures and groove sizes less than 1 mm.Traditional polishing methods are disabled to polish the component,meanw...It is a challenge to polish the interior surface of an additively manufactured component with complex structures and groove sizes less than 1 mm.Traditional polishing methods are disabled to polish the component,meanwhile keeping the structure intact.To overcome this challenge,small-grooved components made of aluminum alloy with sizes less than 1 mm were fabricated by a custom-made printer.A novel approach to multi-phase jet(MPJ)polishing is proposed,utilizing a self-developed polisher that incorporates solid,liquid,and gas phases.In contrast,abrasive air jet(AAJ)polishing is recommended,employing a customized polisher that combines solid and gas phases.After jet polishing,surface roughness(Sa)on the interior surface of grooves decreases from pristine 8.596μm to 0.701μm and 0.336μm via AAJ polishing and MPJ polishing,respectively,and Sa reduces 92%and 96%,correspondingly.Furthermore,a formula defining the relationship between linear energy density and unit defect volume has been developed.The optimized parameters in additive manufacturing are that linear energy density varies from 0.135 J mm^(-1)to 0.22 J mm^(-1).The unit area defect volume achieved via the optimized parameters decreases to 1/12 of that achieved via non-optimized ones.Computational fluid dynamics simulation results reveal that material is removed by shear stress,and the alumina abrasives experience multiple collisions with the defects on the heat pipe groove,resulting in uniform material removal.This is in good agreement with the experimental results.The novel proposed setups,approach,and findings provide new insights into manufacturing complex-structured components,polishing the small-grooved structure,and keeping it unbroken.展开更多
To facilitate the coordinated and large-scale participation of residential flexible loads in demand response(DR),a load aggregator(LA)can integrate these loads for scheduling.In this study,a residential DR optimizatio...To facilitate the coordinated and large-scale participation of residential flexible loads in demand response(DR),a load aggregator(LA)can integrate these loads for scheduling.In this study,a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR.First,based on the operational characteristics of flexible loads such as electric vehicles,air conditioners,and dishwashers,their DR participation,the base to calculate the compensation price to users,was determined by considering these loads as virtual energy storage.It was quantified based on the state of virtual energy storage during each time slot.Second,flexible loads were clustered using the K-means algorithm,considering the typical operational and behavioral characteristics as the cluster centroid.Finally,the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load.The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys,thereby improving the load management performance.展开更多
With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage co...With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.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
In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a sma...In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.展开更多
To improve the resilience of a distribution system against extreme weather,a fuel-based distributed generator(DG)allocation model is proposed in this study.In this model,the DGs are placed at the planning stage.When a...To improve the resilience of a distribution system against extreme weather,a fuel-based distributed generator(DG)allocation model is proposed in this study.In this model,the DGs are placed at the planning stage.When an extreme event occurs,the controllable generators form temporary microgrids(MGs)to restore the load maximally.Simultaneously,a demand response program(DRP)mitigates the imbalance between the power supply and demand during extreme events.To cope with the fault uncertainty,a robust optimization(RO)method is applied to reduce the long-term investment and short-term operation costs.The optimization is formulated as a tri-level defenderattacker-defender(DAD)framework.At the first level,decision-makers work out the DG allocation scheme;at the second level,the attacker finds the optimal attack strategy with maximum damage;and at the third level,restoration measures,namely distribution network reconfiguration(DNR)and demand response are performed.The problem is solved by the nested column and constraint generation(NC&CG)method and the model is validated using an IEEE 33-node system.Case studies validate the effectiveness and superiority of the proposed model according to the enhanced resilience and reduced cost.展开更多
We consider the interior transmission eigenvalue problem corresponding to the scattering for an anisotropic medium of the scalar Helmholtz equation in the case where the boundary?Ωis split into two disjoint parts and...We consider the interior transmission eigenvalue problem corresponding to the scattering for an anisotropic medium of the scalar Helmholtz equation in the case where the boundary?Ωis split into two disjoint parts and possesses different transmission conditions.Using the variational method,we obtain the well posedness of the interior transmission problem,which plays an important role in the proof of the discreteness of eigenvalues.Then we achieve the existence of an infinite discrete set of transmission eigenvalues provided that n≡1,where a fourth order differential operator is applied.In the case of n■1,we show the discreteness of the transmission eigenvalues under restrictive assumptions by the analytic Fredholm theory and the T-coercive method.展开更多
