To solve the problems of strong uncertainty, dynamics, and high complexity during the operation process in a discrete manufacturing shop floor that produces a variety of variable-volume products, a ...data-driven smart management and control framework of a digital twin shop floor (DTS) is proposed. Its implementation process is analyzed. Five key tasks are illustrated in detail: (1) the construction of a shop floor digital twin (DT) model from the multi-dimensional multi-scale perspective; (2) data acquisition and management technology in a DTS; (3) the real-time data-driven synchronous modeling of the shop floor operating status; (4) the model- and data-driven online prediction of the shop floor operation status; and (5) the multi-agent-based operation decision of a DTS. In addition, for products that are complex to produce on the assembly shop floor, a DT-based smart management and control system named the DT-VPPC is developed. The effectiveness of the proposed method is verified by a specific application example on an assembly shop floor.
Buildings are responsible for over 30% of global final energy consumption and nearly 40% of total CO2 emissions. Thus, rapid penetration of renewable energy technologies (RETs) in this sector is ...required. Integration of renewable energy sources (RESs) into residential buildings should not only guarantee an overall neutral energy balance over long term horizon (nZEB concept), but also provide a higher flexibility, a real-time monitoring and a real time interaction with end-users (smart-building concept). Thus, increasing interest is being given to the concepts of Hybrid Renewable Energy Systems (HRES) and Multi-Energy Buildings, in which several renewable and nonrenewable energy systems, the energy networks and the energy demand optimally interact with each other at various levels, exploring all possible interactions between systems and vectors (electricity, heat, cooling, fuels, transport) without them being treated separately. In this context, the present paper gives an overview of functional integration of HRES in Multi-Energy Buildings evidencing the numerous problems and potentialities related to the application of HRESs in the residential building sector. Building-integrated HRESs with at least two RESs (i.e., wind–solar, solar–geothermal and solar–biomass) are considered. The most applied HRES solutions in the residential sector are presented, and integration of HRES with thermal and electrical loads in residential buildings connected to external multiple energy grids is investigated. Attention is focused on the potentialities that functional integration can offer in terms of flexibility services to the energy grids. New holistic approaches to the management problems and more complex architectures for the optimal control are described.
In recent years, variable speed limit (VSL) strategies have proven to be an efficient control measure to mitigate traffic congestion at freeway bottlenecks. In general, the VSL change time is a ...constant value. However, there are certain limitations in traffic situations handled by a constant cycle VSL. Therefore, in this paper, we develop a dynamic cycle strategy of VSL based on predictive control. We first analyze the applicable situation of the dynamic control cycle and establish a probability model to determine the range of cycle selection. Then, the cell transmission model predicts the parameters of macroscopic traffic flow. Finally, an optimization algorithm is designed that is suitable for this strategy, which optimizes the cycle and speed limit options. An objective optimization function is formulated to minimize the total travel time. A sensitivity analysis is applied to compare different control strategies under a variety of road bottleneck structures by both the numerical analysis and simulation experiments. The simulation results show that the strategies and algorithms proposed in this paper can effectively reduce traffic congestion duration and enhance the service level of a freeway network.
Dedicated lanes for autonomous vehicles (AV) are introduced as an effective strategy to improve mobility in mixed traffic of AVs and heterogeneous drivers. However, adding a new lane is costly, and ...dedicating an existing lane may increase traffic congestion in other lanes. Previous studies investigated the impacts of AV dedicated lanes on throughput at the segment level and/or assumed a fixed route choice. However, AV dedicated lanes change route choice behavior, which affects traffic distribution over the network. Therefore, this study explores the impacts of AV dedicated lanes on the traffic performance of large-scale networks by conducting a network-level cost–benefit analysis on the implementation of AV dedicated lanes under different demand and AV market penetration rate (MPR) scenarios. This study examines the impacts of implementing AV dedicated lanes to freeway links on traffic congestion at corridor and network levels. Various factors are explored: changes in aggregate flow–density relationships, throughput, and average travel times. To this end, DYNASMART-P software is updated to consider AV dedicated lanes and is used to simulate the mixed traffic. Traffic simulation analyses on the large-scale network of Chicago indicate that these impacts depend on the AV MPR, demand level, and AV dedicated lane implementation approach. Dedicated lanes for AVs are beneficial for a high demand level scenario at all AV MPRs. However, for the base demand scenario, (760,000 vehicles during a.m. peak), deploying such lanes is only justified for low AV MPRs. Furthermore, the impacts of AV dedicated lanes on traffic at the network level are different from those on single segments.
