Research on Demand Response Potential of Adjustable Loads in Demand Response Scenarios

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.

A Combination Prediction Model for Short Term Travel Demand of Urban Taxi

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.

Stochastic programming based coordinated expansion planning of generation,transmission,demand side resources,and energy storage considering the DC transmission system

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.

Optimal dispatching strategy for residential demand response considering load participation

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.

Optimal Bidding Strategies of Microgrid with Demand Side Management for Economic Emission Dispatch Incorporating Uncertainty and Outage of Renewable Energy Sources

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.

A Novel Defender-Attacker-Defender Model for Resilient Distributed Generator Planning with Network Reconfiguration and Demand Response

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.

A Note on an Order Level Inventory Model with Varying Two-Phased Demand and Time-Proportional Deterioration

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.

Fuzzy Inventory Model under Selling Price Dependent Demand and Variable Deterioration with Fully Backlogged Shortages

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.

Demand and Analysis of Clinical Research Curriculum in Medical Universities

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.

Survey on the Demand for Elderly Care Services of Community Residents in Beijing and Analysis of Influencing Factors

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.

Research on Adaptability Analysis of Environmental Space Demand and Design Optimization of Daycare Centers: Taking Chongqing’s Community F as an Example

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.

Study on the Alignment Between Talent Training Directions and Employment Market Demands in the Landscape Architecture Industry

Currently,talent training in Chinese universities for landscape architecture is mainly divided into three directions:“landscape planning and design,”“landscape construction management,”and“landscape plant planting and maintenance.”However,with the background of the slowing urbanization process and the widespread demand for composite talents in society,it remains to be verified whether the traditional three major talent training directions in landscape architecture align with the job demands in the current construction market.Based on a survey and analysis of over 300 industry practitioners,this study found a clear trend of merging the three major employment directions into“landscape design and construction”and“landscape plant planting and maintenance.”This presents new requirements and directions for the skill training of landscape architecture majors in universities and provides insights into the alignment between talent training and employment demands in other industries.

A Prediction Model of Peasants’ Income in China Based on BP Neural Network

According to the related data affecting the peasants’ income in China in the years 1978-2008,a total of 13 indices are selected,such as agricultural population,output value of primary industry,and rural employees.Based on the standardized method and BP neural network method,the peasants’ income and the artificial neural network model are established and analyzed.Results show that the simulation value agrees well with the real value;the neural network model with improved BP algorithm has high prediction accuracy,rapid convergence rate and good generalization ability.Finally,suggestions are put forward to increase the peasants’ income,such as promoting the process of urbanization,developing small and medium-sized enterprises in rural areas,encouraging intensive operation,and strengthening the rural infrastructure and agricultural science and technology input.

Impact of organophosphorous pesticide exposure on semen quality of Chinese peasants

Aim: To investigate the impact of organophosphorous pesticide exposure and other risk factors on the semen quality of Chinese peasants. Method: Questionnaire investigation, external genital examination and laboratory examination were conducted on 322 male peasants, including the exposed and the control groups of 161 subjects each. Results: Multivariate analysis showed that the educational level and the years of alcohol drinking influenced the semen volume. Compared with subjects of primary school education or lower, those with junior high school education had a higher semen volume (OR=1.961). Proportion of subjects with higher semen volume decreased with increased years of alcohol drinking (OR=0.962). Organophosphorous pesticide exposure decreased the number of forward progression sperm (OR=0.528), the sperm density (OR=0.266), the sperm viability (OR=0.398) and the percentage of normal morphology sperm (OR=0.281). A possible relationship was present between the season of semen collection and the number of forward progression sperm, sperm viability and percentage of normal morphology sperm. Compared with the summer data, the above three indices were higher in winter (OR being 2. 272, 4.060 and 5.249, respectively). Conclusion: Exposure to organophosphorous pesticide could damage the semen quality of the peasants. Education and alcohol drinking also affect the semen quality.