To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,...To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,based on the ideas of pre-optimization and real-time optimization,a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established.At the pre-optimization stage,an improved genetic algorithm was used to obtain the pre-optimized distribution route,a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm,and a variety of operators were introduced to expand the search space of neighborhood solutions;At the real-time optimization stage,a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems,and four neighborhood search operators were used to quickly adjust the route.Two different scale examples were designed for experiments.It is proved that the algorithm can plan the better route,and adjust the distribution route in time under the real-time constraints.Therefore,the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.展开更多
This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)f...This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6255 flights and 8949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.展开更多
The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. Th...The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. The two-phased demand function states the constant function for a certain period and the quadratic function of time for the rest part of the cycle time. No shortages as well as partial backlogging are allowed to occur. The mathematical expressions are derived for determining the optimal cycle time, order quantity and total cost function. An easy-to-use working procedure is provided to calculate the above quantities. A couple of numerical examples are cited to explain the theoretical results and sensitivity analysis of some selected examples is carried out.展开更多
The objective is to develop a model considering demand dependent on selling price and deterioration occurs after a certain period of time, which follows two-parameter Weibull distribution. Shortages are allowed and fu...The objective is to develop a model considering demand dependent on selling price and deterioration occurs after a certain period of time, which follows two-parameter Weibull distribution. Shortages are allowed and fully backlogged. Fuzzy optimal solution is obtained by considering hexagonal fuzzy numbers and for defuzzification Graded Mean Integration Representation Method. A numerical example is provided for the illustration of crisp and fuzzy, both models. To observe the effect of changes in parameters, sensitivity analysis is carried out.展开更多
Understanding digital technology requires a shift in mindset that takes into account the broader implications of design,social dynamics,environmental factors,and cultural influences.Acknowledging the fact that technol...Understanding digital technology requires a shift in mindset that takes into account the broader implications of design,social dynamics,environmental factors,and cultural influences.Acknowledging the fact that technology is not confined to the virtual domain but rather has a tangible influence on our daily lives and the surrounding environment,the extensive integration and potential of digital technologies offer a distinctive prospect to fundamentally transform our shared comprehension of architecture.Digital technologies are revolutionizing design practices,manufacturing processes,and our engagement with and understanding of the built environment,by fostering the development of novel models that promote equity and inclusivity.The application of“digital technologies”can function as a methodology for examining and expressing the possible paths of emerging digital technologies.Extrapolate the expected impact of digital technologies on the design,development,and occupancy of the environment to achieve a more sustainable future in the long run.This paper will examine the potential connections and origins of digital technology concerning modularity,as well as the implications of modularity on forthcoming architectural developments in customization.展开更多
Objective:To investigate the needs of medical students regarding clinical research curricula to provide scientifically sound offerings and cultivate their clinical research thinking.Methods:From June to October 2022,m...Objective:To investigate the needs of medical students regarding clinical research curricula to provide scientifically sound offerings and cultivate their clinical research thinking.Methods:From June to October 2022,medical students at medical universities in Shaanxi Province were surveyed using online questionnaires.The survey covered their demographic information,awareness of their major,understanding of clinical research,and preferences for curriculum content.Results:A total of 341 valid questionnaires were analyzed.Medical students demonstrated a strong awareness of their majors but a relatively low awareness of clinical research.There was significant demand for clinical research courses,with preferences for professionally oriented(81.8%),market-oriented(100%),theoretically and practically integrated teaching(78.6%),and application-focused(73.0%)courses.Conclusion:Medical colleges and universities should align clinical research curricula with the actual needs of medical students and clinical practice.Reforms in curriculum design and teaching methods are essential to better prepare students for careers in public health.展开更多
