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• A co-simulation model is proposed for parameters selection of vibratory rollers considering multiple systems. • The effectiveness of proposed model is verified by field test of a 20-ton vibratory roller. • The proposed model gives a more accurate results than traditional simulation model. • Optimal working parameters of the vibratory roller are selected by proposed model. The working parameters of vibratory rollers have an important effect on the compaction quality. The traditional method of obtaining the best working parameters through field tests is time-consuming and laborious. In order to determine the best working parameters more conveniently and accurately, a mechanical-hydraulic-finite element co-simulation method is proposed in this paper. This method considers the effect of the hydraulic system on vibration compaction and makes the simulation result as close to the actual condition as possible. By analyzing the change of soil stress and settlement, the effect regulation of working parameters on compaction quality is obtained. The results show that the proposed co-simulation method can accurately reflect the real conditions, and the best compaction quality can be achieved when the walking speed is 3 km/h, the vibration frequency is 24 Hz, and the amplitude is 2.5 mm. The research provides a reference for improving the compaction quality and compacting-related simulation. [ABSTRACT FROM AUTHOR]

The failure mode of a structural component subjected to fire loading is sensitive to its mechanical boundary conditions. It follows that controlling boundary conditions is crucial to obtain a realistic loading scenario with a fire experiment. Hybrid fire testing has been developed for this purpose. Specifically, a structural component under test is loaded using actuators and exposed to fire loading. A coordination algorithm updates actuator setpoints on the fly so that the tested structural component experiences the sought mechanical boundary conditions, e.g., associated with a virtual assembly that is simulated numerically. To enable interoperability of simulation tools and control systems utilized in hybrid testing, a number of middlewares have been proposed, some of which have been adapted to hybrid fire testing. Middlewares facilitate the implementation of hybrid fire testing within the same laboratory. However, the portability of hybrid models from one laboratory to another is critical when different middleware and simulation tools are adopted. A consequence of that is that round-robin verification cannot be easily deployed for hybrid fire testing. In response to this limitation, this paper proposes to craft hybrid fire testing experiments using the Co-Simulation paradigm supported by the Functional Mock-up Interface standard. The methodology is demonstrated experimentally. [ABSTRACT FROM AUTHOR]

This paper introduces multi-use applications to unlock behind-the-meter flexibility by integrating grid-serving capabilities with user-oriented control strategies. We deploy a hierarchical flexibility coordination process in a co-simulation research environment and propose a control strategy prioritizing self-consumption optimization with a secondary focus on grid-serving applications. This approach enhances the viability of behind-the-meter technologies, particularly benefiting battery energy storage systems with high investment costs. It also facilitates active grid operation amid the growing presence of distributed energy resources. The research's key contribution lies in designing an information architecture to efficiently utilize behind-the-meter flexibility for grid-serving processes. The paper demonstrates the feasibility of a multi-use operation, combining user-oriented optimization and grid-serving flexibility provision for local grid congestion management. The implemented control algorithm in a home energy management system achieves grid-serving objectives while maintaining behind-the-meter asset performance. Co-simulation results show that in less than 2.5 % of simulated time steps, transformer utilization exceeds operational limits in both scenarios, indicating the viability of multi-use operation for leveraging new value streams and managing grid congestion simultaneously. • Multi-use applications can unlock flexibility potentials hidden behind-the-meter. • Behind-the-meter flexibility can serve for local grid congestion management. • Stacking grid-serving applications obtains good results regarding utilization. • Multi-use applications can add new value streams to behind-the-meter flexibility. [ABSTRACT FROM AUTHOR]

This paper introduces an advanced co-simulation environment developed to assess the cyber resilience of active distribution grids, with a focus on demand side management concepts. By integrating energy systems, communication networks, and operational technologies, the framework evaluates the impact of cyber threats on the functionality and stability of distribution grids. The focus of this paper is the newly introduced communication simulator, which provides a solution to simulate the communication flow between the different actors with a generalised representation of the protocols used. This approach enables the investigation of system architectures without requiring the specific implementation of, for example, protocol stacks. Utilising the STRIDE framework for comprehensive threat modelling, the framework then simulates cyber–physical disruptions in an abstract manner, thereby allowing for a nuanced understanding of potential vulnerabilities and resilience strategies. A case study demonstrates the application of the framework, highlighting its potential to enhance grid resilience through strategic simulation of various cyber attack scenarios. • Co-simulation to investigate the cyber resilience of demand side management. • Flexible solution for attack simulation based on threat modelling concepts. • Case study investigating a resilience enhancing fallback mechanism. [ABSTRACT FROM AUTHOR]

This paper develops a novel multi-rate, multi-solver co-simulation framework combining dynamic phasors, transient stability, base-frequency dynamic phasors for frequency-adaptive simulation of transients, and electromagnetic transient (EMT) models. This framework subdivides a given power network into several types of subsystems based on the connected devices, required accuracy in representing dynamic details, electrical distance from perturbations, and the intended purpose of the study; as such, the paper describes methods and guidelines to simulate each subsystem using the most appropriate solver and time-step size to maximize simulation efficiency and accuracy. It also addresses the tasks of multiple interfacing and solver interactions that are essential in coupling different solvers. The proposed framework is built around an industrial-grade EMT simulator, to which other solvers are interfaced, enabling access to a variety of power system models and distinct features. The accuracy and efficiency of the framework are demonstrated through co-simulations carried out on a modified version of the 118-bus network, which includes an MMC-HVDC system. • The paper develops a multi-solver co-simulator interfacing EMT, DP, and TS solvers. • The co-simulator allows to simulate different EMT regions using different time-steps. • An MMC-embedded 118-bus system is used to demonstrate the solver's capabilities. • Simulation time comparisons show the computational benefits of the new co-simulator. [ABSTRACT FROM AUTHOR]

This paper presents results and convergence study of the Global–Local Iterative Coupling through the implementation in the commercial software Abaqus making use of the co-simulation engine. A hierarchical modeling and simulation approach is often required to alleviate modeling burdens. Particular focus has been devoted here on convergence acceleration and performance optimization. Two applications in statics with nonlinear material behavior and geometrically nonlinear formulation are considered here: first a holed curved plate under traction with elastic–plastic material, then a pre-stressed bolted joint connecting two plates between each other and subjected to traction load. Three different convergence acceleration techniques are compared in terms of convergence performance and accuracy. An inexact solver strategy is proposed to improve computing time performance. The results show promising results for the coupling technology and constitute a step forward in the availability of non-intrusive multi-scale modeling capabilities for complex structures and assemblies. [Display omitted] • Implementation of the GLIC technique in Abaqus co-simulation engine. • Test of 3 acceleration techniques on 2 challenging use cases of industrial interest. • Test of an inexact solving strategies to enhance performance. [ABSTRACT FROM AUTHOR]

• An unprecedented very large-scale T&D dataset covering Texas is made publicly available. • The sheer size of this dataset is intended to provide a challenge for the scientific community. • This lays the foundation for demonstrating the coordination of T&D. • It can help foster the improvement of algorithms and tools for years to come. Distributed energy resources, such as rooftop solar, have rapidly expanded in recent years, given declining costs and the desire to reduce carbon emissions. With more energy resources located in the lower-voltage distribution system, it is increasingly helpful to utilize combined transmission and distribution (T&D) system models to analyze interactions between these normally-distinct subsystems. This paper proposes a methodology for creating very large-scale, highly detailed, combined T&D systems that are synthetic—that is, free from non-public data—yet still realistic. The methodology creates very large-scale combined T&D systems by merging the most up-to-date techniques for creating synthetic distribution feeder networks with the latest methods for building synthetic, meshed bulk-power transmission networks. This methodology is demonstrated on a T&D system geolocated in Texas, and benchmarked with co-simulation results. Validation demonstrates that the resulting syn -texas-TDgrid synthetic test system realistically represents characteristics found in actual networks, addressing the lack of available T&D test systems. With over 15,000 feeders and 46 million electrical nodes, this T&D dataset has applications for research in optimal power flow algorithms, voltage control, reconfiguration, and T&D coordination schemes under high adoption of distributed energy resources. [ABSTRACT FROM AUTHOR]

