Agent-Based Simulation for Interconnection-Scale Renewable Integration and Demand Response Studies

This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council(WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methods presented.

Agent-Based Simulation for Analyzing Network Formation with Learning Dynamics

In game theoretic context, it is assumed that the decision maker has the extraordinary skills of reasoning and calculation. This assumption is called ＂perfect rationality＂. A player with perfect rationality can solve complex problems without making mistakes. However, recently, many studies have restricted this rationality or the structure of game. These restrictions are called ＂bounded rationality.＂ The authors also focus on bounded rationality, but with learning dynamics and complex networks. A complex network covers a wide area. Currently, a wide range of studies have not only investigated network formation and the characteristics of a formed network, but also analyzed situations where a network is already provided. In addition, in an analysis using game theory, a prisoners＇ dilemma type game was used to investigate how a change in the network structure would affect the players＇ relationships Therefore, our model employs decision makers with learning dynamics and describes the interaction of decision makers as a network. The purpose of this study is to examine the behavior of the decision maker with learning dynamics and the formation of networks by the interaction of decision makers through an agent-based simulation.

An agent-based simulation with NetLogo platform to evaluate forward osmosis process(PRO Mode)

Forward osmosis(FO), as an emerging technology, is influenced by different factors such as operating conditions,module characteristics, and membrane properties. The general aim of this study was to develop a suitable(flexible,comprehensive, and convenient to use) computational tool which is able to simulate osmosis through an asymmetric membrane oriented in pressure retarded osmosis(PRO) mode in a wide variety of scenarios. For this purpose, an agent-based model was created in NetLogo platform, which is an easy-to-use application environment with graphical visualization abilities and well suited for modeling a complex system evolving over time. The simulation results were validated with empirical data obtained from literature and a great agreement was observed. The effect of various parameters on process performance was investigated in terms of temperature,cross-flow velocity, length of the module, pure water permeability coefficient, and structural parameter of the membrane. Results demonstrated that the increase in all parameters, except structural parameter of the membrane and the length of module led to the increase of average water flux. Moreover, nine different draw solutes were selected in order to assess the influence of net bulk osmotic pressure difference between the draw solution(DS) and feed solution(FS)(known as the driving force of FO process) on water flux. Based on the findings of this paper, the performance of FO process(PRO mode) can be efficiently evaluated using the NetL ogo platform.

Using agent-based simulation to assess diseaseprevention measures during pandemics

Despite the growing interest in macroscopic epidemiological models to deal with threats posed by pandemics such as COVID-19,little has been done regarding the assessment of disease spread in day-to-day life,especially within buildings such as supermarkets where people must obtain necessities at the risk of exposure to disease.Here,we propose an integrated customer shopping simulator including both shopper movement and choice behavior,using a force-based and discrete choice model,respectively.By a simple extension to the force-based model,we implement the following preventive measures currently taken by supermarkets;social distancing and one-way systems,and different customer habits,assessing them based on the average individual disease exposure and the time taken to complete shopping(shopping efficiency).Results show that maintaining social distance is an effective way to reduce exposure,but at the cost of shopping efficiency.We find that the one-way system is the optimal strategy for reducing exposure while minimizing the impact on shopping efficiency.Customers should also visit supermarkets less frequently,but buy more when they do,if they wish to minimize their exposure.We hope that this work demonstrates the potential of pedestrian dynamics simulations in assessing preventative measures during pandemics,particularly if it is validated using empirical data.

Assessment of Multiple Working Condition System Reliability with Agent-Based Simulation Method

The mission reliability assessment plays a great role in logistics planning and supporting resource optimization of complex system.But the current problem,which is difficult to solve,is how to model and analyze the characters of system reliability under the complex mission profile.In order to solve the problem,an agentbased simulation method was used to assess reliability for complex systems with various random working conditions.A multi-working condition simulation agent(MA)was designed and used to simulate the random transferring process of working conditions of system,and it cooperated with system simulation agents(SAs)and unit simulation agents(UAs)to realize system mission reliability(MR)simulation.Through simulation experiments,effect of multiple working conditions mission on the reliability of system was analyzed by comparing with the basic reliability condition.Feasibility and efficiency of the method were proved through simulation experiments of the case system.The research result provides a viable and useful method and a solution for MR analysis and assessment of complex systems in multi-working conditions,which can help to evaluate the reliability of operating system orienting to the practical mission and environment,and it is meaningful for the reliability analysis and the design of complex systems.

