Proposed Simulation Framework Research Articles

Chronological operation simulation framework for regional power system under high penetration of renewable energy using meteorological data

Chronological operation simulation (COS) is an essential tool for planning and analyzing power systems under high penetration of renewable energy. Conventional COS methods heavily depend on the availability of renewable power output data to obtain accurate results, and often require hours or even days of computational time while the sequential simulation could easily get infeasible for power systems with intensive flexibility. To cover the absence of output data for newly proposed wind and solar projects and accelerate the computation speed, this paper proposes a novel COS simulation framework for regional power systems with high penetration of renewable energies using meteorological data. The proposed simulation framework consists of the following three steps: data preparation, modeling and solving, and result output. In the data preparation step, wind, solar power output profiles and heat demands are converted from public accessible meteorological data. Then in the modeling and solving step, a unit commitment based COS model for simulating the hourly operation of power and heat sectors is proposed, and the proposed model is solved with a time domain partitioning (TDP) and a rollback mechanism to accelerate the computation speed as well as avoiding infeasible solutions. The accuracy of the wind and solar power output converted from meteorological data is verified through comparing with measured power output. Moreover, the feasibility and accuracy of utilizing the proposed COS framework to simulate the operation of a real regional power system is also verified through the 2015 annual operation statistics of the Northwest China Grid.

VIPS: A simulator for platoon system evaluation

Development of intelligent behaviors for vehicles has to cope with rigorous specifications. Many tests are performed for verification, validation and a detailed study of resulting behaviors. In this workflow, testing algorithms with real vehicles is a cornerstone step in developing new intelligent features for future transportation systems. This step requires a lot of experiments before efficiently set up embedded autonomous systems. However, the development of such tests is not linear and it highly depends on external variable factors (weather, hardware or software issues, etc.). To overcome these issues, it is possible to carry out a first series of validation under a simulation framework. In this paper, we describe a simulation platform called VIPS (Vehicles In Platoon Simulator), which provides a virtual environment designed to test and validate platoon control approaches, as close as possible to reality, before bringing them in the real vehicle system. Among the features provided by the simulator, one main contribution is the direct matching between perception and control of both real and virtual vehicles. Moreover, VIPS is also able to deal with perturbations, which are dynamically added to running scenarios so as to reproduce real world conditions. Simulation results in the context of platoon control systems show the benefits of the proposed simulation framework.

Intelligent viewpoint selection for efficient CT to video registration in laparoscopic liver surgery

PurposeMinimally invasive surgery offers advantages over open surgery due to a shorter recovery time, less pain and trauma for the patient. However, inherent challenges such as lack of tactile feedback and difficulty in controlling bleeding lower the percentage of suitable cases. Augmented reality can show a better visualisation of sub-surface structures and tumour locations by fusing pre-operative CT data with real-time laparoscopic video. Such augmented reality visualisation requires a fast and robust video to CT registration that minimises interruption to the surgical procedure.MethodsWe propose to use view planning for efficient rigid registration. Given the trocar position, a set of camera positions are sampled and scored based on the corresponding liver surface properties. We implement a simulation framework to validate the proof of concept using a segmented CT model from a human patient. Furthermore, we apply the proposed method on clinical data acquired during a human liver resection.ResultsThe first experiment motivates the viewpoint scoring strategy and investigates reliable liver regions for accurate registrations in an intuitive visualisation. The second experiment shows wider basins of convergence for higher scoring viewpoints. The third experiment shows that a comparable registration performance can be achieved by at least two merged high scoring views and four low scoring views. Hence, the focus could change from the acquisition of a large liver surface to a small number of distinctive patches, thereby giving a more explicit protocol for surface reconstruction. We discuss the application of the proposed method on clinical data and show initial results.ConclusionThe proposed simulation framework shows promising results to motivate more research into a comprehensive view planning method for efficient registration in laparoscopic liver surgery.

ExRET-Opt: An automated exergy/exergoeconomic simulation framework for building energy retrofit analysis and design optimisation

Energy simulation tools have a major role in the assessment of building energy retrofit (BER) measures. Exergoeconomic analysis and optimisation is a common practice in sectors such as the power generation and chemical processes, aiding engineers to obtain more energy-efficient and cost-effective energy systems designs. ExRET-Opt, a retrofit-oriented modular-based dynamic simulation framework has been developed by embedding a comprehensive exergy/exergoeconomic calculation method into a typical open-source building energy simulation tool (EnergyPlus). The aim of this paper is to show the decomposition of ExRET-Opt by presenting modules, submodules and subroutines used for the framework’s development as well as verify the outputs with existing research data. In addition, the possibility to perform multi-objective optimisation analysis based on genetic-algorithms combined with multi-criteria decision making methods was included within the simulation framework. This addition could potentiate BER design teams to perform quick exergy/exergoeconomic optimisation, in order to find opportunities for thermodynamic improvements along the building’s active and passive energy systems. The enhanced simulation framework is tested using a primary school building as a case study. Results demonstrate that the proposed simulation framework provide users with thermodynamic efficient and cost-effective designs, even under tight thermodynamic and economic constraints, suggesting its use in everyday BER practice.