As a key equipment in deep-sea drilling and production operations, the riser tensioner provides a nearly constant tensioner for the riser to overcome the influence of the floating platform on the riser when it is makingheave motion with the waves. In the harsh deep-water area, when the tethers of Tension Leg Platform (TLP) failure, the Top Tensioned Risers (TTRs) will jump, resulting in the migration of the riser resonance region, which will cause the parametric resonance and interference phenomenon of the riser. Therefore, based on Adams and AMESim co-simulation, this paper calculates the dynamic characteristics of the displacement tension of the tensioner system on the traditional TLP under tether failure. Based on the dynamic characteristics of the tensioner system, a synchronous control strategy of the displacement tension of the tensioner under tether failure is proposed. The strategy uses the opening of the anti-recoil valve to realize the stable recovery of the riser and adjusts the output tension of the tensioner in the recoil process of the riser through the proportional relief valve. Compared with the traditional control method and non-control method, the effectiveness of this strategy is verified. The results show that the designed displacement tension synchronization control strategy can provide more stable tension for the riser, and the displacement amplitude of the hydraulic cylinder is smaller, which can realize the stable recovery of the riser. Moreover, it is found in many simulations that the opening of the main valve and the displacement curve of the hydraulic cylinder mainly affect the retraction speed of the hydraulic cylinder, and the maximum opening pressure of the proportional relief valve affects the output tension of the tensioner system. • The dynamic characteristics of the tensioner is simulated when the tendon of TLP fails instantaneously. • A hydraulic control system is designed to overcome the influence of a platform on risers. • A double-cavity synchronous control method is adopted for the hydraulic cylinder to realize the compensation control. • Dynamic responses of the cylinders in the anti-recoil control process considering the second-order wave force are simulated. [ABSTRACT FROM AUTHOR]

The paper presents a hybrid co-simulator comprising EMT and dynamic phasor-based simulators. The EMT simulator models portion(s) of the network wherein fast transients are prevalent and detailed modeling is necessary. The dynamic phasor solver models the rest of the network using extended-frequency Fourier components. Specialized algorithms are developed and presented to accurately map instantaneous EMT and counterpart dynamic phasor samples. Interfacing requirements for co-simulation using different time-steps in the two solvers are also discussed along with implications on accuracy and numerical stability. The paper demonstrates the developed co-simulation algorithm using an example of the IEEE three-phase 118-bus network in which a wind farm is included. The wind farm and the network in its vicinity are modeled in the PSCAD/EMTDC electromagnetic transient simulator, and are interfaced to the rest of the system modeled in a dynamic phasor-based solver. The paper demonstrates the accuracy of the proposed co-simulation for a range of time-step ratios of the two solvers, and also reports the substantial computational time savings obtained using the hybrid simulator. [ABSTRACT FROM AUTHOR]

Pumped storage hydro (PSH) based generation of electricity is a proven grid level storage technique. A new configuration i.e., adjustable speed PSH (AS-PSH) power plant is modeled and discussed in this paper. Hydrodynamic models are created using partial differential equations and the governor topology adopted from an existing, operational AS-PSH unit. Physics-based simulation of both hydrodynamics and power system dynamics has been studied individually in the past. This paper demonstrates a co-simulation of an AS-PSH unit between penstock hydrodynamics and power system events in a real-time environment. Co-simulation provides an insight into the dynamic and transient operation of AS-PSH connected to a bulk power system network. The two modes of AS-PSH operation presented in this paper are turbine and pump modes. A general philosophy of operating in turbine mode is prevalent in the field when the prices of electricity are high and in the pumping mode when prices are low. However, recently there is renewed interest in operating PSH to also provide ancillary services. A real-time co-simulation at sub-second regime of AS-PSH connected to the IEEE 14 bus test system is performed using digital real-time simulator and the results are discussed. [ABSTRACT FROM AUTHOR]

The maritime industry is constantly facing new challenges and technological advancements, making the adaptation of innovative solutions like digital twins a bridge enhancing safety and efficiency between theoretical models and real-world maritime applications. Digital twin simulators for complex dynamic operation systems such as shipboard cranes, allow the operators to practice demanding operations in a risk-free immersive environment with various scenarios. This paper presents the process of developing a digital twin-based simulation tool designed for shipboard crane operations. It is based on co-simulation using the Functional Mock-up Interface (FMI) standard. This allows for the integration of the operation scenarios with different physical domain models, including such as the ship, environmental forces, hydraulic power systems, and controllers. In addition, the digital twin has opened up new opportunities for the optimization of maritime systems. It can be used to identify the optimal operating conditions, predict potential risks, and provide onboard support to the operator. A demo crane digital twin is implemented for the Palfinger crane on the Gunnerus research vessel with system validation via a series of marine operations being real-time monitored by the Remote Control Center (RCC). • Co-simulation technology based on the FMI standard integrating the operation scenarios with different physical domain models. • Real-time ship-crane operations monitored by Remote Control Center lying in the collection, transmission, and storage of sensor data for IoT solutions. • System validation using sensor data and offshore pre-operation varying the environmental parameters in demanding operations. [ABSTRACT FROM AUTHOR]

• Introduces an innovative framework integrating deterministic and probabilistic simulation techniques to address the critical research gap concerning variability in minimal power loss and voltage profile alterations in DGS placement. • Quantifies uncertainty levels in power loss and voltage profiles through Monte Carlo simulations and probability density functions, offering valuable insights for decision-makers to optimize DGS placement and ensure consistent voltage profiles, enhancing grid resilience. • Demonstrates substantial reductions in power loss and consistent adherence to desired voltage limits in the case study feeder, highlighting the significance of considering uncertainties in DGS placement strategies for achieving optimal outcomes. • Contributes to establishing a more resilient and sustainable power distribution network by addressing the critical aspect of uncertainty in DGS placement, paving the way for informed decision-making and a cleaner, more reliable energy future. The surge in renewable energy sources (RESs) and decentralized generation has reshaped power distribution, with distributed generation systems (DGS) like solar photovoltaic (PV) and wind turbines offering advantages including reduced losses and improved grid resilience. However, optimal placement of DGSs within radial distribution feeders faces challenges due to uncertainties in minimal power loss and voltage profile improvements tied to load variations, RES generation, and system parameters. Despite previous investigations, a research gap stays concerning variability in minimal power loss and voltage profile alterations beyond specified limits, hampering well-informed decision-making and potentially leading to sub-optimal solutions and reduced grid reliability. This research paper introduces an uncertainty analysis framework to address this gap, integrating deterministic and probabilistic simulation techniques. Validated initially in the IEEE 33 bus system, the framework is then applied to the Katunje Distribution Feeder in Bhaktapur, Nepal. Utilizing Monte Carlo simulations and probability density functions, the framework quantifies uncertainty levels in power loss and voltage profiles, offering valuable insights for decision-makers. The study underscores the importance of incorporating uncertainty into DGS placement strategies to enhance grid resilience and ensure consistent voltage profiles, even under fluctuating conditions. [ABSTRACT FROM AUTHOR]

Maximizing energy conservation, improving energy efficiency and integration and control of renewable energy sources are critical in order to achieve a low carbon future. An integrated modelling system is needed to evaluate and improve energy performance of urban energy systems’ design and operation, from both financial and environmental perspectives. To this end, this paper presents an urban energy co-simulation framework. It is based on co-simulation standard Functional Mock-up Interface (FMI) and CityGML-based semantic 3D city model and utilized programing packages, like PyFMI, FMILibrary, and mosaik, which is capable of orchestrating the execution of dynamic simulation models supporting the for co-simulation. To demonstrate the proof of concept, two simulation tools are coupled in the first instance: EnergyPlus and No-MASS. Based on the two use cases, the principles and workflow of the framework and results from its application are described. Results from use cases show that synchronization and interaction between our urban energy co-simulation framework and coupled co-simulation components works as intended. The paper concludes by discussing strategies to tackle more complex and multiscale energy systems. [ABSTRACT FROM AUTHOR]