Nowadays,the elderly have become an increasingly large group of people in China,but still many problems exist in their living space.This paper explores the physiological and psychological behavioral changes of the eld...Nowadays,the elderly have become an increasingly large group of people in China,but still many problems exist in their living space.This paper explores the physiological and psychological behavioral changes of the elderly,studies their living space requirements,and tries to put forward targeted design strategies in response.Therefore,making a better and more reasonable living space for the elderly as well as improving their living quality,finally helping the development of elderly-friendly design in China.展开更多
Objective: To investigate the current situation of the demand for geriatric care services of community residents in Beijing and analyze the influencing factors to provide a reference basis for meeting the demand for d...Objective: To investigate the current situation of the demand for geriatric care services of community residents in Beijing and analyze the influencing factors to provide a reference basis for meeting the demand for diversified and professional geriatric care services. Methods: A self-made questionnaire was used to randomly survey 1558 elderly individuals at community health service centers in 8 urban districts where elderly care centers were planned to be built. The influencing factors of the different characteristics of elderly care service needs from three aspects were analyzed using a dichotomous logistic regression model: predisposing, enabling, and, need factors. Results: 69.7% of the elderly required home care services, 22.8% wanted to get care services at elderly care centers, 15.9% wanted to get care services at nursing homes, 12.3% required community care services, and 7.4% didn’t know where to access care services. 68.5% of the elderly required care services for disabilities/semi-disabilities, 58.0% for dementia, 54.7% for common diseases, 34.9% for rehabilitation training, 33.0% for plumbing care, and 7.5% for hospice care. At the same time, there were urban- rural differences in the demand for elderly care services, with suburban elderly having a higher demand for care services than those living in urban areas (P < 0.05). The elderly’s demand for care services was mainly related to age, place of residence, and gender in the causative factors, mode of residence and physical condition among able factors, and mode of care services and care needs among need factors (P < 0.05). Conclusion: The demand for elderly care services was differentiated by factors including place of residence, age, and gender. It is crucial to accurately match the demand for elderly care services, innovate the mode of elderly care services, and improve the service quality to improve the elderly health service system.展开更多
To further enhance the effectiveness of talent cultivation for interior design in vocational colleges,it is necessary to vigorously promote the construction of an industry-education integration model.Through this mode...To further enhance the effectiveness of talent cultivation for interior design in vocational colleges,it is necessary to vigorously promote the construction of an industry-education integration model.Through this model,the roles of both enterprises and schools can be leveraged to jointly facilitate the continuous improvement of students’professional abilities and practical skills,providing a steady stream of high-quality talents for the development of the interior design field.Therefore,this paper analyzes the current issues in interior design talent cultivation in vocational colleges from the perspective of industry-education integration and proposes corresponding improvement measures.展开更多
Currently,there is a lack of research on the detailed environmental spatial design of community daycare centers at the micro level.This study focuses on Community F in Chongqing,using the elderly’s“willingness to de...Currently,there is a lack of research on the detailed environmental spatial design of community daycare centers at the micro level.This study focuses on Community F in Chongqing,using the elderly’s“willingness to demand”as a central aspect.It examines indoor and outdoor environmental space needs at a micro level,considering both functional requirements and spiritual needs based on existing research.The analysis incorporates three adaptive elements:current construction,surrounding environment,and operational management.It explores the feasibility of restructuring spatial layouts,utilizing local resources,and integrating Bayu cultural characteristics.Finally,through design optimization practices,the study proposes three strategies for aging optimization:functional integration and interaction,user-friendly facilities,and emotional connections to place.展开更多
With the constant change of fashion trends,interior design styles are changing day by day.Based on Unity3D technology,this paper develops a system for modern interior-style design and application.Taking the residentia...With the constant change of fashion trends,interior design styles are changing day by day.Based on Unity3D technology,this paper develops a system for modern interior-style design and application.Taking the residential interior as a case study,the interior style design is achieved through 3D modeling and texture rendering and then combined with the Unity3D engine to achieve scene roaming and interactive design.The system enables designers to express design concepts more intuitively and efficiently and also improves customer participation and satisfaction.Through the experience of designers and customers,the system is verified to have more practical value than traditional interior design solutions.展开更多
基金the National Natural Science Foundation of China Youth Fund,Research on Security Low Carbon Collaborative Situation Awareness of Comprehensive Energy System from the Perspective of Dynamic Security Domain(52307130).