Analysis and Operational Challenges of Dynamic Ride Sharing Demand Responsive Transportation Models

Abstract: There is a wide evidence that sustainable mobility is not only a technological question, automotive technology will be part of the solution as a necessary but not sufficient condition, sufficiency is emerging as a combination of a paradigm shift from car ownership to vehicle usage consequence of socio-economic changes, with the application of Information and Communication Technologies (ICT) that make possible for a user to have access to a mobility service from anywhere to anywhere at any time. Among the many emergent mobility services Multiple Passenger Ridesharing and its variants look the more promising. However, implementations of these systems accounting specifically for time dependencies, and time windows reflecting users' needs raise challenges in terms of real-time fleet dispatching and dynamic route calculation. On the other hand the feasibility and impacts analysis in terms of the many factors influencing the behavior of the system, as for example the service demand, the size of the service fleet, the capacity of the shared vehicles, the time windows requirements, soft or tight. This paper analyzes both aspects. The first is approached in terms of a Decision Support System whose solutions are computed in terms of ad hoc heuristics of variants of Pick Up and Delivery Problems with Time Windows and Feasibility and Profitability criteria rooted on Dynamic Insertion Heuristics. For the evaluation of the applications a Simulation Framework is proposed based on a microscopic simulation model that emulates real-time traffic conditions and a real traffic information system, and interacts with the Decision Support System feeding it with the required data to make the decisions that are implemented in the simulation to emulate the behavior of the shared fleet. The proposed simulation framework has been implemented in a model of Barcelona's Central Business District. The paper is completed with the discussion of the achieved results.

SmartBuilds: An Energy and Power Simulation Framework for Buildings and Districts

We introduce a district level multiple buildings energy and power simulation framework. At the building level, the proposed simulation framework, SmartBuilds, leverages EnergyPlus as the core simulation engine for building energy assessment, thereby benefiting from the capabilities of a widely accepted and used state-of-the-art modeling tool. Building models may include batteries for energy storage and renewable energy generators: PV arrays and wind turbines. At the district level, one of the main goals is to provide a versatile platform for the simulation and optimization of the interaction between the electric grid and buildings as well as of the interaction between buildings. Because buildings can participate in intelligent social-like activities through which energy tokens/budgets can be exchanged, the tools provide collective optimization opportunities beyond the usual techniques applied at building level. This paper introduces SmartBuilds’ architecture and demonstrates its usefulness in scenarios where multiple buildings are simulated concurrently to assess and seek operating schedules for battery energy storage systems that minimize the overall energy consumption at the district level.

공공보건을 고려한 시뮬레이션 연계기반 속도관리전략 평가기법 개발

최근 교통안전과 공공보건에 대한 관심이 증대됨에 따라 친환경 교통시스템의 설계 및 구축의 필요성도 높아지고 있다. 교통의 패러다임 변화 및 환경성 관심의 증대로 공공보건 및 교통안전 증진을 위한 교통관리전략이 요구됨에 따라 본 연구에서는 이를 평가할 수 있는 시뮬레이션 연계기반의 평가방법론을 개발하는 연구를 수행하였다. 이를 위해 교통시뮬레이션 및 환경시뮬레이션을 연계하여 교통관리전략의 효과를 미시적 및 거시적 관점으로 통합평가 할 수 있는 분석 툴과 절차를 제시하였다. 본 연구에서 제안하는 방법론을 교통정온화기법을 바탕으로 하는 속도관리전략의 효과를 평가하는데 적용하여 분석사례를 제시하였다. 분석결과 시케인을 적용한 시나리오가 종합적으로 기존 미설치의 경우보다 우수한 것으로 도출되어 기존의 교통환경을 개선할 수 있을 것으로 판단된다. 따라서 무분별한 과속방지턱 보다는 효과적인 속도감속유도를 위한 타 시설을 고려할 필요가 있다. 본 연구의 결과는 공공보건 및 교통안전 등 다양한 요소를 고려한 교통관리전략 수립 시 정책결정자의 의사결정을 효과적으로 지원할 것으로 판단된다. Recent interests in both vehicle emissions and public health have facilitated the development of more eco-friendly transportation systems. This study proposed an integrated simulation approach for evaluating the effectiveness of speed management strategies from the various perspectives including safety, operational efficiency, and environmental compatability. Those simulation methods include driving simulation, traffic flow simulation, emissions simulation, and air dispersion simulation. An essence of the proposed simulation framework is to create the systematic connection of each simulation method toward the evaluation of effectiveness of speed management strategies. As an example, chicane and speed hump in residential area were evaluated by the proposed method. It is expected that the proposed simulation-based approach would be effectively used for the decision-making process in selecting better alternatives considering both safety and public health.