Microscopic traffic simulation is often used in conjunction with vehicle dynamics simulation to test cooperative or perception-based driver assistance functions. On the other hand, visualization and the interaction of a large number of swarm vehicles is computationally burdensome, limiting the size of scenarios. To remedy this problem, this paper introduces a mesoscopic traffic model, namely the extension of the shockwave profile model to road networks, that handles traffic as continuous flows of vehicles. Adopting the idea of level of detail from computer graphics, the modeling of swarm vehicles is carried out in less detail farther away from the EGO vehicle. These levels are defined using the classical (macroscopic, mesoscopic, and microscopic) categorization of traffic modeling. The macroscopic traffic model is responsible for the traffic demand and traffic assignment. The proposed mesoscopic model is capable of capturing the fluctuating nature of traffic on lane level. Closer to the EGO vehicle microscopic traffic simulation is employed while the EGO vehicle is modeled in full-detail including vehicle dynamics too. The 3D rendering of the simulation is performed by the vehicle dynamics simulator. The challenge in the proposed methodology is transitioning between the mesoscopic and the microscopic models, i.e., selecting the boundary and spawning/destroying vehicle agents. The paper addresses this challenge with a linear (w.r.t. the vehicle number) time complexity algorithm. Practically, a dynamic downscaling of the microscopic simulation to mesoscopic level is realized outside the vicinity of the EGO vehicle. The proposed methodology is generic, and can be adapted to most existing vehicle dynamics and microscopic traffic simulator software. The solution is tested with SUMO as microsimulation and Carla as vehicle dynamics simulation through a simple path following test case in two scenarios: a congested residential area and a complex scenario with both a highway section and an urban area. Simulation results suggest that the simulation performance could be improved by 200–500% while retaining modeling accuracy, compared to the case when only microscopic simulation is used. [ABSTRACT FROM AUTHOR]

This paper presents a SOC estimation model in real-time applications such as smart grid. Authors list the existing SOC estimation methods and propose a SOC model to overcome the limitations of the precedent methods presented in the literature. Furthermore, this paper proposes a scalable, self-adaptive, and generic SOC model to meet the smart grid requirement. Multi-agent system approach is proposed to manage the smart grid and a co-simulation is proposed enabling the physical variables modeling while the discrete decision-making is given by developing agents under Jade framework. The results analyses have shown a SOC model which depends on the battery use conditions that can match with all batteries technologies and therefore can be suitable for smart grid applications. [ABSTRACT FROM AUTHOR]

In large and complex processes use of simulators will take place more and more in the future to avoid and learn about transients and unexpected situations. There are plenty of dynamic simulation tools in the markets but most of them have been developed and used for quite specific and limited application areas. At the moment there are just few simulation tools which are capable to handle dynamically in the same simulation case challenging process areas like combustion, distillation, chemistry and control of very large process areas. For this reason, in this study, there was a need to carry out co–simulation where two dynamic simulation tools Apros and Aspen Plus Dynamics were combined together by using Matlab Simulink as an interface. The co–simulation approach was a way to construct large dynamic process simulation environment, where typical operational transients and failure situations of an oxy fired power plant were possible to test and analyze. Under EU 7th Framework Programme (FP7) the FLEXI BURN CFB project an oxy firing concept based on circulated fluidized bed (CFB) combustion and supercritical once-through (OTU) water steam cycle was developed and successfully demonstrated [1] . This project also generated a dynamic simulation model of the 1st generation oxy firing concept, as we call it. In the EU 7th Framework Program's project O2GEN (Optimization of Oxygen-based CFBC Technology with CO 2 capture), the 2 nd generation concept of CFB based oxy firing was developed. The target of the project was, at first, to increase O 2 content in recirculated flue gas to see what kind of effect it has to the heat exchange and corrosion in the boiler. Secondly, the target was to carry out exergy analysis to increase the whole concept efficiency by decreasing energy consumption in the boiler, Air Separation Unit (ASU) and CO 2 -purification unit (CPU). Based on these steady state analysis means the refined concept was then modelled for dynamic simulations which were carried out by using Apros and Aspen Plus Dynamics dynamic modelling tools in a co–simulation mode. This paper deals with dynamic simulation of the 2 nd generation 600 MW oxy fired CFB once trough boiler. In this paper we will present the dynamic model which includes oxy fired CFB boiler, turbine island, ASU and CPU with all needed equipment like heat exchangers, pipes, pumps, air and fuel feeding systems, distillation columns and sequestration vessels. Automation like measurements, controllers and actuators are included in the model. The simulation case selected for this paper presents an analysis what happens when one of the oxidant fans trips on boiler full load operation and how to handle this kind of failure by decreasing the boiler load to sufficient level of regarding the available oxidant feeding capacity. There were several items which were taken into account in the boiler, turbine island, ASU and CPU side when this kind of failure takes impact. The main findings in the failure analysis will be presented. Finally, discussion and future aspects of the simulation approach described will be given. [ABSTRACT FROM AUTHOR]

• A novel usage of the translation technique to correct measured I-V curves to STC. • Robust PV modeling based MGWO and translation technique to extract ODM parameters. • RFCs-based fault detection and diagnosis method reached a prominent 99.4% accuracy. • The proposed method outperformed SVM, KNN, MLP Classifier, DT, and SGDC ML models. Accurate and reliable fault detection procedures are crucial for optimizing photovoltaic (PV) system performance. Establishing a trustworthy PV array model is the primary step and a vital tool for monitoring and diagnosing PV systems. This paper outlines a two-step approach for creating a reliable PV array model and implementing a fault detection procedure using Random Forest Classifiers (RFCs). Firstly, we extracted the five unknown parameters of the one-diode model (ODM) by combining the current–voltage translation method to predict the reference curve and employing the modified grey wolf optimization (MGWO) algorithm. In the second step, we simulated the PV array to obtain maximum power point (MPP) coordinates and construct operational databases through co-simulations in PSIM/MATLAB. We developed two RFCs: one for fault detection (a binary classifier) and another for fault diagnosis (a multiclass classifier). Our results confirmed the accuracy of the PV array modeling approach. We achieved a root mean square error (RMSE) value of 0.0122 for the ODM parameter extraction and RMSEs lower than 0.3 in dynamic PV array output current simulations under cloudy conditions. Regarding the fault detection procedure, our results demonstrate exceptional classification accuracy rates of 99.4% for both fault detection and diagnosis, surpassing other tested models like Support Vector Machines (SVM), K-Nearest Neighbors (KNN), Neural Networks (MLP Classifier), Decision Trees (DT), and Stochastic Gradient Descent (SGDC). [ABSTRACT FROM AUTHOR]

Deep decarbonization of the energy sector, which is now a worldwide priority, will result in a sharp increase of the reserves needed for coping with the variability introduced by a steady increase of the share of renewable energy resources (RES), such as rooftop solar panels, in the generation mix. In this context, a big challenge is to obtain the optimal import/export potential of a network with high penetration of RES in the distribution side. Hence, this paper proposes a market based transmission and distribution co-simulation under bidirectional power flow to address this challenge. To this end, a Jacobian-based interface (JBI) for co-simulation which is more efficient and stable than the traditional fixed-point iteration (FPI) method is applied in this study. Moreover, a comparative assessment of JBI and FPI accuracy and stability are also performed on actual Hydro-Quebec power grid (consisting of a 3000-bus transmission model in PSS/E, interacting with a 6100-bus distribution model in CYMdist) and a T&D 68K-bus test system. Simulation results demonstrate the importance of considering co-simulation approach for this type of study and also demonstrate the stability of JBI in comparison with the FPI methods. Furthermore, the expected value of import/export and the participation of RESs are compared for different level of decarbonization and co-simulation approach. • Two co-simulation approaches called fixed point iteration and Jacobian-based interface are implemented and compared in the terms of convergence capability under T&D networks with +68K buses. • In a technology penetration study in a T&D network, the JBI method has better convergent in all scenarios comparing to FPI method. • The JBI method is employed to integrate the active distribution networks in the wholesale electricity market through co-simulation approach for the first time. • The optimal import/export of a T&D network, DER participation in the wholesale electricity market with different level of decarbonization are determined. [ABSTRACT FROM AUTHOR]

