Ecological water demand:the case of the slope systems in the East Liaohe River Basin

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.

Modeling and scenario prediction of a natural gas demand system based on a system dynamics method

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.

Prediction-based Manufacturing Center Self-adaptive Demand Side Energy Optimization in Cyber Physical Systems

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.

Testing the Adding up Condition in Demand Systems

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.

Demand Elasticity for China's Major Imported Agriculture Textile Material Based on Restricted Version of Source Differentiated Almost Ideal Demand System Model

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.

Analyzing Effect of Demand Rate on Safety of Systems with Periodic Proof-tests

Quantitative safety assessment of safety systems plays an important role in decision making at all stages of system lifecycle, i.e., design, deployment and phase out. Most safety assessment methods consider only system parameters, such as configuration, hazard rate, coverage, repair rate, etc. along with periodic proof-tests （or inspection）. Not considering demand rate will give a pessimistic safety estimate for an application with low demand rate such as nuclear power plants, chemical plants, etc. In this paper, a basic model of IEC 61508 is used. The basic model is extended to incorporate process demand and behavior of electronic- and/or computer-based system following diagnosis or proof-test. A new safety index, probability of failure on actual demand （PFAD） based on extended model and demand rate is proposed. Periodic proof-test makes the model semi-Markovian, so a piece-wise continuous time Markov chain （CTMC） based method is used to derive mean state probabilities of elementary or aggregated state. Method to determine probability of failure on demand （PFD） （IEC 61508） and PFAD based on these state probabilities are described. In example, safety indices of PFD and PFAD are compared.

The 3D simulation and optimized management model of groundwater systems based on eco-environmental water demand

Through the study of mutual process between groundwater systems and eco-environmental water demand, the eco-environmental water demand is brought into groundwater systems model as the important water consumption item and unification of groundwater抯 economic, environmental and ecological functions were taken into account. Based on eco-environmental water demand at Da抋n in Jilin province, a three-dimensional simulation and optimized management model of groundwater systems was established. All water balance components of groundwater systems in 1998 and 1999 were simulated with this model and the best optimal exploitation scheme of groundwater systems in 2000 was determined, so that groundwater resource was efficiently utilized and good economic, ecologic and social benefits were obtained.

Battery Energy Storage System and Demand Response Based Optimal Virtual Power Plant Operation

With certain controllability of various distribution energy resources (DERs) such as battery energy storage system (BESS), demand response (DR) and distributed generations (DGs), virtual power plant (VPP) can suitably regulate the powers access to the distribution network. In this paper, an optimal VPP operating problem is used to optimize the charging/discharging schedule of each BESS and the DR scheme with the objective to maximize the benefit by regulating the supplied powers over daily 24 hours. The proposed solution method is composed of an iterative dynamic programming optimal BESS schedule approach and a particle swarm optimization based (PSO-based) DR scheme approach. The two approaches are executed alternatively until the minimum elec-tricity cost of the whole day is obtained. The validity of the proposed method was confirmed with the obviously decreased supplied powers in the peak-load hours and the largely reduced electricity cost.

Time-variant fragility analysis of the bridge system considering time-varying dependence among typical component seismic demands

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.

Application of a Bayesian Network Complex System Model Examining the Importance of Customer-Industry Engagement to Peak Electricity Demand Reduction

This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand Model (REPDM). The REPDM is based on a multi-disciplinary perspective designed to solve the complex problem of residential peak energy demand. The model provides a way to conceptualise and understand the factors that shift and reduce consumer demand in peak times. To gain insight into the importance of customer-industry engagement in affecting residential peak demand, this research investigates intervention impacts and major influences through testing five scenarios using different levels of customer-industry engagement activities. Scenario testing of the model outlines the dependencies between the customer-industry engagement interventions and the probabilities that are estimated to govern the dependencies that influence peak demand. The output from the model shows that there can be a strong interaction between the level of CIE activities and interventions. The influence of CIE activity can increase public and householder support for peak reduction and the model shows how the economic, technical and social interventions can achieve greater peak demand reductions when well-designed with appropriate levels of CIE activities.