Quantifying the complexity of traffic scenarios not only provides an essential foundation for constructing the scenarios used in autonomous vehicle training and testing, but also enhances the ...robustness of the resulting driving decisions and planning operations. However, currently available quantification methods suffer from inaccuracies and coarse‐granularity in complexity measurements due to issues such as insufficient specificity or indirect quantification. The present work addresses these challenges by proposing a comprehensive entropy‐based model for quantifying traffic scenario complexity across multiple dimensions based on a consideration of the essential components of the traffic environment, including traffic participants, static elements, and dynamic elements. In addition, the limitations of the classical information entropy models applied for assessing traffic scenarios are addressed by calculating magnitude entropy. The proposed entropy‐based model is analyzed in detail according to its application to simulated traffic scenarios. Moreover, the model is applied to real world data within a naturalistic driving dataset. Finally, the effectiveness of the proposed quantification model is illustrated by comparing the complexity results obtained for three typical traffic scenarios with those obtained using an existing multi‐factor complexity quantification method.
The study presents an entropy‐based model for quantifying the multi‐ dimensional complexity of traffic scenarios. The proposed model considers both static and dynamic fundamental element's characteristics, which impact traffic participants. Simulation and comparison with existing methods demonstrate its effectiveness and advantage.
Connected and Autonomous Vehicles (CAVs) can receive various information from surrounding vehicles through Vehicle‐to‐Everything (V2X) communication technologies and adjust their car‐following ...behaviour accordingly. Although several studies have evaluated the impact of CAVs on traffic flow stability in a small segment of networks, most approaches are focused on their specific applications considering the trajectory information, and there is a lack of studies analyzing the impact of CAVs on a large‐scale network. This paper proposes a novel viscous continuum traffic model considering the anticipation of space headway, the throttle angle, and brake torque information during cooperative car‐following. The methods employed to develop the new car‐following model and its counterpart continuum traffic model have been described. The linear and non‐linear stability analyses of the newly developed model have been conducted to obtain the critical stability factors in small perturbations. Numerical simulations have been carried out to investigate the effect of the anticipation, the throttle angle, and brake torque information on traffic stability, fuel consumption, and exhaust emissions. The numerical results reveal that the anticipation of space headway and the transmission of the throttle angle and brake torque information during cooperative car‐following manoeuvres can improve the traffic flow stability and reduce fuel consumption and emissions.
This paper proposes a novel viscous continuum traffic model based on the cooperative car‐following behaviour of CAVs considering the anticipation of space headway and the throttle angle‐brake torque transmission.
Alkaline electrolyzers (AELs) have emerged as promising candidates for providing flexible grid services. However, a comprehensive understanding of their operational flexibility has been hindered by a ...lack of consideration of their thermodynamics in previous studies. To address this limitation, this paper presents comprehensive models that analyze the impact of AEL thermodynamics on their operational flexibility. Specifically, a closed-loop thermal model with temperature-stabilizing control is established to capture the temperature evolution, followed by the development of a temperature-dependent U–I model to characterize the influence of temperature on electrical performance. Case studies are conducted to simulate a practical 26 kW AEL facility using Matlab/Simulink. The results demonstrate that the proposed temperature-stabilizing control effectively maintains the temperature at the setpoint when adjusting the power consumed by AELs. Consequently, the power regulation range of AELs increases from 7.4 kW to 16 kW, compared to a simple control that fixes the cooling water flow at 0.02 m3/h. While increasing the fixed water flow to 0.05 m3/h can also enhance the regulation capacity, the proposed control ensures higher system efficiency than that of the fixed flow control. Moreover, the temperature-stabilizing performance of the controller is influenced by the cooling system’s parameters. Hence, a coordinated design approach between the cooling system and temperature controller is recommended to achieve favorable temperature-stabilizing performance.
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