文摘To address the issues of limited demand response data,low generalization of demand response potential evaluation,and poor demand response effect,the article proposes a demand response potential feature extraction and prediction model based on data mining and a demand response potential assessment model for adjustable loads in demand response scenarios based on subjective and objective weight analysis.Firstly,based on the demand response process and demand response behavior,obtain demand response characteristics that characterize the process and behavior.Secondly,establish a feature extraction and prediction model based on data mining,including similar day clustering,time series decomposition,redundancy processing,and data prediction.The predicted values of each demand response feature on the response day are obtained.Thirdly,the predicted data of various characteristics on the response day are used as demand response potential evaluation indicators to represent different demand response scenarios and adjustable loads,and a demand response potential evaluation model based on subjective and objective weight allocation is established to calculate the demand response potential of different adjustable loads in different demand response scenarios.Finally,the effectiveness of the method proposed in the article is verified through examples,providing a reference for load aggregators to formulate demand response schemes.
基金supported by the Surface Project of the National Natural Science Foundation of China(No.71273024)the Fundamental Research Funds for the Central Universities of China(2021YJS080).
文摘This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing factors.The model integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)and Convolutional Long Short Term Memory Neural Network(ConvLSTM)to predict short-term taxi travel demand.The CEEMDAN decomposition method effectively decomposes time series data into a set of modal components,capturing sequence characteristics at different time scales and frequencies.Based on the sample entropy value of components,secondary processing of more complex sequence components after decomposition is employed to reduce the cumulative prediction error of component sequences and improve prediction efficiency.On this basis,considering the correlation between the spatiotemporal trends of short-term taxi traffic,a ConvLSTM neural network model with Long Short Term Memory(LSTM)time series processing ability and Convolutional Neural Networks(CNN)spatial feature processing ability is constructed to predict the travel demand for urban taxis.The combined prediction model is tested on a taxi travel demand dataset in a certain area of Beijing.The results show that the CEEMDAN-ConvLSTM prediction model outperforms the LSTM,Autoregressive Integrated Moving Average model(ARIMA),CNN,and ConvLSTM benchmark models in terms of Symmetric Mean Absolute Percentage Error(SMAPE),Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and R2 metrics.Notably,the SMAPE metric exhibits a remarkable decline of 21.03%with the utilization of our proposed model.These results confirm that our study provides a highly accurate and valid model for taxi travel demand forecasting.
基金the National Key Research and Development Program of China(2018YFA0703400)the Young Scientists Fund of the National Natural Science Foundation of China(52205447)Changjiang Scholars Program of the Chinese Ministry of Education。
文摘It is a challenge to polish the interior surface of an additively manufactured component with complex structures and groove sizes less than 1 mm.Traditional polishing methods are disabled to polish the component,meanwhile keeping the structure intact.To overcome this challenge,small-grooved components made of aluminum alloy with sizes less than 1 mm were fabricated by a custom-made printer.A novel approach to multi-phase jet(MPJ)polishing is proposed,utilizing a self-developed polisher that incorporates solid,liquid,and gas phases.In contrast,abrasive air jet(AAJ)polishing is recommended,employing a customized polisher that combines solid and gas phases.After jet polishing,surface roughness(Sa)on the interior surface of grooves decreases from pristine 8.596μm to 0.701μm and 0.336μm via AAJ polishing and MPJ polishing,respectively,and Sa reduces 92%and 96%,correspondingly.Furthermore,a formula defining the relationship between linear energy density and unit defect volume has been developed.The optimized parameters in additive manufacturing are that linear energy density varies from 0.135 J mm^(-1)to 0.22 J mm^(-1).The unit area defect volume achieved via the optimized parameters decreases to 1/12 of that achieved via non-optimized ones.Computational fluid dynamics simulation results reveal that material is removed by shear stress,and the alumina abrasives experience multiple collisions with the defects on the heat pipe groove,resulting in uniform material removal.This is in good agreement with the experimental results.The novel proposed setups,approach,and findings provide new insights into manufacturing complex-structured components,polishing the small-grooved structure,and keeping it unbroken.