Assessing the impacts of traffic calming at network level:A multimodal agent-based simulation

The reduction of speed limits in urban roads through traffic calming schemes intends to ensure safer traffic conditions among road users by reducing the probability related to the occurrence of severe accident.Looking it from a different perspective,traffic calming measures can potentially resolve congestion problems at the same time by lowering the overall accessibility and attractiveness of private cars in urban areas.This study proposes a new methodological approach to explore and assess the direct impacts of traffic calming in the transport system efficiency of a metropolitan area.The multi-agent transport simulation(MATSim)and Open-Berlin scenario are utilized to perform this simulation experiment.By developing a new external tool,the free flow speed and road capacity of each network link is updated based on new speed limits and different compliance rates,which are defined per road hierarchy level.The test scenarios that are formulated present radical conditions,where the speed limit in most urban roads of Berlin drops to 30 km/h or even 15 km/h.The findings of this study show a considerably high increase in trips,passenger hours,and passenger kilometers using public transport modes,when traffic calming links are introduced,the reserve change is observed in private cars trips.Although the speed limits are decreased in inner urban roads in most of the scenarios,the decrease of average travel speed of private cars is not so high as it was expected.Surprisingly,private cars are used for longer distances in all test scenarios.Car drivers seem to use already existed motorways and private road to commute.In simulations,driver compliance to the new speed limits seems to be a determinant factor that is strongly influenced by the design interventions applied in a traffic calming area.

Complex adaptive system theory,agent-based modeling,and simulation in dominant technology formation

Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.

Evaluating the flooding level impacts on urban metro networks and travel demand:behavioral analyses,agent-based simulation,and large-scale case study

With urban residents’increasing reliance on metro systems for commuting and other daily activities,extreme weather events such as heavy rainfall and flooding impacting the metro system services are becoming increasingly of concern.Plans for such emergency interruptions require a thorough understanding of the potential outcomes on both the system and individual component scales.However,due to the complex dynamics,constraints,and interactions of the elements involved(e.g.,disaster,infrastructure,service operation,and travel behavior),there is still no framework that comprehensively evaluates the system performance across different spatiotemporal scales and is flexible enough to handle increasingly detailed travel behavior,transit service,and disaster information data.Built on an agent-based model(ABM)framework,this study adopts a data-driven ABM simulation approach informed by actual metro operation and travel demand data to investigate the impact of flood-induced station closures on travelers as well as the overall system response.A before-after comparison is conducted where the traveler behaviors in disaster scenarios are obtained from a discrete choice model of alternative stations and routes.A case study of the Shanghai Metro is used to demonstrate the ability of the proposed approach in evaluating the impacts of flood-induced station closures on individual traveler behavior under normal operation and a series of water level rise scenarios of up to 5m.It was found that,when the flood-induced station closures only affect a few river-side stations in the city center,the travelers experience only minor disruptions to their trips due to the availability of unaffected stations nearby as a backup.However,as the water level increases and more stations(mainly in the suburban area)are affected,up to 25%of trips are no longer being fulfilled due to the loss of entrances,exits,or transfer links.The system experiences overall less crowdedness in terms of passenger volume and platform waiting time with a few exceptions of increased passenger load due to concentrations of passenger flows to alternative stations under flooding-induced station closures.The proposed approach can be adapted to other disaster scenarios to reveal the disaster impacts on both aggregated and disaggregated levels and guide the design of more spatio-and temporally-targeted emergency plans for metro systems.

COVID-19 transmission in U.S.transit buses:A scenario-based approach with agent-based simulation modeling(ABSM)

The transit bus environment is considered one of the primary sources of transmission of the COVID-19(SARSCoV-2)virus.Modeling disease transmission in public buses remains a challenge,especially with uncertainties in passenger boarding,alighting,and onboard movements.Although there are initial findings on the effectiveness of some of the mitigation policies(such as face-covering and ventilation),evidence is scarce on how these policies could affect the onboard transmission risk under a realistic bus setting considering different headways,boarding and alighting patterns,and seating capacity control.This study examines the specific policy regimes that transit agencies implemented during early phases of the COVID-19 pandemic in USA,in which it brings crucial insights on combating current and future epidemics.We use an agent-based simulation model(ABSM)based on standard design characteristics for urban buses in USA and two different service frequency settings(10-min and 20-min headways).We find that wearing face-coverings(surgical masks)significantly reduces onboard transmission rates,from no mitigation rates of 85%in higher-frequency buses and 75%in lower-frequency buses to 12.5%.The most effective prevention outcome is the combination of KN-95 masks,open window policies,and half-capacity seating control during higher-frequency bus services,with an outcome of nearly 0%onboard infection rate.Our results advance understanding of COVID-19 risks in the urban bus environment and contribute to effective mitigation policy design,which is crucial to ensuring passenger safety.The findings of this study provide important policy implications for operational adjustment and safety protocols as transit agencies seek to plan for future emergencies.