Efficient reliability evaluation methodologies for combinational circuits

Reliability evaluation methodologies have become important in circuit design. In this paper, we focus on the probabilistic transfer matrix (PTM), which has proven to be a gate-level approach for accurately assess the reliability of a combinational circuit with penalty in simulation runtime and memory usage. In order to improve its efficiency, several methodologies based on traditional PTM are proposed. A general tool is developed to calculate the reliability of a circuit with efficient computation methods based on an optimized PTM (denoted as ECPTM), which achieves runtime and memory usage improvement. Experiments demonstrate how the proposed simulation framework, combined with traditional PTM method, can provide significant reduction in computation runtime and memory usage with different benchmark circuits.

Automated wireless video surveillance: an evaluation framework

In the past years, surveillance systems have attracted both industries and researchers due to its importance for security. Automated Video Surveillance (AVS) systems are established to automatically monitor objects in real-time. Employing wireless communication in an AVS system is an attractive solution due to its convenient installation and configuration. Unfortunately, wireless communication, in general, has limited bandwidth, not to mention the intrinsic dynamic conditions of the network (e.g., collision and congestion). Many solutions have been proposed in the literature to solve the bandwidth allocation problem in wireless networks, but much less work is done to design evaluation frameworks for such solutions. This paper targets the demand for a realistic wireless AVS system simulation framework that models and simulates most of the details in a typical wireless AVS framework. The proposed simulation framework is built over the well-known NS-3 network simulator. This framework also supports the testing and the evaluation of cross-layer solutions that manages many factors over different layers of AVS systems in the wireless 802.11 infrastructure network. Moreover, the simulation framework supports the collection of many used performance metrics that are usually used in AVS system performance evaluation.

A simulation framework for measuring robustness of incentive mechanisms and its implementation in reputation systems

In game theoretical analysis of incentive mechanisms, all players are assumed to be rational. Since it is likely that mechanism participants in the real world may not be fully rational, such mechanisms may not work as effectively as in the idealized settings for which they were designed. Therefore, it is important to evaluate the robustness of incentive mechanisms against various types of agents with bounded rational behaviors. Such evaluations would provide us with the information needed to choose mechanisms with desired properties in real environments. In this article, we first propose a general robustness measure, inspired by research in evolutionary game theory, as the maximal percentage of invaders taking non-equilibrium strategies such that the agents sustain the desired equilibrium strategy. We then propose a simulation framework based on evolutionary dynamics to empirically evaluate the equilibrium robustness. The proposed simulation framework is validated by comparing the simulated results with the analytical predictions based on a modified simplex analysis approach. Finally, we implement the proposed simulation framework for evaluating the robustness of incentive mechanisms in reputation systems for electronic marketplaces. The results from the implementation show that the evaluated mechanisms have high robustness against a certain non-equilibrium strategy, but is vulnerable to another strategy, indicating the need for designing more robust incentive mechanisms for reputation management in e-marketplaces.

Numerical simulations of elastic wave propagation using graphical processing units—Comparative study of high-performance computing capabilities

Abstract High-performance computing is important in many areas of engineering. Increasing capabilities of modern workstations open new possibilities in scientific computing. This paper demonstrates how graphical processing units can be used efficiently for large models of elastic wave propagation in complex media. The method is based on the local interaction simulation approach and a parallel algorithm architecture. The focus of the work presented is on numerical implementation and covers aspects related to software modular architecture, computer memory organisation and optimisation. A domain decomposition approach allowing for calculations using multiple-GPU configurations is proposed, implemented and examined. The performance of the proposed simulation framework is tested for numerical models of different sizes, various computing precisions and hardware platforms. The results obtained are discussed in terms of graphical processing unit limitations. Obtained results indicate significant speed-up factors comparing to calculations using central processing units or different modelling approaches.