基金supported by the Basic Science(Natural Science)Research Project of Jiangsu Higher Education Institutions(No.23KJB470020)the Natural Science Foundation of Jiangsu Province(Youth Fund)(No.BK20230384)。
文摘To facilitate the coordinated and large-scale participation of residential flexible loads in demand response(DR),a load aggregator(LA)can integrate these loads for scheduling.In this study,a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR.First,based on the operational characteristics of flexible loads such as electric vehicles,air conditioners,and dishwashers,their DR participation,the base to calculate the compensation price to users,was determined by considering these loads as virtual energy storage.It was quantified based on the state of virtual energy storage during each time slot.Second,flexible loads were clustered using the K-means algorithm,considering the typical operational and behavioral characteristics as the cluster centroid.Finally,the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load.The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys,thereby improving the load management performance.
基金supported by Science and Technology Project of SGCC(SGSW0000FZGHBJS2200070)。
文摘With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.
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.
文摘In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.
基金supported by the Technology Project of State Grid Jiangsu Electric Power Co.,Ltd.,China (J2022160,Research on Key Technologies of Distributed Power Dispatching Control for Resilience Improvement of Distribution Networks).
文摘To improve the resilience of a distribution system against extreme weather,a fuel-based distributed generator(DG)allocation model is proposed in this study.In this model,the DGs are placed at the planning stage.When an extreme event occurs,the controllable generators form temporary microgrids(MGs)to restore the load maximally.Simultaneously,a demand response program(DRP)mitigates the imbalance between the power supply and demand during extreme events.To cope with the fault uncertainty,a robust optimization(RO)method is applied to reduce the long-term investment and short-term operation costs.The optimization is formulated as a tri-level defenderattacker-defender(DAD)framework.At the first level,decision-makers work out the DG allocation scheme;at the second level,the attacker finds the optimal attack strategy with maximum damage;and at the third level,restoration measures,namely distribution network reconfiguration(DNR)and demand response are performed.The problem is solved by the nested column and constraint generation(NC&CG)method and the model is validated using an IEEE 33-node system.Case studies validate the effectiveness and superiority of the proposed model according to the enhanced resilience and reduced cost.
基金supported by the National Natural Science Foundation of China(11571132,12301542)the Natural Science Foundation of Hubei(2022CFB725)the Natural Science Foundation of Yichang(A23-2-027)。
文摘We consider the interior transmission eigenvalue problem corresponding to the scattering for an anisotropic medium of the scalar Helmholtz equation in the case where the boundary?Ωis split into two disjoint parts and possesses different transmission conditions.Using the variational method,we obtain the well posedness of the interior transmission problem,which plays an important role in the proof of the discreteness of eigenvalues.Then we achieve the existence of an infinite discrete set of transmission eigenvalues provided that n≡1,where a fourth order differential operator is applied.In the case of n■1,we show the discreteness of the transmission eigenvalues under restrictive assumptions by the analytic Fredholm theory and the T-coercive method.
基金supported by Natural Science Foundation Project of Gansu Provincial Science and Technology Department(No.1506RJZA084)Gansu Provincial Education Department Scientific Research Fund Grant Project(No.1204-13).