Agent-based simulation for symmetric electricity market considering price-based demand response

With the development of electricity market mechanism and advanced metering infrastructure(AMI),demand response has become an important alternative solution to improving power system reliability and effi-ciency. In this paper, the agent-based modelling and simulation method is applied to explore the impact of symmetric market mechanism and demand response on electricity market. The models of market participants are established according to their behaviors. Consumers’ response characteristics under time-of-use(TOU) mechanism are also taken into account. The level of clearing price and market power are analyzed and compared under symmetric and asymmetric market mechanisms. The results indicate that the symmetric mechanism could effectively lower market prices and avoid monopoly.Besides, TOU could apparently flatten the overall demand curve by enabling customers to adjust their load profiles,which also helps to reduce the price.

STUDIES ON HORIZONTAL COMPETITION AMONG HOMOGENOUS RETAILERS THROUGH AGENT-BASED SIMULATION

This paper adopts agent-based simulation to study the horizontal competition among homogenous price-setting retailers in a one-to-many supply chain (a supply chain consists of one supplier and multiple retailers). We model the supplier and retailers as agents, and design their behavioral rules respectively. The results show that although the agents learn individually based on their own experiences, the system converges asymptotically to near Nash equilibrium steady states. When analyzing the results, we first discuss the properties of these steady states. Then based on these properties, we analyze the effects of the retailers’ horizontal competition on the retail prices, retailers’ profits and supplier’s revenue.

Agent-Based Simulation of Rumor Propagation on Social Network Based on Active Immune Mechanism

To simulate the rumor propagation process on online social network during emergency, a new rumor propagation model was built based on active immune mechanism. The rumor propagation mechanisms were analyzed and corresponding parameters were defined. BA scale free network and NW small world network that can be used for representing the online social network structure were constructed and their characteristics were compared. Agent-based simulations were conducted on both networks and results show that BA scale free network is more conductive to spreading rumors and it can facilitate the rumor refutation process at the same time. Rumors paid attention to by more people is likely to spread quicker and broader but for which the rumor refutation process will be more effective. The model provides a useful tool for understanding and predicting the rumor propagation process on online social network during emergency, providing useful instructions for rumor propagation intervention.

基于Plant Simulation的化纤自动落丝系统仿真实验分析

基于Plant Simulation软件,构建一种化纤自动落丝系统的3D数字化模型,对系统效率关键输入因子进行参数化设置,将系统各工位三维数字模型导入软件中建立层次化运动机构图形结构,并运用Simltalk语言实现三维动作仿真,通过基础物理参数设置,保证了仿真数字化模型与现实系统更具一致性。通过多级实验设计分析了系统影响因子对于系统效率的影响特性曲线,并进一步通过动态参数化实验方法,计算出双输入因子对系统效能影响的敏感度。该实验结果可为化纤自动落丝系统的建设成本控制与可行性分析提供指导,具有较好的工程应用价值。

基于Simulation X的多轴转向系统功能安全仿真分析

基于ISO 26262《道路车辆功能安全》的标准要求,对特种车的多轴电液转向系统进行分析,以提高系统的安全性和可靠性。运用Simulation X软件建立详细的多轴特种车仿真模型,通过模拟故障模式注入进行仿真试验。对仿真结果和数据进行分析,评估得到故障的严重性、暴露度和可控性,从而确定相应的汽车安全完整性等级。基于故障注入仿真的汽车功能安全分析方法,在系统早期设计阶段可以作为评估架构安全性的重要手段。

Agent-based Simulation Systems for Emergency Management

Emergencies, which are very difficult to be forecasted, would always bring about huge harm to people. Therefore, to find ways to reduce such devastating effects, researches on emergency management have turned to be paramount. Nowadays, the rapid development of computer technology has supplied a new and effective idea for the researches of emergency management, namely that the researches can be done in computers by performing simulation experiments according to the artificial societies, computational experiments, parallel execution （ACP） approach. Guided by this approach, this paper has proposed one agent-based prototype simulation system to research emergency management. Firstly, structure of the simulation system oriented to emergency management was analyzed and designed. Then a simulation system oriented to public health emergency management was constructed to study the transmission of infectious diseases. Finally, several experiments were carried out based on the system, with several significant conclusions having also been obtained.