The simulation of the control rod drive mechanism is a co-simulation process of multi-physics coupling. It has the problem of conflict between simulation accuracy and efficiency in the simulation process based on the centralized simulation idea. Therefore, a multidisciplinary co-simulation method and simulation platform with adaptive step size are proposed in this paper. According to the characteristics of the simulation nodes, the fruit fly optimization method is used to determine the adaptive step size of different simulation stages. A multi-disciplinary co-simulation platform is constructed based on the Isight which can integrate co-simulation tool. The co-simulation process of the control rod drive mechanism is completed with the method and platform. The results show that the simulation accuracy of the platform built in this paper is increased by 23%, and the simulation efficiency is increased by 64%, which verifies that the proposed method has good compatibility in terms of simulation accuracy and efficiency. • a multidisciplinary co-simulation method with an adaptive step size mechanism is proposed. • A multidisciplinary co-simulation platform system is constructed based on Isight. • The application in the multidisciplinary simulation process of the control rod drive mechanism. [ABSTRACT FROM AUTHOR]

Co-simulation is an effective and versatile way to determine the forward-dynamics behaviour of complex engineering applications. In co-simulation setups, the overall system dynamics is split into several subsystems that evolve in time separately. This makes it possible to use modelling and integration methods that can be tailored to the specific nature and behaviour of each of them. Co-simulation subsystems coordinate their execution by means of information exchanges through a discrete-time interface. In some cases, this limited exchange of data can cause accuracy and stability issues in the simulation process, especially when explicit coupling schemes are employed. Correction algorithms are then required to ensure the accuracy of the obtained results. This paper provides insight into the structure of explicit co-simulation problems, revealing the effect of input extrapolation at the discrete-time interface between subsystems. The resulting system equations are formulated in terms of control theory expressions, which can be then used to develop compensation solutions to correct the perturbations introduced at the co-simulation interface. The compensator architecture is chosen to ensure the eigenstructure assignability condition, which has been ad-hoc developed in this paper. These aspects are illustrated here in the explicit co-simulation of linear mechanical systems. • Instability and inaccuracy of co-simulation due to signal exchange are investigated. • A novel model to analyse the effect of co-simulation perturbation is provided. • A compensation algorithm based on the eigenstructure assignment method is proposed. • The compensator automatically adapts to system and co-simulation settings. • A novel eigenstructure assignability condition to design the compensator is proposed. [ABSTRACT FROM AUTHOR]

Among the various factors that affect building performance, occupant behavior (OB) has received more and more attention and has become a research hotspot in building design and operation in recent years. However, due to the remarkable randomness and diversity of OB in buildings, it is difficult to accurately describe its characteristics using a fixed schedule, which is a normal approach of most energy simulation tools. DeST, a whole building energy simulation tool offers the function of stochastic OB simulation so that the simulation results can be more in line with the actual situation. In the newly released DeST 3.0, the OB modules are developed based on the actual observed OB data and are divided into two parts: occupancy and occupant action modules. The occupancy module is based on the Markov chain, which simulates the occupant movements among the spaces inside and outside the buildings. The occupant action modules are proposed with an environment and event-driven stochastic infrastructure based on a three-parameter Weibull distribution, such as occupant shading, window, and air-conditioning (AC)/heating control behavior modules. This paper presents the OB modules development for coupled simulation in DeST 3.0 and discusses the effects of integrated simulation of occupant behavior on building energy consumption. Firstly, an overview of the current modelling efforts of OB is given, from the trend to the existing foundation. Secondly, the development of OB modules for coupled simulation in DeST 3.0 is introduced in-depth, including co-simulation of AC/heating control behavior, window behavior and shading behavior. Lastly, two case studies that realize coupled simulation using the developed modules are shown, one is the comparison between existing occupancy schedules from GB standards and the developed occupancy simulation, and the other is the comparison between the result of simulating with or without using AC/heating control behavior modules in two bedrooms of the residential building. [ABSTRACT FROM AUTHOR]

• A parallel processing approach for the simulation of power system transients on grids with massive integration of renewable energy sources. • Functional Mockup Interface for establishing a co-simulation environment where several instances of an EMT-type software can be executed in parallel. • a multi-rate approach can be used for solving wind parks with smaller time-steps when required. • it becomes possible to simulate detailed wind parks with computational speeds equivalent to their aggregated equivalents. This paper presents a co-simulation tool to link multiple instances of an electromagnetic transient (EMT) simulation tool for parallel and fast computations. The tool exploits the propagation delays of transmission lines and cables to create network decoupling into several smaller sub-networks. These sub-networks are solved in parallel without approximations. A multi-rate option is also incorporated, in which the sub-networks can use different numerical integration time-steps. The Functional Mock-up Interface (FMI) is used for creating the co-simulation interface between multiple instances according to a master-slave communication scheme and the data sharing method is implemented using low-level synchronization primitives called semaphores. The interfaces between each subnetwork are automatically initialized for time-domain simulations using load-flow results. [ABSTRACT FROM AUTHOR]

This paper presents techniques to interface a Transient Stability Analysis (TSA) based model to an ElectroMagnetic Transient (EMT) based model running on a Real Time Digital Simulator. Practical challenges of implementing such an interface are discussed. The proposed TSA model can be simulated using a substantially larger time-step compared to the EMT model. The interface between the EMT model and the TSA model is implemented using a transmission line modeled using Dynamic Phasors (DP). Time-step delay is the primary cause of numerical instability in co-simulations. In this work, a traveling wave model of a transmission line is used to decouple the EMT and TSA networks. The interface requires that the propagation delay of the interfaced transmission lines be greater than the EMT time-step even though the TSA is simulated using a much larger time-step than the EMT model. The proposed technique is validated using the IEEE 39 bus system and a power system with 500 buses. [ABSTRACT FROM AUTHOR]

[Display omitted] • An architect-friendly rapid evaluation for the adaptive facades (AFs) is presented. • The method eliminates uncertainty in AFs selection during the early design stage. • Optimal hourly values are obtained via co-simulation with EnergyPlus and Python. • AFs strategy is characterized by climate and optimal values using a white-box model. • U-value strategy reduces consumption by up to 6.6%, SHGC&τ v strategy by 17.0%. Adaptive façades (AFs) are technologies with great potential to reduce energy consumption by changing their properties to adapt to variable climatic conditions. This paper proposes an architect-friendly computational approach for the exploration of strategies for the selection of the thermal parameters of AFs based on co-simulation and white-box models in the early design stage. In the case study, the proposed approach is applied to obtain strategies with variable U -values and variable SHGC& τ v values for high-rise office buildings in seven cities. The energy consumption analysis of five scenarios is carried out to investigate the energy-saving potential of the AFs and to propose design strategies for transparent façades, and the accuracy of the approach is verified. It is concluded that the highest match of the variable U- value strategy with the optimal hourly U- values is 85.3%, while that between the variable SHGC& τ v strategy and the optimal hourly SHGC& τ v values is only 71.0%. Regarding the energy-saving potential, the highest energy-saving rate is 6.6% for the variable U- value strategy. However, for the variable SHGC& τ v strategy, the highest energy-saving rate is greater than 10.8% in seven cities. The difference between the energy-saving rates of the proposed strategy and the optimal hourly strategy is less than 0.4%, and it is 0.8% for the AFs with variable U- values and variable SHGC& τ v values, respectively. This architect-friendly approach represents a widely used design strategy for AFs that can directly provide recommended thermal parameters based on climatic conditions, and is an effective way to demonstrate the potential application of AFs in the early design stage. [ABSTRACT FROM AUTHOR]