Effect of structural characteristics distribution on strength demand and ductility reduction factor of MDOF systems considering soil-structure interaction

It is known that structural stiffness and strength distributions have an important role in the seismic response of buildings. The effect of using different code-specified lateral load patterns on the seismic performance of fixed-base buildings has been investigated by researchers during the past two decades. However, no investigation has yet been carried out for the case of soil-structure systems. In the present study, through intensive parametric analyses of 21,600 linear and nonlinear MDOF systems and considering five different shear strength and stiffness distribution patterns, including three code-specified patterns as well as uniform and concentric patterns subjected to a group of earthquakes recorded on alluvium and soft soils, the effect of structural characteristics distribution on the strength demand and ductility reduction factor of MDOF fixed-base and soil-structure systems are parametrically investigated. The results of this study show that depending on the level of inelasticity, soil flexibility and number of degrees-of-freedoms (DOFs), structural characteristics distribution can significantly affect the strength demand and ductility reduction factor of MDOF systems. It is also found that at high levels of inelasticity, the ductility reduction factor of low-rise MDOF soil-structure systems could be significantly less than that of fixed-base structures and the reduction is less pronounced as the number of stories increases.

高质量发展是全面建设社会主义现代化国家的首要任务

党的二十大报告提出以中国式现代化全面推进中华民族伟大复兴,形成对中国式现代化的系统性认知,强调高质量发展是全面建设社会主义现代化国家的首要任务。改革开放以来,在中国共产党的领导下,我国逐步摆脱观念桎梏和教条约束,坚持一切从国情出发,创造了人类文明新形态。经济全球化势不可挡,世界必然是和而不同的全球格局,不同文明形态、不同经济体制、不同行为方式共存形成人类命运共同体。这是中国式现代化的底层逻辑,体现了中国经济高质量发展的世界意义。从中国式现代化视角透视高质量发展的深刻叙事,有助于深刻诠释中国式现代化的核心意涵。

Demand and Response in Smart Grids for Modern Power System

Micro-grid plays a vital role in fulfilling the increasing demand by using distributed renewable energy resources. Demand and response technique can be broadly classified under the setup DR deployed (e.g. ISO’s/RTO’s). Demand response program can be implemented to improve power system quality, reliability and increasing demand. In modern power industry, strategic player can take more benefit from more emphasized DR study in terms of social benefit (uninterrupted power supply to consumers) and economy. This paper proposes the distributed micro-grid control and implemented control setup implemented demand response algorithm, which provides better power system reliability. This paper presents contingencies control demand and response for micro-grid. The main advantage of implementation of demand and response algorithms in Micro-grids provides reliable power supplies to consumers. The proposed micro-grid TCP/IP setup provides a chance to respond the contingencies to recover the shed to active condition. Micro-grid controller implements demand and response algorithm reasonable for managing the demand of the load and intelligent load scheme in case of blackout.

基于多代理的Demand Bus模拟系统

Demand Bus系统作为解决城市交通堵塞的一种新的公共运输系统在世界各地备受关注。在分析Demand Bus系统特点的基础上,提出了一种基于Q语言的多代理模拟系统框架,并且实现一个原型系统,对我国大城市使用Demand Bus系统进行了简单的评价。

大盂产业新城供水系统研究及净水处理工艺设计

大盂产业新城作为规划拓展的北部新区,处于城市公共供水盲区。为实现安全可靠的供水体系保障,着重对供水系统的整体布局、水源选取进行了分析,从水量预测、方案优选、厂站选址、处理工艺等方面进行了论述,提出了多水源、大高差、统一管网下分区、分压运行模式的设计思路,达到了多水源并网、压力平衡的效果,解决了新城城市公共供水体系建设的难题。