基于Plant Simulation的压气机叶片型线加工产线分析与优化

运用专业仿真软件Plant Simulation,根据压气机叶片型线机械加工工艺特点和物料运行流程建立生产线仿真模型,从产能、设备利用率及产线瓶颈等多方面进行仿真分析与优化。结果表明:Plant Simulation仿真平台的仿真可以找出规划设计方案中存在的问题并验证方案的合理性。该仿真结果为型线机械加工产线的优化设计提供了可靠依据,达到了节约投资成本和缩短设计周期的目的。

Exhaustive review of acceleration strategies for Monte Carlo simulations in photon transit

Monte Carlo simulation techniques have become the quintessence and a pivotal nexus of inquiry in the realm of simulating photon movement within biological fabrics.Through the stochastic sampling of tissue archetypes delineated by explicit optical characteristics,Monte Carlo simulations possess the theoretical capacity to render unparalleled accuracy in the depiction of exceedingly intricate phenomena.Nonetheless,the quintessential challenge associated with Monte Carlo simulation methodologies resides in their extended computational duration,which significantly impedes the refinement of their precision.Consequently,this discourse is specifically dedicated to exploring innovations in strategies and technologies aimed at expediting Monte Carlo simulations.It delves into the foundational concepts of various acceleration tactics,evaluates these strategies concerning their speed,accuracy,and practicality,and amalgamates a comprehensive overview and critique of acceleration methodologies for Monte Carlo simulations.Ultimately,the discourse envisages prospective trajectories for the employment of Monte Carlo techniques within the domain of tissue optics.

Global hybrid simulations of soft X-ray emissions in the Earth’s magnetosheath

Earth’s magnetopause is a thin boundary separating the shocked solar wind plasma from the magnetospheric plasmas,and it is also the boundary of the solar wind energy transport to the magnetosphere.Soft X-ray imaging allows investigation of the large-scale magnetopause by providing a two-dimensional(2-D)global view from a satellite.By performing 3-D global hybrid-particle-in-cell(hybrid-PIC)simulations,we obtain soft X-ray images of Earth’s magnetopause under different solar wind conditions,such as different plasma densities and directions of the southward interplanetary magnetic field.In all cases,magnetic reconnection occurs at low latitude magnetopause.The soft X-ray images observed by a hypothetical satellite are shown,with all of the following identified:the boundary of the magnetopause,the cusps,and the magnetosheath.Local X-ray emissivity in the magnetosheath is characterized by large amplitude fluctuations(up to 160%);however,the maximum line-of-sight-integrated X-ray intensity matches the tangent directions of the magnetopause well,indicating that these fluctuations have limited impact on identifying the magnetopause boundary in the X-ray images.Moreover,the magnetopause boundary can be identified using multiple viewing geometries.We also find that solar wind conditions have little effect on the magnetopause identification.The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will provide X-ray images of the magnetopause for the first time,and our global hybrid-PIC simulation results can help better understand the 2-D X-ray images of the magnetopause from a 3-D perspective,with particle kinetic effects considered.

The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation

The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.

Frontogenesis and Frontolysis of a Cold Filament Driven by the Cross-Filament Wind and Wave Fields Simulated by a Large Eddy Simulation

The variations of the frontogenetic trend of a cold filament induced by the cross-filament wind and wave fields are studied by a non-hydrostatic large eddy simulation. Five cases with different strengths of wind and wave fields are studied.The results show that the intense wind and wave fields further break the symmetries of submesoscale flow fields and suppress the levels of filament frontogenesis. The changes of secondary circulation directions—that is, the conversion between the convergence and divergence of the surface cross-filament currents with the downwelling and upwelling jets in the filament center—are associated with the inertial oscillation. The filament frontogenesis and frontolysis caused by the changes of secondary circulation directions may periodically sharpen and smooth the gradient of submesoscale flow fields.The lifecycle of the cold filament may include multiple stages of filament frontogenesis and frontolysis.