文摘To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,based on the ideas of pre-optimization and real-time optimization,a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established.At the pre-optimization stage,an improved genetic algorithm was used to obtain the pre-optimized distribution route,a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm,and a variety of operators were introduced to expand the search space of neighborhood solutions;At the real-time optimization stage,a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems,and four neighborhood search operators were used to quickly adjust the route.Two different scale examples were designed for experiments.It is proved that the algorithm can plan the better route,and adjust the distribution route in time under the real-time constraints.Therefore,the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.
文摘This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6255 flights and 8949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.
文摘The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. The two-phased demand function states the constant function for a certain period and the quadratic function of time for the rest part of the cycle time. No shortages as well as partial backlogging are allowed to occur. The mathematical expressions are derived for determining the optimal cycle time, order quantity and total cost function. An easy-to-use working procedure is provided to calculate the above quantities. A couple of numerical examples are cited to explain the theoretical results and sensitivity analysis of some selected examples is carried out.
文摘The objective is to develop a model considering demand dependent on selling price and deterioration occurs after a certain period of time, which follows two-parameter Weibull distribution. Shortages are allowed and fully backlogged. Fuzzy optimal solution is obtained by considering hexagonal fuzzy numbers and for defuzzification Graded Mean Integration Representation Method. A numerical example is provided for the illustration of crisp and fuzzy, both models. To observe the effect of changes in parameters, sensitivity analysis is carried out.
文摘Understanding digital technology requires a shift in mindset that takes into account the broader implications of design,social dynamics,environmental factors,and cultural influences.Acknowledging the fact that technology is not confined to the virtual domain but rather has a tangible influence on our daily lives and the surrounding environment,the extensive integration and potential of digital technologies offer a distinctive prospect to fundamentally transform our shared comprehension of architecture.Digital technologies are revolutionizing design practices,manufacturing processes,and our engagement with and understanding of the built environment,by fostering the development of novel models that promote equity and inclusivity.The application of“digital technologies”can function as a methodology for examining and expressing the possible paths of emerging digital technologies.Extrapolate the expected impact of digital technologies on the design,development,and occupancy of the environment to achieve a more sustainable future in the long run.This paper will examine the potential connections and origins of digital technology concerning modularity,as well as the implications of modularity on forthcoming architectural developments in customization.
基金Supporting Fund Project of the First Affiliated Hospital of Xi’an Medical University(XYFYPT-2022-02)Scientific and Technological Innovation Team Project of Xi’an Medical University(2021TD14)+1 种基金Postgraduate Education and Teaching Reform Project of Shaanxi Traditional Chinese Medicine University(JGCX003)Education and Teaching Reform Project of Xi’an Medical University(2022JG-67)。
文摘Objective:To investigate the needs of medical students regarding clinical research curricula to provide scientifically sound offerings and cultivate their clinical research thinking.Methods:From June to October 2022,medical students at medical universities in Shaanxi Province were surveyed using online questionnaires.The survey covered their demographic information,awareness of their major,understanding of clinical research,and preferences for curriculum content.Results:A total of 341 valid questionnaires were analyzed.Medical students demonstrated a strong awareness of their majors but a relatively low awareness of clinical research.There was significant demand for clinical research courses,with preferences for professionally oriented(81.8%),market-oriented(100%),theoretically and practically integrated teaching(78.6%),and application-focused(73.0%)courses.Conclusion:Medical colleges and universities should align clinical research curricula with the actual needs of medical students and clinical practice.Reforms in curriculum design and teaching methods are essential to better prepare students for careers in public health.
基金“Research on the Design Strategies of the Senior Community from the Perspective of Community Operation and Service Management,”University-level Research Projects in 2023(Project No.XdKY234732).
文摘Nowadays,the elderly have become an increasingly large group of people in China,but still many problems exist in their living space.This paper explores the physiological and psychological behavioral changes of the elderly,studies their living space requirements,and tries to put forward targeted design strategies in response.Therefore,making a better and more reasonable living space for the elderly as well as improving their living quality,finally helping the development of elderly-friendly design in China.
