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.

Estimating the Fresh Vegetables Demand System in Jordan： A Linear Approximate Almost Ideal Demand System

The main objective of this research is to estimate the different types of demand elasticities for the main fresh vegetables consumed in Jordan. The estimated elasticities can be used to measure the impacts of agricultural policies and can be used to predict future consumption in the context of food security in terms of access, availability, stability, and food quality. The reported demand estimates were obtained through the estimation of a Linear Approximate Almost Ideal Demand Systems （LA/AIDS） for Jordan fresh vegetable crops demand system using the most recent cross-sectional data of household expenditure survey in 2005. A censored regression method for the system of equations was used to analyze fresh vegetables consumption patterns. This method allows for inclusion of a large number of zero consumption for some foods through two-step demand system estimation. All of the own-price demand elasticities have the correct negative signs and statistically significant. According to the expenditure elasticity, tomato, cucumber, and potato are the necessity goods. The mean budget shares indicate that consumers spend 30 percent of their allocated budget to vegetables on tomatoes and potatoes. The green bean elasticity is the highest indicating that demand for beans is highly responsive to any changes in the price. The expenditure elasticities reveal that the demand on all vegetables is expected to grow over the coming few years. High own-price elasticities of all vegetables studied suggests that any changes in the prices of these crops could bring about a significant shift in fruits and vegetable constanption patterns.

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.

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.

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.

Physics Guided Deep Learning-Based Model for Short-Term Origin–Destination Demand Prediction in Urban Rail Transit Systems Under Pandemic

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.

Optimization research on supply and demand system for water resources in the Chang-Zhu-Tan urban agglomeration

Using system analysis theory and methods, a dynamic model of a water resource supply and demand system was built to simulate trends in the supply and demand of water in the Changsha-Zhuzhou-Xiangtan （Chang-Zhu-Tan） urban agglomeration for the period 2012 to 2030. Four scenarios were examined; namely, a traditional development model, an economic development model, a water-saving model, and a coordinated development model. （i） The problem of balancing water resource supply and demand is becoming increasingly conspicuous with a growing population and a rapidly developing economy. （ii） By 2030, water demand is set to reach a total of 105.1 × 10^8 m^3, with a water supply of 5.4 × 10^8 m^3. A coordinated development model for water resource supply could meet the growing demands of socio-economic development, and generate huge comprehensive benefits. This will be the best solution for the development and utilization of a water resource supply and demand system in the Chang-Zhu-Tan urban agglomeration. （iii） We should accelerate the construction of water conservation projects, strengthen the management of water conservation, optimize economic structures, enhance our awareness of the importance of protecting water resources, hasten the recycling of waste water and environmental improvement, and promote utilization efficiency, and support the capabilities of water resources to meet our expectations.

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.

Station-and-network–coordinated planning of integrated energy system considering integrated demand response

The integrated energy system(IES)is an important energy supply method for mitigating the energy crisis.A station-and-network–coordinated planning method for the IES,which considers the integrated demand responses(IDRs)of flexible loads,electric vehicles,and energy storage is proposed in this work.First,based on load substitution at the user side,an energy-station model considering the IDR is established.Then,based on the characteristics of the energy network,a collaborative planning model is established for the energy station and energy network of the IES,considering the comprehensive system investment,operation and maintenance,and clean energy shortage penalty costs,to minimize the total cost.This can help optimize the locations of the power lines and natural gas pipelines and the capacities of the equipment in an energy station.Finally,simulations are performed to demonstrate that the proposed planning method can help delay or reduce the construction of new lines and energy-station equipment,thereby reducing the investment required and improving the planning economics of the IES.

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.

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.