For residential buildings with radiator heating system, the supply temperature is conventionally adjusted by weather compensator, which results in large fluctuations in the indoor air temperature and high energy consumption of heating. The solutions on current researches mainly focus on heat prediction of demand side, so that the supply temperature can be adjusted according to the predicted heat demand and achieve a heat balance. However, this requires a significant amount of historical data, which limits their applicability. And the lack of pre-simulation platform of the new strategies makes their practical application more difficult. In this paper, a digital twinning of secondary district heating system (DHS) is created, which considers both human behavior and radiator heat dissipation characteristics. A new supply temperature regulate strategy based on indoor temperature feedback is proposed. It contains an indoor temperature prediction model, which require a small amount of measured data and can keep the prediction error within ± 0.6 °C. The control effects are analyzed by comparing the proposed regulation strategy with the weather compensator. The result shows that the new temperature regulate strategy is superior to the weather compensator in maintaining indoor temperature and can save energy by 5.4%. • The simulation test bed of radiator heating system for multi-family buildings. • The accurate indoor temperature predictive model. • Energy saving rate is 5.4% compared with weather compensator. [ABSTRACT FROM AUTHOR]

Abstract: This paper gives an overview of the existing co-simulation platforms for co-design of networked control systems (NCSs). NCSs contain coupled control and communication perspectives. However, the existing simulators focus either on control systems or communication networks. In order to analyse the coupling effect from both sides, co-simulation method is under consideration as one of the most promising solutions. This paper briefly introduces the commonly used individual control and communication simulators. Then the existing co-simulation platforms have been reviewed and discussed. Synchronization technique is the key point toward co-simulation, thus different synchronization methods have also been summarized. Two sample case studies with results are provided to show the beneficial of co-simulations. [Copyright &y& Elsevier]

Abstract: Recent results show that a predictive building automation can be used to operate buildings in an energy and cost effective manner with only a small retrofitting requirements. In this approach, the dynamic models are of crucial importance. As industrial experience has shown, modeling is the most time-demanding and costly part of the automation process. Many papers devoted to this topic actually deal with modeling of building subsystems. Although some papers identify a building as a complex system, the provided models are usually simple two-zones models, or extremely detailed models resulting from the use of building simulation software packages. These are, however, not suitable for predictive control. The objective of this paper is to share the years-long experience of the authors in building modeling intended for predictive control of the building''s climate. We provide an overview of identification methods for buildings and analyze their applicability for subsequent predictive control. Moreover, we propose a new methodology to obtain a model suitable for the use in a predictive control framework combining the building energy performance simulation tools and statistical identification. The procedure is based on the so-called co-simulation that has appeared recently as a feature of various building simulation software packages. [Copyright &y& Elsevier]

Co-simulation is a promising approach for the modelling and simulation of complex systems, that makes use of mature simulation tools in the respective domains. It has been applied in various different domains, oftentimes without a comprehensive study of the impact to the simulation results. As a consequence, over the recent years, researchers have set out to understand the essential challenges arising from the application of this technique. This paper complements the existing surveys in that the social and empirical aspects were addressed. More than 50 experts participated in a two-stage Delphi study to determine current challenges, research needs and promising standards and tools. Furthermore, an analysis of the strengths, weakness, opportunities and threats of co-simulation utilizing the analytic hierarchy process resulting in a SWOT-AHP analysis is presented. The empirical results of this study show that experts consider the FMI standard to be the most promising standard for continuous time, discrete event and hybrid co-simulation. The results of the SWOT-AHP analysis indicate that factors related to strengths and opportunities predominate. [ABSTRACT FROM AUTHOR]

Engineering efforts to handle contemporary energy supply challenges and mitigate pollutant emission lead towards more complicated systems. Power plants are supplementing with additional processing units, alternative production modes and higher level of automation. Wind and solar sources, biomass combustion, gasification, carbon capture and storage (CCS), and cogeneration have appeared as important players in the energy systems. The increasing complexity comprises a risk that the systems become less manageable and less stable than currently. Traditional steady-state engineering methods cannot fully address these challenges that are inherently dynamic in their nature. Dynamic process simulation appears as important tool to the systems design and optimisation tasks. A large variety of dynamic process modelling and simulation approaches has been presented recent years. This paper presents a brief review of methods and simulation packages that are generally applied for studying energy systems' transient behaviour. A CCS capable power plant is presented as an example of utilizing dynamic process simulation for virtual evaluation of a novel electricity production concept. The modelling was performed using two simulators Apros and Aspen Plus Dynamics, which were linked together for dynamic simulating the full chain of cryogenic oxygen distillation, oxy combustion, turbine islands and carbon dioxide purification and liquefaction operations. • Dynamic simulations for design and optimisation of contemporary energy systems have been reviewed. • A case study for evaluating oxy combustion CFB boiler cycle with carbon capturing is presented. • Co-simulation with two dynamic process simulation software: Apros and Aspen Plus Dynamics were shown. • Flexibility aspects of oxy combustion power plant are discussed. [ABSTRACT FROM AUTHOR]

The paper describes the collaborative processes and technologies used to develop a prototype for a Cyber-Physical Production System of USB sticks. The development of this system follows the model-based approach where co-simulations of different components, detailed at different level of abstractions, serve as a basis for structured dialogue between specialised teams and agreement on shared interactions. The focus is primarily on the co-simulation technology, allowing a gradual increase of fidelity and independent testing and validation of the composing subsystems. This technology may be equally complemented with group decision-making tools to better support the collaboration during the design of model interactions. [ABSTRACT FROM AUTHOR]

• Study interdependencies of energy demand and supply side in coupled optimization. • Development of co-simulation and optimization framework, combining simulators. • New bi-objective formulation for simultaneous building and energy hub optimization. • Comparison of coupled optimization to regular, consecutive approach. • Showing importance of simultaneous design of buildings and multi-energy systems. This paper presents a co-simulation framework for the simultaneous optimization of building geometries and multi-energy systems using the energy hub approach. The rationale for such coupling is that building geometry has an impact on energy demands and solar potentials on roofs and façades, thus also altering the corresponding optimal energy system. As a demonstration of this approach, we formulate bi-objective optimization problems for minimizing operational cost and carbon emissions, with decision variables for building geometry and for selection and sizing of energy system technologies. The methodology is applied to a case study in the city of Zurich, Switzerland, involving four office buildings. Different carbon emissions targets are studied to show the impact on cost, densities, sizing of the multi-energy system, and architectural design implications. Results for this case study show a clear relation between emissions targets and densities due to available solar potentials for renewable energy generation, with an optimal density in the strictest emissions target reaching only 10% of the optimal density without emissions target. This indicates that differentiated environmental targets should be defined depending on the location of a building, where rural sites could have stricter targets than dense urban sites to reflect the respective marginal costs for achieving the targets. Our study shows that coupling multiple simulators into a common optimization and design workflow brings together architectural aspects, such as geometry, with engineering aspects, such as the energy system design, and microclimate conditions, such as local solar potentials. Thus, essential interdependencies between the energy supply and demand side can be captured in the design of energy efficient cities. [ABSTRACT FROM AUTHOR]