Simulation studies as designed experiments: the comparison of penalized regression models in the "large p, small n" setting.

New algorithms are continuously proposed in computational biology. Performance evaluation of novel methods is important in practice. Nonetheless, the field experiences a lack of rigorous methodology aimed to systematically and objectively evaluate competing approaches. Simulation studies are frequently used to show that a particular method outperforms another. Often times, however, simulation studies are not well designed, and it is hard to characterize the particular conditions under which different methods perform better. In this paper we propose the adoption of well established techniques in the design of computer and physical experiments for developing effective simulation studies. By following best practices in planning of experiments we are better able to understand the strengths and weaknesses of competing algorithms leading to more informed decisions about which method to use for a particular task. We illustrate the application of our proposed simulation framework with a detailed comparison of the ridge-regression, lasso and elastic-net algorithms in a large scale study investigating the effects on predictive performance of sample size, number of features, true model sparsity, signal-to-noise ratio, and feature correlation, in situations where the number of covariates is usually much larger than sample size. Analysis of data sets containing tens of thousands of features but only a few hundred samples is nowadays routine in computational biology, where “omics” features such as gene expression, copy number variation and sequence data are frequently used in the predictive modeling of complex phenotypes such as anticancer drug response. The penalized regression approaches investigated in this study are popular choices in this setting and our simulations corroborate well established results concerning the conditions under which each one of these methods is expected to perform best while providing several novel insights.

Safety and Security in Fresh Good Supply Chain

Abstract This paper proposes a model aimed at investigating safety and security issues in fresh good supply chain. Particular attention is paid on fresh goods contamination since the increasing complexity of supply chains makes these events more likely to happen. To this end, a discrete event simulator (DES) underpinned by an analytical model has been developed as a support tool for prevention and mitigation. Indeed, the simulation model is able to recreate the disruption wave propagation along the supply chain due to a contamination event as well as the effects on the dynamic evolution of contaminated products demand taking into account complex phenomena like media campaigns. In addition, even the economic impacts in terms of costs (i.e. transportation costs, inventory costs, and lost sales) can be assessed. The potentials of the proposed simulation framework have been investigated in a real case study of a fresh food supply chain located in the north of Italy.

An integrated cyber-physical simulation environment for smart grid applications

The concept of Cyber-Physical Systems (CPSs), which combine computation, networking, and physical processes, is considered to be beneficial to smart grid applications. This study presents an integrated simulation environment to provide a unified platform for the investigation of smart grid applications involving power grid monitoring, communication, and control. In contrast to the existing approaches, this environment allows the network simulator to operate independently, importing its results to the power system simulation. This resolves conflicts between discrete event simulation and continuous simulation. In addition, several data compensation methods are proposed and investigated under different network delay conditions. A case study of wide-area monitoring and control is provided, and the efficiency of the proposed simulation framework has been evaluated based on the experimental results.

An Event-Based Simulation Framework to Examine the Response of Power Grid to the Charging Demand of Plug-In Hybrid Electric Vehicles

This paper describes the development of a discrete-event simulation framework that emulates the interactions between the power grid and plug-in hybrid electric vehicles (PHEVs) and examines whether the capacity of the existing power system can meet the PHEV load demand. The probability distribution functions for the arrival time and energy demand of each vehicle are extracted from real-world statistical transportation data. The power grid's limited generation and transmission capacities are considered to be the major constraints. Therefore, vehicles may have to wait to receive any charge. The proposed simulation framework is justified and described in some detail in applying it to two real cases in the United States to determine certain regions' grid potential to support PHEVs. Both Level-1 and -2 charging are considered.

Simulation Framework for Modeling Large-Scale Flexible Transit Systems

Despite the prevalent use of simulation methods in a majority of areas in transportation research, transit and paratransit research has not relied heavily on simulation models, not only because traditional transit studies do not necessarily require simulation techniques but also because proper simulation packages are not available for modeling innovative transit systems. This study proposes a new type of simulation framework, targeting large-scale flexible transit systems with various vehicle operation schemes. The intent of this study is to describe the generalized concepts and the detailed architecture of the framework developed for urban transportation networks. A comprehensive process for the framework development, including considerations of simulation data conversion and user interface design, is discussed. Two real-time flexible transit applications are modeled with the proposed simulation framework: high coverage point-to-point transit and real-time shuttle service. Detailed simulation results are provided, and the importance of simulation design and operational features is addressed. The results also show that the framework can model realistic large networks several times faster than real time with standard desktop computers; these results raise the possibility of its use in real-time optimization schemes as well as for synchronous modeling with commercial road traffic simulators.