Risk-taking path choice behaviors under ATIS in transportation networks with demand uncertainty

A new travel time reliability-based traffic assignment model is proposed to investigate the effects of an advanced transportation information system (ATIS) on drivers' risk-taking path choice behaviours in transportation networks with demand uncertainty. In the model, drivers are divided into two classes. The first class is not equipped with ATIS, while the second class is equipped with ATIS. Different risk-taking path choice behaviours of the two classes are studied, respectively. A corresponding mixed equilibrium traffic assignment model is formulated as a variational inequality problem in terms of path flows, which is solved by a heuristic solution algorithm. Numerical results indicate that the ATIS can influence the drivers' risk-taking path choice behaviours and the total system travel time in transportation networks with demand uncertainty. It is also found that under higher demand levels, the benefits of ATIS for network performance enhancement may be more obvious.

支撑新能源电力系统灵活性需求的用户侧资源应用与关键技术

伴随着传统电力系统向以新能源为主体的新型电力系统转型升级,高比例新能源的接入和传统机组占比下降导致电力系统灵活性产生缺额。电动汽车、数据中心、P2X(power-to-X)等需求侧资源可以在多时间尺度为电力系统提供灵活性,是新型电力系统灵活性的重要组成部分。该文首先描述高比例新能源背景下输电网和配电网在不同时间尺度的灵活性需求,然后对比总结了典型需求侧资源的调节特性与应用实践,研究了需求侧资源在支撑高比例新能源输电网和配电网中运行、规划2个层面多时间尺度灵活性需求的应用场景。最后针对未来需求侧资源的研究重点,从聚合技术、电碳协同优化调控策略、可信调节能力量化和通信与信息交换标准等角度,对支撑新型电力系统需求侧资源应用的关键技术进行了总结与展望。

Design &Implementation of an Optimization Loading System in Electric by Using Genetic Algorithm

The purpose of this paper is to propose a new system for the distribution of electric power by using the concept of Active Demand procedures to obtain a low cost and ensure the continuity of energy. This paper consists of two parts: the first includes the method of optimal distribution of electricity in the presence of Active Demand based on the price of energy for the specific time in the system;this feature will help the consumer to determine the process of consumption through the advertised price;all this will appear through the energy box. The second part involves the introduction of the genetic algorithm to obtain the best solutions for costs and also the best choice for the distribution of electrical power, which makes this method optimize by introducing the genetic algorithm with electrical energy. The main drivers of this work are to provide continuous electrical energy at the lowest cost and also to simulate active demand, in addition to the rapid processing of energy failures by the aggregator and raising awareness of the process of energy conservation for the consumer.

Development and Evaluation of a Distance Learning System Based on CSCW

This paper described a distance learning system, which allows Internet users to conduct a lesson in real time from any kinds attached computers. Participants can jointly view and edit relevant multimedia information distributed through Internet. Teachers and students can also simultaneously communicate by voice and text to discuss the problems. Teacher can broadcast streaming PowerPoint presentation in real time to network users. In addition to sliders, presenters can broadcast video and audio simultaneously to deliver a live multimedia show online, and store their presentations for on demand playback. Teachers distributed in different places can also use cooperative editing tool to edit and encode existing digital content. We discussed some important design principles of the system. Then, the system configuration and the results of evaluation are also presented. The system has proved to be applicable to the distance learning based on CSCW (Computer Support Cooperative Work) in Internet.

Economic Model Predictive Control for Hot Water Based Heating Systems in Smart Buildings

This paper presents a study to optimize the heating energy costs in a residential building with varying electricity price signals based on an Economic Model Predictive Controller (EMPC). The investigated heating system consists of an air source heat pump (ASHP) incorporated with a hot water tank as active Thermal Energy Storage (TES), where two optimization problems are integrated together to optimize both the ASHP electricity consumption and the building heating consumption utilizing a heat dynamic model of the building. The results show that the proposed EMPC can save the energy cost by load shifting compared with some reference cases.