Highlights • A market model for energy trading and energy management of Microgrids is described. • Device-oriented bidding strategies are presented for each device type in buildings. • PV probabilistic forecast is integrated to demonstrate market dynamics on different type days. • The utility and prosumers benefit, in addition to the added value of the ICT infrastructure are quantified. Abstract Energy trading markets are one of the most viable solutions to incentivize prosumers in Microgrids. They offer the utility a versatile access for flexible loads coordination without violating the consumer privacy. In the literature, several models and designs were presented to address different aspects of energy trading markets, yet there is a gap between these models and their application in real-life. This paper describes a novel discrete-timely double-sided auction model that facilitates energy trading between prosumers in near real-time and forward markets. Since the practical realization of the model represents a crucial criterion for this model, the market is designed with fast clearing mechanism and simple bidding rules that guarantee the benefits of the prosumers, their privacy, and consider their personal preferences. Additionally, a decentralized home energy management approach is followed at the prosumer level to maximize the system reliability and enable an easy integration of multiple devices from different manufacturers. Hence, a device-oriented bidding strategy is demonstrated that considers the physical characteristics and technical limitations of each device type such as electric vehicles (EV), micro-combined heat and power systems (micro-CHP) or heat pumps. Furthermore, an open-source day-ahead probabilistic forecast for the photovoltaic systems (PV) is integrated with a bidding scheme that maximizes the prosumers commitment in the forward market. In the results, field measurements and testbeds data are used to quantify the benefits of the market model to the utility and the prosumers based on different metrics such as self-sufficiency, self-consumption, peak load and CO 2 emission reduction, and total costs. The results indicate that the market model can increase self-sufficiency and self-consumption of a microgrid while reducing the prosumer costs on average by 23%. [ABSTRACT FROM AUTHOR]

Abstract This paper compares Active Disturbance Rejection Control (ADRC), Proportional–Integral (PI) and ultra-local adaptive controller (also labeled intelligent-PID) when applied to Automatic Generation Control (AGC) for a multi-area power system with co-simulation of the communication system. The co-simulation platform PiccSIM integrates Simulink/Matlab and Network Simulator Ver. 2 (NS2) with real-time simulation data exchanged through Local Area Network (LAN). Instead of the traditional control center, automatic generation controller is embedded in each participating generation unit locally to avoid communication delay for the control signals. This new control scheme is referred to as fully distributed AGC. The performance of the proposed scheme is tested on a nonlinear model of New England (NE) 39-bus system with the co-simulated tie-line power flow communication delays. The simulation results present very promising performance and good robustness of ADRC in the presence of communication delays, suggesting that the stability of the overall cyber–physical system is enhanced significantly. [ABSTRACT FROM AUTHOR]

Highlights • Time-discretization at co-simulation interfaces introduces energy errors in integration. • Energy errors can be monitored and corrected acting on the coupling variables. • Energy correction can improve the stability and quality of the co-simulation process. Graphical abstract Abstract Non-iterative co-simulation is an increasingly important technique for the simulation of complex mechanical systems. Adopting co-simulation schemes enables the simultaneous use of computational resources and makes it possible to select the most appropriate modelling techniques and algorithms to describe and solve the dynamics of each system component. However, it inherently requires the coupling of different subsystems at discrete communication times, which may compromise the stability of the overall integration process. One of the negative effects of discrete-time communication is the introduction of artificial energy in the system dynamics, which can render the simulation unstable if it accumulates over time. Excess energy can be dissipated introducing virtual damping elements in the subsystem models. The actual amount of damping must be adjusted as the simulation progresses to ensure that all the artificially generated energy is removed from the system while keeping the dynamics realistic. In this paper, we introduce a monitoring framework to keep track of this excess energy, and put forward a dissipation methodology to eliminate it. The ability of this framework to achieve stable non-iterative co-simulation was tested with several mechanical system examples. [ABSTRACT FROM AUTHOR]

Abstract District energy systems are a central element in transforming the energy system towards a low-carbon system. Simulation is regarded as key method for concept development and assessment as well as for operational optimization to address the growing complexity of these systems and to derive quantitative feedback e.g., as input for decision-support or operational processes. In this paper we present a comprehensive comparison of four widely used general-purpose modelling tools for district-scale energy systems, including a detailed discussion of modelling paradigms and co-simulation capabilities. This comparison is based on an extensive literature review, a comprehensive questionnaire that was conducted by tool and library developers, as well as a comparison of pipe model behavior of various libraries against measured data. The results including the experimental data are openly available and can support users in academia and industry with the selection of suitable modelling paradigms and associated tools and libraries. [ABSTRACT FROM AUTHOR]

Abstract: The grand challenge facing the power and energy industries is the development of efficient, environmentally friendly, and affordable technologies for next-generation energy systems. To provide solutions for energy and the environment, the U.S. Department of Energy''s (DOE) National Energy Technology Laboratory (NETL) and its research partners in industry and academia are relying increasingly on the use of sophisticated computer-aided process design and optimization tools. In this paper, we describe recent progress toward developing an Advanced Process Engineering Co-Simulator (APECS) for the high-fidelity design, analysis, and optimization of energy plants. The APECS software system combines steady-state process simulation with multiphysics-based equipment simulations, such as those based on computational fluid dynamics (CFD). These co-simulation capabilities enable design engineers to optimize overall process performance with respect to complex thermal and fluid flow phenomena arising in key plant equipment items, such as combustors, gasifiers, turbines, and carbon capture devices. In this paper we review several applications of the APECS co-simulation technology to advanced energy systems, including coal-fired energy plants with carbon capture. This paper also discusses ongoing co-simulation R&D activities and challenges in areas such as CFD-based reduced-order modeling, knowledge management, advanced analysis and optimization, and virtual plant co-simulation. Continued progress in co-simulation technology – through improved integration, solution, and deployment – will have profound positive impacts on the design and optimization of high-efficiency, near-zero emission fossil energy systems. [Copyright &y& Elsevier]

To reduce large peak torque and improve the vehicle's dynamic performance during frequent stops and starts, a novel mechatronics-electro-hydraulic power coupling system (MEH-PCS) is proposed. It combines a conventional electric motor and a piston pump/motor into a single unit that converts electrical, mechanical, and hydraulic energy. After a theoretical analysis of the system power flow, the paper establishes a rule-based dynamic optimal energy management strategy to control energy distribution and the dynamic switching of working modes in real-time. Moreover, a prototype vehicle model (MEH-PCEV) based on the MEH-PCS is developed by analyzing the working modes of the system. Thereafter, the feasibility and superiority of MEH-PCEV are verified by comparing it with AMESim certified pure electric vehicles. The verification results indicate that the MEH-PCEV's battery consumption rate is reduced by 14.418% and 21.174%, respectively, in the new European driving cycle and the American city cycle. Furthermore, the time for the vehicle to reach the start-up speed threshold is enhanced, and the electric peak torque is substantially reduced. Ultimately, the paper proposes a fuzzy controller with vehicle speed and pressure of the accumulator as variables to optimize the logic threshold control strategy. The electric torque is substantially reduced while the overall efficiency of the motor operating point is enhanced. The consumption rate of electric energy has been improved somewhat. Under the drive strategy's control, the MEH-PCS is well suited for frequent stops and starts conditions. As a development, this research is expected to provide a reference for improving electric torque. • A novel mechatronics-electro-hydraulic power coupling system is proposed. • The power flow is analyzed to get the factors that affect the electrical power. • A method for switching operating modes to reduce the electric peak torque is proposed. • A regular and dynamically optimal energy management strategy is designed. • A fuzzy logic optimization method is designed to reduce the electric peak torque. [ABSTRACT FROM AUTHOR]