On the Mobility Scenario Implementation Using a Graphical P2P Discrete Event Simulator for the Bittorrent Protocol

Peer-to-Peer computing is nowadays the application platform which utilizes a novel distributed computing paradigm. It allows any number of participants to exchange and coordinate their resources with minimum overhead through centralized servers/services. This paradigm is also gaining ground in mobile computing environments. By merging the wireless and the static worlds of Peer-to-Peer applications, new services emerge. As Peer-to-Peer networks have nowadays become the basis for efficiently sharing data among users (both wireless and static) this work elaborates on the design of a new simulation framework via which, a mobility-based scenario can be utilized using the Bittorrent protocol. The framework uses a structured-based overlay for the static peers, and unstructured for mobile peers. Many parameters were introduced for the diffusion process and the seeding techniques that are utilized by the Bittorrent simulation framework. By using the Object Oriented design paradigm the proposed simulation framework is developed to be highly scalable being capable to potentially host new components. The simulation tool can encompass a scenario with partial mobility characteristics in a Peer-tracker and a Peer-to-Peer communication enhancement scheme. The proposed simulation framework can evaluate effectively the scalable mobility and can estimate the availability of requested resources of each individual user (both mobile and static). Finally the created simulation framework and the designed modules take into consideration the active intercluster peer participation and evaluate a degree of participation while resources are being exchanged.

A framework for service enterprise workflow simulation with multi-agents cooperation

Process dynamic modelling for service business is the key technique for Service-Oriented information systems and service business management, and the workflow model of business processes is the core part of service systems. Service business workflow simulation is the prevalent approach to be used for analysis of service business process dynamically. Generic method for service business workflow simulation is based on the discrete event queuing theory, which is lack of flexibility and scalability. In this paper, we propose a service workflow-oriented framework for the process simulation of service businesses using multi-agent cooperation to address the above issues. Social rationality of agent is introduced into the proposed framework. Adopting rationality as one social factor for decision-making strategies, a flexible scheduling for activity instances has been implemented. A system prototype has been developed to validate the proposed simulation framework through a business case study.

Physics-Based SPICE-Compatible Compact Model for Simulating Hybrid MTJ/CMOS Circuits

A simulation framework that can comprehend the impact of material changes from the device level to the system level design can be of great value, especially to evaluate the impact of emerging devices on various applications. To that effect, we developed a SPICE-based hybrid magnetic tunnel junction (MTJ)/CMOS simulator, which can be used to explore new opportunities in large scale system design. In the proposed simulation framework, MTJ modeling is based on Landau-Lifshitz-Gilbert (LLG) equation incorporating both spin-torque and external magnetic field(s). LLG, along with heat diffusion equation, thermal variations, and electron transport, is implemented using SPICE-in-built voltage-dependent current sources and capacitors. The proposed simulation framework is flexible because the physical device parameters such as MgO thickness, ferromagnet material anisotropy (Ku), and device dimensions are user-defined parameters. Furthermore, we benchmarked this model with experiments in terms of switching current density (JC), switching time (TSWITCH), and tunneling magnetoresistance. Finally, we used the simulation framework to study different MTJ structures, such as in-plane magnet anisotropy and perpendicular magnet anisotropy, the impact of parametric process variations and temperature on the yield of spin transfer torque magnetoresistive random access memories, magnetic flip-flops, and spin-torque oscillators.

Investigation of Underwater Acoustic Networking Enabling the Cooperative Operation of Multiple Heterogeneous Vehicles

AbstractIn this paper, we investigate the creation of an underwater acoustic network to support marine operations based on static and mobile nodes. Each underwater device combines communication, networking, and sensing capabilities and cooperates with the other devices in coordinated missions. The proposed system is built upon the SUNSET framework, providing acoustic communications and networking capabilities to autonomous underwater vehicles, autonomous surface vessels, and moored systems, using underwater acoustic modems. Specific solutions have been developed and tested to control the underwater nodes acoustically and to instruct the vehicles on keeping a given formation using acoustic links. One of the novelties of our approach has been the development and utilization of a realistic simulation infrastructure to provide a very accurate representation of all the dynamic systems involved in the network, modeling the vehicle dynamics, the acoustic channel, and the communication messages. This infrastructure has been extensively used to investigate and validate the proposed solutions under different environmental conditions before the actual deployment of devices. Several experiments were then conducted in the laboratory and in the field. The experimental results have confirmed the effectiveness of the proposed solutions and the reliability of the proposed simulation framework in estimating system performance.