Strategies for Cultivating New Peasants Based on Modern Agricultural Development

Development of modern agriculture has higher and higher requirements on quality of peasants.This study,on the basis of connotations of modern agriculture,current situation and problems of Chinese peasants,and contradictions between modern agricultural development and peasants' quality,specifies requirements of modern agriculture on new peasants,proposes corresponding suggestions to promote the cultivation of new Chinese peasants.

Different Characteristics of Peasant Issues from the Connections between Peasants and Land

The paper analyzes the different characteristics of peasant issues formed by connections between peasants and land at different historical stages,and offers a reference for us to look squarely at peasant issues in the reality.The characteristics of peasant issues with land as the inherent feature are:the degree of connection decides the classification and policies of peasants;the private ownership of land decides the political status and influences of peasants;the inherence of private connections with land determines the future of peasants.The characteristics of peasant issues with land as the core value are:the peasant issues with land as the core is the key to victory of new-democratic revolution;the peasant issues with land as the core is the basis of establishment of socialist system;the characteristics of peasant issues with land as the guarantee are:carriers of peasants interests change from unicity to diversity;peasants change from identity certification to vocational certification;the economic influence of peasants changes and penetrates from part to entirety.

Reflections on the Peasants＇ Subjectivity in the Development of Rural Deliberative Democracy

The subjectivity of China's people deliberative democracy is essentially different from Western capital deliberative democracy. And the people's subjectivity naturally manifests as peasant's subjectivity in the deliberative democracy in rural areas. Combined with normative analysis of the whole process of rural deliberation practice,peasants' subjectivity can be summarized as broad equality of participation,completeness of the program,as well as final benefit of the result. However,there are some hidden dangers which may give rise to alienation development of deliberative politics in the current dilemma of rural deliberation practice.The fundamental way to solve the problem lies in combining subjectivity and institutionalization together to develop the rural deliberative democracy.

Approaches of Realizing Cultural Value of Red Revolutionary Site in Jiangxi Province:A Case Study of Chinese Workers' and Peasants' Red Army in Xiushui County

Red revolutionary site is a significant carrier for inheriting and spreading red culture,a witness of revolutionary history and stones,and also the best place to show connotations and value of red culture.Taking the regiment headquarter and the division headquarter of the First Division of the First Army in Xiushui County,Jiangxi Province for example,this paper explored cultural value of red site,analyzed the existing problems,tried to figure out scientific approaches of realizing cultural value of red site,so as to promote the sharing and inheritance of cultural value of red revolutionary site.

Optimal Operation of Distributed Generations Considering Demand Response in a Microgrid Using GWO Algorithm

The widespread penetration of distributed energy sources and the use of load response programs,especially in a microgrid,have caused many power system issues,such as control and operation of these networks,to be affected.The control and operation of many small-distributed generation units with different performance characteristics create another challenge for the safe and efficient operation of the microgrid.In this paper,the optimum operation of distributed generation resources and heat and power storage in a microgrid,was performed based on real-time pricing through the proposed gray wolf optimization(GWO)algorithm to reduce the energy supply cost with the microgrid.Distributed generation resources such as solar panels,diesel generators with battery storage,and boiler thermal resources with thermal storage were used in the studied microgrid.Also,a combined heat and power(CHP)unit was used to produce thermal and electrical energy simultaneously.In the simulations,in addition to the gray wolf algorithm,some optimization algorithms have also been used.Then the results of 20 runs for each algorithm confirmed the high accuracy of the proposed GWO algorithm.The results of the simulations indicated that the CHP energy resources must be managed to have a minimum cost of energy supply in the microgrid,considering the demand response program.

Foreign Ducks Help Peasants to Shake Off Poverty

ＦｏｒｅｉｇｎＤｕｃｋｓＨｅｌｐＰｅａｓａｎｔｓｔｏＳｈａｋｅＯｆｆＰｏｖｅｒｔｙＢｙｓｔａｆｆｒｅｐｏｒｔｅｒＬＩＪＩＡＮＧＵＯＬＹＩＮＧＩＮｔｈｅＤａｂｉｅＭｏｕｎｔａｉｎＡｒｅａｉｎｃｅｎｔｒａｌＣｈｉＸｉｎｙａｎｇＰｒｅｆｅｃｔｕｒｅｗａｓｆ...