Abstract: One of the most flexible and modular approaches to reconfigurable systems is a bus-based approach. In order to get realistic performance estimates of these systems, detailed modeling of the processor as well as the bus and memory hierarchy is required. In addition, when coupling one or more reconfigurable units with a superscalar, out-of-order issue, load/store RISC CPU using the on-chip system bus, there are issues relating to cache coherency that need to be addressed. We have developed a cycle accurate co-simulator that uses a ‘C’ model of the processor and HDL models of the bus and reconfigurable units. We have also made modifications to the CPU pipeline to allow for non-cacheable accesses to the reconfigurable unit. This is reported in the paper. We have used this simulator to look at (a) The speedup obtained for two examples, namely, matrix multiplication and Lempel–Ziv compression, (b) the speedup obtained when there is a context switch from one application to the other and full reconfiguration is employed and (c) speedup obtained with partial reconfiguration. These results are reported in the paper. [Copyright &y& Elsevier]

Given the complexity and interconnection of different aspects involved in building evaluation, one of the most relevant, and challenging, research topics is the integration of different domain models (such as thermal comfort, indoor environmental quality and occupant comfort) to effectively describe and inform improvement strategies for the behaviour and performance of a building and building stock. Currently, this problem is unsolved with only one study attempting to integrate building energy simulation and life cycle assessments (separately, both practices are utilised to facilitate the design and management of buildings, traditionally consultancies offer building energy simulation services – most commonly for regulatory purposes – and more recently life cycle impact assessments), whilst no work has attempted this integration in a dynamic manner. This study addresses this gap by developing a dynamic, open building information modelling based co-simulation architecture. This architecture is the first to tightly couple and integrate EnergyPlus and Brightway2, in a way that does not rely upon heuristics or simplified tools. Furthermore, it is the first building energy simulation and life cycle assessment co-simulation to enable time-differentiated (dynamic) results and the first to be enabled only by open technologies. The architecture has been validated against two case-study non-domestic buildings located in the United Kingdom and Luxembourg, demonstrating its applicability to the construction and operational life cycle phases of buildings. The work presented in this paper has shown how a time-differentiated co-simulation approach across energy and lifecycle domains enables a more holistic analysis of whole buildings with greater accuracy and granularity. • There is a lack of studies co-simulating building energy simulation and life cycle assessment. • This study develops an open, building information modelling based co-simulation architecture. • The developed co-simulation architecture tightly couples whole building energy simulation and life cycle assessment models. • Co-simulation architecture has been validated against two non-domestic buildings, in the United Kingdom and Luxembourg. • The developed architecture enables time-differentiated (dynamic) life cycle assessment results. • Time-differentiated life cycle assessment results provide results at a finer level of granularity and accuracy. [ABSTRACT FROM AUTHOR]

Modeling buildings and smart energy systems requires coupling a wide range of components into one unified simulation process, which can be difficult given the complexity of these systems. Hence, a large number of researchers integrate separate simulations for each of the individual components in a co-simulation instead. To systematically analyze techniques, standards, tools and applications of co-simulation in the field of buildings and smart energy systems, the publications on co-simulations in this field are reviewed by means of taxonomic analysis. Furthermore, the reproducibility as well as the validation approach of the respective papers are evaluated. Results show that Functional Mock-up Interface (FMI) is the most prominent standard for co-simulation in modeling buildings and smart energy systems. Co-simulation is mostly used in Heating, Ventilation, and Air Conditioning (HVAC) and occupancy analysis applications. Since nearly 70% of publications are not reproducible, we advocate that journals and funding agencies adopt stricter data and code-sharing policies. [ABSTRACT FROM AUTHOR]

This paper introduces a novel co-simulation framework running on the Java Virtual Machine built on a software architecture known as the Entity-Component-System. Popularised by games, this architecture favours composition over inheritance, allowing for greater flexibility. Rather than using a fixed inheritance tree, an entity is defined by its traits, which can be seamlessly changed during simulation. The framework supports the Functional Mock-up Interface standard for co-simulation, as well as the System Structure and Parameterisation standard for defining the system structure. Furthermore, the employed architecture allows users to seamlessly integrate physics engines, plotting, 3D visualisation, co-simulation masters and other types of systems into the framework in a modular way. To show its effectiveness, this paper compares the framework to four similar open-source co-simulation frameworks by simulating a quarter-truck system defined using the System Structure and Parameterisation standard. • Presentation of Vico, a novel co-simulation framework based on the ECS software architecture. • Accuracy and performance comparison of Vico against other frameworks supporting both the FMI and SSP standards. • Case-studies utilising co-simulation models of both a generic quarter-truck system and the R/V Gunnerus. [ABSTRACT FROM AUTHOR]

In electric power system, disturbance detection has become an important part of grid operation and refers to the detection of a voltage and current excursion caused by the wide variety of electromagnetic phenomena. This paper proposes a computationally efficient and robust algorithm for synchronized measurement technology (SMT) supported online disturbance detection, suitable for AC and HVDC grids. The proposed algorithm is based on the robust median absolute deviation sample dispersion measure to locate dataset outliers. The algorithm is capable of identifying the disturbance occurrence and clearance measurement sample based on the dynamic criteria, driven by present power system conditions. The effectiveness of the proposed algorithm is verified by real-time simulations using a cyber-physical simulation platform, as a co-simulation between the SMT supported electric power system model and underlying ICT infrastructure. The presented results demonstrate effectiveness of the proposed algorithm, making it suitable for an AC and HVDC online disturbance detection application or as a pre-step of backup protection schemes. [ABSTRACT FROM AUTHOR]

PV/T collector turns out to be a promising alternative for the traditional solar thermal collector for domestic hot water (DHW) application. In this paper, four comprehensive thermal and electrical models including unglazed PV/T, glazed PV/T, PV and flat plate thermal collector are established for the purpose of accurate long-term simulation and optimization. The detailed 2-D temperature distributions of the glazed and unglazed PV/T collector are illustrated and compared for the first time. Besides, the dynamic response characteristics of different collectors are discussed and compared. By running the models under a broad combination of the operating conditions, the comprehensive performances are obtained and found to be significantly influenced by flow rate, temperatures, radiation and wind speed. A multi-objective optimization model coupling TRNSYS and NSGA-II tool is established to study and optimize the PV/T DHW system for a complete year. The Pareto frontier of conflicting objectives (life cycle savings and prime energy saving efficiency) is obtained for the optimal system design. The mass flow rate on the Pareto frontier is between 0.0085 kg/s and 0.011 kg/s in this study. The optimal value of tank volume on Pareto frontier shows an equally scattering distribution between 99.5 L and 218.6Lfor a 2 m 2 glazed PV/T collector. [ABSTRACT FROM AUTHOR]

Manufacturing is a competitive global market and efforts to mitigate climate change are at the forefront of public perception. Current trends in manufacturing aim to reduce costs and increase sustainability without negatively affecting the yield of finished products, thus maintaining or improving profits. Effective use of energy within a manufacturing environment can help in this regard by lowering overhead costs. Significant benefit can be gained by utilising simulations in order to predict energy demand allowing companies to make effective retrofit decisions based on energy as well as other metrics such as resource use, throughput and overhead costs. Traditionally, Building Energy Modelling (BEM) and Manufacturing Process Simulation (MPS) have been used extensively in their respective fields but they remain separate and segregated which limits the simulation window used to identify energy improvements. This review details modelling approaches and the simulation tools that have been used, or are available, in an attempt to combine BEM and MPS, or elements from each, into a holistic approach. Such an approach would be able to simulate the interdependencies of multiple layers contained within a factory from production machines, process lines and Technical Building Services (TBS) to the building shell. Thus achieving a greater perspective for identifying energy improvement measures across the entire operating spectrum and multiple, if not all, manufacturing industries. In doing so the challenges associated with incorporating BEM in manufacturing simulation are highlighted as well as gaps within the research for exploitation through future research. This paper identified requirements for the development of a holistic energy simulation tool for use in a manufacturing facility, that is capable of simulating interdependencies between different building layers and systems, and a rapid method of 3D building geometry generation from site data or existing BIM in an appropriate format for energy simulations of existing factory buildings. [ABSTRACT FROM AUTHOR]