Dynamic Analysis of Supply and Demand Coupling of Ecosystem Services in Loess Hilly Region:A Case Study of Lanzhou,China

The relationship between the supply and demand for ecosystem services(ESs)is a key issue for the rational allocation of natural resources and optimisation of sustainable development capacity.This paper investigateed the dynamic evolution features of supply and demand of four ESs in Lanzhou of China,namely,water supply,food supply,carbon fixation and soil retention services.The crosssectional data of 2005 and 2017 were used for calculating ESs value and its supply and demand through ArcGIS software,InVEST model,elastic coefficient model and coupling coordination model.Results showed that:1)from 2005 to 2017,the supply of water supply services increased,the demand of soil retention services decreased,and the supply and demand of food supply and carbon fixation services increased.The high-value areas of service supply were mainly distributed in the rocky mountain areas in the southeast and northwest with high vegetation coverage,while the high-value areas of demand were mainly distributed in the urban areas and surrounding areas with high population density.2)There were five different types of coupling relations.Water supply service was dominated by a negative coupling type D,which means that the decrease in demand for ESs has had a positive response on the supply of ESs.Negative coupling type C was the main type of food supply and carbon fixation services,which means that the increase in demand for ESs has had a negative response on the supply of ESs.All three services were supplemented by a positive coupling type A,which means that the increase in demand for ESs has had a positive response on the supply of ESs.Soil retention service generally exhibits a positive coupling type B,which means that the decrease in demand for ESs has had a negative response on the supply of ESs.3)Over the past 12 yr,the coordination degree of supply and demand of water supply,food supply and soil retention services decreased,and the coordination degree of carbon fixation service increased.Various types of ES had a low degree of coupling and coordination,showing different characteristics of temporal and spatial evolution.The areas with imbalanced ESs supply and demand were mainly distributed in urban areas dominated by construction land.The research results are valuable to the optimisation of urban and rural ecological environments and the sustainable development of territory space under the framework of ecological civilisation,including similar ecologically vulnerable areas in other developing countries.

Power system planning with high renewable energy penetration considering demand response

Electric system planning with high variable renewable energy(VRE)penetration levels has attracted great attention world-wide.Electricity production of VRE highly depends on the weather conditions and thus involves large variability,uncertainty,and low-capacity credit.This gives rise to significant challenges for power system planning.Currently,many solutions are proposed to address the issue of operational flexibility inadequacy,including flexibility retrofit of thermal units,inter-regional transmission,electricity energy storage,and demand response(DR).Evidently,the performance and the cost of various solutions are different.It is relevant to explore the optimal portfolio to satisfy the flexibility requirement for a renewable dominated system and the role of each flexibility source.In this study,the value of diverse DR flexibilities was examined and a stochastic investment planning model considering DR is proposed.Two types of DRs,namely interrupted DR and transferred DR,were modeled.Chronological load and renewable generation curves with 8760 hours within a whole year were reduced to 4 weekly scenarios to accelerate the optimization.Clustered unit commitment constraints for accommodating variability of renewables were incorporated.Case studies based on IEEE RTS-96 system are reported to demonstrate the effectiveness of the proposed method and the DR potential to avoid energy storage investment.

Architecture design and demand analysis on application layer of standard system for ubiquitous power Internet of Things

The ubiquitous power Internet of Things(UPIoT)is an intelligent service system with comprehensive state perception,efficient processing,and flexible application of information.It focuses on each link of the power system and makes full use of the mobile internet,artificial intelligence,and other advanced information and communication technologies in order to realize the inter-human interaction of all things in all links of the power system.This article systematically presents to the national and international organizations and agencies in charge of UPIoT layer standardization the status quo of the research on the Internet of Things(IoT)-related industry standards system.It briefly describes the generic standard classification methods,layered architecture,conceptual model,and system tables in the UPIoT application layer.Based on the principles of inheritance,innovation,and practicability,this study divides the application layer into customer service,power grid operation,integrated energy,and enterprise operation,emerging business and analyzes the standard requirements of these five fields.This study also proposes a standard plan.Finally,it summarizes the research report and provides suggestions for a follow-up work.