文摘Objective: To investigate the current situation of the demand for geriatric care services of community residents in Beijing and analyze the influencing factors to provide a reference basis for meeting the demand for diversified and professional geriatric care services. Methods: A self-made questionnaire was used to randomly survey 1558 elderly individuals at community health service centers in 8 urban districts where elderly care centers were planned to be built. The influencing factors of the different characteristics of elderly care service needs from three aspects were analyzed using a dichotomous logistic regression model: predisposing, enabling, and, need factors. Results: 69.7% of the elderly required home care services, 22.8% wanted to get care services at elderly care centers, 15.9% wanted to get care services at nursing homes, 12.3% required community care services, and 7.4% didn’t know where to access care services. 68.5% of the elderly required care services for disabilities/semi-disabilities, 58.0% for dementia, 54.7% for common diseases, 34.9% for rehabilitation training, 33.0% for plumbing care, and 7.5% for hospice care. At the same time, there were urban- rural differences in the demand for elderly care services, with suburban elderly having a higher demand for care services than those living in urban areas (P < 0.05). The elderly’s demand for care services was mainly related to age, place of residence, and gender in the causative factors, mode of residence and physical condition among able factors, and mode of care services and care needs among need factors (P < 0.05). Conclusion: The demand for elderly care services was differentiated by factors including place of residence, age, and gender. It is crucial to accurately match the demand for elderly care services, innovate the mode of elderly care services, and improve the service quality to improve the elderly health service system.
基金University-Level Teaching Reform Project“Research on Effective Models and Pathways for University-Enterprise Co-Construction of an Industry College Based on the School of Architecture and Urban Industry”(Q2310003)。
文摘To further enhance the effectiveness of talent cultivation for interior design in vocational colleges,it is necessary to vigorously promote the construction of an industry-education integration model.Through this model,the roles of both enterprises and schools can be leveraged to jointly facilitate the continuous improvement of students’professional abilities and practical skills,providing a steady stream of high-quality talents for the development of the interior design field.Therefore,this paper analyzes the current issues in interior design talent cultivation in vocational colleges from the perspective of industry-education integration and proposes corresponding improvement measures.
基金Scientific and Technological Research Project of Chongqing Municipal Education Commission:Evaluation and Optimization Research on Planning and Implementation of Community Daycare Centers from the Perspective of Subject-Object Relationship(Project No.KJQN202301901)。
文摘Currently,there is a lack of research on the detailed environmental spatial design of community daycare centers at the micro level.This study focuses on Community F in Chongqing,using the elderly’s“willingness to demand”as a central aspect.It examines indoor and outdoor environmental space needs at a micro level,considering both functional requirements and spiritual needs based on existing research.The analysis incorporates three adaptive elements:current construction,surrounding environment,and operational management.It explores the feasibility of restructuring spatial layouts,utilizing local resources,and integrating Bayu cultural characteristics.Finally,through design optimization practices,the study proposes three strategies for aging optimization:functional integration and interaction,user-friendly facilities,and emotional connections to place.
基金Research and Development of Wear-resistant Filament Monitoring System for Medicinal Core(Project No.:H20240260)Anqing Normal University Wanjiang Cultural Digital Protection and Intelligent Processing Key Laboratory Project,“Huangmei Opera Intelligent Digital Human Design and Application”+1 种基金Anqing Mayor Triangle Future Industry Research Institute Science and Technology Project,“Exploration of the Metaverse Design of Opera Culture and the Integration Model of Cultural Tourism”Anhui Provincial Social Science Innovation and Development Research Project,“Huangmei Opera Cultural Relics and Cultural Digital Native Protection and Utilization Innovation Research Project(Project No.:2023KY012)”。
文摘With the constant change of fashion trends,interior design styles are changing day by day.Based on Unity3D technology,this paper develops a system for modern interior-style design and application.Taking the residential interior as a case study,the interior style design is achieved through 3D modeling and texture rendering and then combined with the Unity3D engine to achieve scene roaming and interactive design.The system enables designers to express design concepts more intuitively and efficiently and also improves customer participation and satisfaction.Through the experience of designers and customers,the system is verified to have more practical value than traditional interior design solutions.