Since infrastructure systems are threatened by natural or man-made hazards with unprecedented frequency and intensity, decision-makers spare no efforts in proposing methods and tools to improve the resilience of interdependent infrastructures. However, these approaches and toolkits are flawed in characterizing the heterogeneous operating regimes of different infrastructure systems. Moreover, worst-case scenario is commonly harnessed when generating the hazard information maps and assessing the induced adverse consequences on infrastructures, which is exaggerated as all the identified vulnerable spots in infrastructures rarely suffer from the worst situation simultaneously. Besides, resilience assessment methods are mostly static and not competent in capturing the emergence and development of specified hazard event and revealing the dynamic resilience behavior of interdependent infrastructure systems. To address these gaps, this paper proposes an overarching High Level Architecture (HLA)-based co-simulation framework which is composed of the HLA-based service adaptation supported by the Run Time Infrastructure (RTI) libraries, simulators and interface design between the federates, and typical scenarios to facilitate interdependent infrastructure resilience management. It further adapts and orchestrates the generic HLA-based co-simulation framework to suit the interdependent infrastructure resilience management scenarios, while accommodating the physics-based domain-specific simulators; supports seamless and interoperable message exchange between interdependent infrastructures along with the development of specific hazards; and provides interface design between the infrastructure-specific simulators and the RTI. A typical flooding case is adopted to demonstrate the validity and transferability of our proposed framework. The overarching HLA-based co-simulation framework aims to formalize a modeling paradigm to investigate the time-varying resilience behavior of interdependent infrastructure systems, in order to contribute to the collaborative and joint decision making efforts between stakeholders of infrastructure regulatory agencies. • An overarching HLA-based co-simulation framework was proposed for interdependent infrastructure resilience management. • Adapted and orchestrated the generic HLA-based simulation method to suit infrastructure resilience scenarios. • Accommodated the physics-based simulators to capture infrastructure heterogeneities and the dynamic resilience behavior. • An urban flooding case was adopted to demonstrate the efficacy of the proposed framework. [ABSTRACT FROM AUTHOR]

• Provided a platform to test various residential building control systems. • Used probability of occupancy to determine setback temperature when unoccupied. • Integrated optimizer with adaptive and occupancy control. • Generated dynamic electricity tariff based on wholesale electricity pricing. • Evaluated the peak load shaving potential with dynamic pricing and optimization. Energy consumption in buildings continues to rise with increased deployment of energy-consuming equipment such as Heating, Ventilation, and Air Conditioning (HVAC) amid a growing world economy. Renewable energy is projected to comprise a majority of the future electricity supply, but the intermittent nature of renewables means that consumption must respond to dynamic supply for optimal utilization. This paper proposes a novel HVAC control strategy for residential buildings using the adaptive comfort model, considering occupancy through probability and real-time information, and optimizing the HVAC schedule to reduce cost, maintain thermal comfort, and respond to the dynamic availability of renewable energy while being generalizable to different situations. To validate this approach, the Universal CPS Environment for Federation (UCEF) co-simulation platform is used to connect advanced building controls with the building energy simulation software EnergyPlus. Simulations are performed for a residential building in Sacramento, CA during a typical summer week. Economic impacts, energy consumption, and thermal comfort are analyzed for traditional, adaptive, and occupancy-based control strategies under demand-based, tiered, and fixed electric tariff systems. Simulation results show that occupancy consideration, adaptive thermal comfort, and optimization can reduce cost by 50.1 %, electricity consumption by 52.9 %, and discomfort by 56.2 % compared to traditional fixed setpoints. The ability of the proposed HVAC control strategy to shift energy consumption away from peak times under a demand-based tariff system is qualitatively analyzed and findings suggest that maximum load-shifting on a grid-scale is attained using occupancy consideration with optimized control and demand-based pricing. For individual residential buildings, similar economic benefits can be gained using the less-complex adaptive HVAC control strategy with existing tiered or simple electric tariff systems. [ABSTRACT FROM AUTHOR]

The human factor of critical infrastructure systems (CISs), which refers to the impact of various human characteristics on system operations and management, is a significant contributor to failures in CISs. Advanced techniques for simulating the dynamic influence between the human and technical aspects of CISs are needed for understanding the evolution of man-made disasters in CISs and proposing measures for improving CISs reliability and resilience. Hence, this paper proposes a high-level architecture (HLA) based framework for co-simulating CISs domain-specific models and human performance models and analyzing dynamic human-system interactions. A case study demonstrates the efficacy of the proposed framework in simulating complex feedback loops between the operator performance and system states. The proposed framework is valuable for CISs managers in identifying potential human-related failure points in the systems and making informed decisions to mitigate them. Moreover, future research can leverage the proposed framework for improving the resilience assessment of CISs. • An HLA-based framework for modeling infrastructure systems operations is proposed. • The framework incorporates human factor using dynamic human performance models. • Dynamic performance shaping factors are adjusted based on systems states. • Effect of continuous working hours on human reliability is modeled and assessed. • The occurrence and propagation of system failures due to human error are analyzed. [ABSTRACT FROM AUTHOR]

This paper presents an intelligent fire-fighting robot with multiple sensors and introduces the composition of the control system. The kinematic equation of the robot and the fire water monitor jet trajectory are established. Moreover, the fire extinguishing space at the end of the fire water monitor is simulated and analyzed to obtain the operating range of the fire-fighting robot and provide theoretical support for the precise fire extinguishing of the robot. The fire-fighting robot virtual prototype is established in RecurDyn. Aiming at trajectory deviation caused by centroid offset, the trajectory correction based on PID control strategy is proposed. According to the co-simulation of RecurDyn and Matlab/Simulink, it is found that the fluctuation range of centroid velocity decreases by 25.2%, and the variance value decreases by 26.2% after using PID deviated angle correction strategy during climbing. The acceleration fluctuation range is lowered by 38.9%, and the mean value is lowered by 51.2%, verifying the accuracy of the trajectory correction control model. [ABSTRACT FROM AUTHOR]

Facade integrated ventilation systems have the potential to improve local air quality and occupant comfort, reduce building energy consumption and provide economic retrofit opportunities. However, existing modelling and evaluation methods are not able to sufficiently address the technology's potential capabilities. In this paper, a new model is developed specifically adapted to facade-integrated air handling units interacting with ventilated fenestration systems. The new modelling approach is based on the co-simulation of two different models through a Functional Mock-Up Unit (FMU) Interface. An airflow network model of the air handling unit is developed in Modelica and exported as an FMU based on this specification. The FMU is then simulated within an updated version of the building simulation program Fener that includes a physical model that calculates the window heat fluxes and temperatures, as well as the window gap air outlet temperature in case of ventilated facades. The different sub-models are first validated versus experimental data from a test chamber in Villafranca di Verona, Italy. Then, the full co-simulation approach is applied to a case study in which different control strategies for the fenestration system are investigated. [ABSTRACT FROM AUTHOR]

History matching is an iterative process that modifies a reservoir model to reproduce field behavior. Due to the scarcity of data the true distribution of facies, porosity and permeability between widely spaced wells is unknown, resulting in high uncertainty. As the spatial patterns of permeability and porosity often significantly affect the flow response, evaluating heterogeneity is key in history matching. This work presents a stochastic method for use in probabilistic and iterative history matching. We select a set of the best geostatistical realizations and reproduce their spatial patterns in subsequent iterations to create a new set of better-matched models. All models, throughout the process, honor well log data and continuity, modeled with the variograms. This paper uses four approaches: two using a global method and two using a regional method. Both methods improved dynamic history data matching while honoring all well data but each is suited to different times in exploration and production. We present the global method as a simple tool to improve models. Characterized as an update of the entire reservoir, it is useful when the number of wells and the dynamic history data are scarce. The regional method is more efficient to process large amounts of information, enabling the independent match of dynamic well data, avoiding mismatches with other wells. [ABSTRACT FROM AUTHOR]