System Dynamics Approach to Urban Water Demand Forecasting—A Case Study of Tianjin

A system dynamics approach to urban water demand forecasting was developed based on the analysis of urban water resources system, which was characterized by multi-feedback and nonlinear interactions among sys-tem elements. As an example, Tianjin water resources system dynamic model was set up to forecast water resources demand of the planning years. The practical verification showed that the relative error was lower than 10%. Fur-thermore, through the comparison and analysis of the simulation results under different development modes pre-sented in this paper, the forecasting results of the water resources demand of Tianjin was achieved based on sustain-able utilization strategy of water resources.

Optimal operation of cold–heat–electricity multi-energy collaborative system based on price demand response

In a multi-energy collaboration system, cooling, heating, electricity, and other energy components are coupled to complement each other. Through multi-energy coordination and cooperation, they can significantly improve their individual operating efficiency and overall economic benefits. Demand response, as a multi-energy supply and demand balance method, can further improve system flexibility and economy. Therefore, a multi-energy cooperative system optimization model has been proposed, which is driven by price-based demand response to determine the impact of power-demand response on the optimal operating mode of a multi-energy cooperative system. The main components of the multi-energy collaborative system have been analyzed. The multi-energy coupling characteristics have been identified based on the energy hub model. Using market elasticity as a basis, a price-based demand response model has been built. The model has been optimized to minimize daily operating cost of the multi-energy collaborative system. Using data from an actual situation, the model has been verified, and we have shown that the adoption of price-based demand response measures can significantly improve the economy of multi-energy collaborative systems.

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.

Demand side management for solving environment constrained economic dispatch of a microgrid system using hybrid MGWOSCACSA algorithm

Microgrids are a type of restricted power distribution systems in which electricity is generated,transmitted,and distributed within a small geographic region.They are used to ensure that renewable energy sources are used to their full potential.Microgrids provide further benefits,such as lowering transmission losses and the expenses associated with them.This research compares and contrasts the aims of economic dispatch,emission dispatch,fractional programing based combined economic emission dispatch,and environmental restricted economic dispatch(ECED).A low-voltage microgrid system is investigated for three different scenarios.As a study optimization tool,an innovative,resilient,and strong hybrid swarm-intelligence optimization algorithm is utilised,which is based on combining the properties of the traditional grey-wolf optimiser,sine-cosine algorithm,and crow search algorithm.The employment of a time-of-use energy mar-ket pricing approach instead of a fixed pricing plan resulted in a 15%decrease in gen-eration costs throughout the course of the research.When ECED was assessed with a 15%-20%demand side management based restructured load demand model for the microgrid system,the generation costs were reduced even further.

Analysis of an Inventory System for Items with Stochastic Demand and Time Dependent Three-Parameter Weibull Deterioration Function

In recent times, mathematical models have been developed to describe various scenarios obtainable in the management of inventories. These models usually have as objective the minimizing of inventory costs. In this research work we propose a mathematical model of an inventory system with time-dependent three-parameter Weibull deterioration and a stochastic type demand in the form of a negative exponential distribution. Explicit expressions for the optimal values of the decision variables are obtained. Numerical examples are provided to illustrate the theoretical development.

THE APPLICATION RESEARCH OF VIDEO SERVER SYSTEM FOR VIDEO ON DEMAND

A comprehensive research on key issues of the large-scale video server system for Video On Demand (VOD) client/server system is conducted based mainly on real time (rt)/non-real time (nrt) Variable Bit Rate or Constant Bit Rate (VBR/CBR) MPEG-2 MP@ML Signal Program Transport Stream (SPTS) for movies, and general architecture for storage, control, caching subsystems from Loosely Coupled Computer (LCC), Symmetric Multiple Processing (SMP), and Massively Parallel Processing (MPP) video server is conceptualized. Meanwhile, Redundant Array of Inexpensive Disks (RAID) storage system are presented and the centralized FCP/SAN huge storage technology is introduced in terms of its scalability, throughput, and connectivity performances.