Classic Mosaik keeps the setup time nearly constant around 7s but it cannot handle more than 10k instances due to its design limitations. Cite this article. As the study by Dahash et al. This distributed configuration participates in the hybrid scaling vision of implementing horizontal scaling. Toshimasa Takanohashi, , Kazuo Nakamura, , Yuki Terao and, Masashi Iino. IEEE. However, since these modifications are not user-friendly and are not included in Mosaiks API implementation, this framework was used as is, with this scaling limitation. Then, the DRTS will be interconnected with a distributed co-simulation environment running other MES models. Google Scholar, Barbierato L, Schiera DS, Patti E, Macii E, Pons E, Bompard EF, et al (2020) GAMES: a general-purpose architectural model for multi-energy system engineering applications. Indeed, Mosaik-AIOMAS takes 0.78s at 10k instances and AIOMAS takes 0.76s, while all the others take around 0.1s. In a nutshell, these operations are related to the Initialization task of a general co-simulation framework. 8, the setup execution time performances of the different configurations are presented. The KPI trends of the total execution time in Fig. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. As already mentioned, a comparison with Mosaik is only possible below 10k Model Instances. Co-simulation is an emerging enabling technique, where global simulation of a coupled system can be achieved by composing the simulations of its parts. Energy Informatics IEEE. A high-level representation of the multi-model energetic scenario is presented in Fig. The 6th International Conference on Power and Energy Systems Engineering (CPESE 2019), September 20-23, 2019, Okinawa, Japan. 2020), of which the most prominent example can be found in the Smart Grid concept. Simulators instead contain a specific Model Instance class and have different functionalities (e.g. When dealing with a high number M of Agents, a Main Container (e.g. Energy & Fuels 2000, 14 (3) , 566-574. 2011) and HELICS(Palmintier etal. The authors conclude that implementing benchmarks and deriving a comparative performance analysis of the co-simulation frameworks is worth investigating for future works. This Simulator collects the hourly data coming from the PV Simulator and the Building Simulator (i.e. This approach enhances the performances with respect to having a centralized Data Exchange Management with an Orchestrator. For the purpose of evaluating the scalability of the co-simulation frameworks presented in Enabling technologies for co-simulation environments section, a hybrid scaling approach has been chosen among the three possible options to assess what could be the impact of scaling up and scaling out a generic MES Scenario on a distributed cluster of nodes. His research interests include use of data-driven methods to detect and diagnose attacks in cyber-physical systems, statistical machine learning, and deep learning applications for anomaly detection. Agents are thought of as software components that perform computations and virtually mimic the actions and interactions of real-world systems. Transmission and distribution cosimulation: a review and propositions To draw some conclusions, it is possible to say that Mosaik is a very useful framework when dealing with small/medium size environments, offering good quality results and ease of implementation. In our case, this threshold is above 100 Model instances. The four Simulators (or Containers in the AIOMAS perspective) are: (i) the Meteo Simulator, (ii) the PV Simulator, (iii) the Building Simulator, and (iv) the Power Grid Simulator. 2019; Bottaccioli etal. (2021) to simulate a building equipped with a heat pump system. 5560, Schweiger G, Gomes C, Engel G, Hafner I, Schoeggl J, Posch A et al (2019) An empirical survey on co-simulation: promising standards, challenges and research needs. Finally, each Simulator iteratively runs M Model Instances in its process; (b) The Multi-process Co-simulation implementation (see Fig. 4c) is the typical configuration of the AIOMAS framework in which agents are represented as simulators. multiple processes), going from around 6s to 62s. In fact, Mosaik has a design limitation on the maximum size of data exchanged that did not allow scaling beyond 10k of Model Instances. Research areas: Systems modeling and optimization to energy and the environment. (Suppl 4), 53 (2022). The proposed co-simulation benchmark configurations: (a) Classic Co-simulation, (b) Multi-process Co-simulation, (c) Multi-Agent System as Co-simulation framework, and (d) Classic Co-simulation configuration with encapsulated multi-process Multi-Agent System, Decomposition of the Total Execution Time in its main contribution: (i) the Scenario Setup, (ii) the Co-simulation, and (iii) the Termination Processes. Then, the trend flattens out because the same number of parallel processes have been launched. An advanced adaptive multi-rate co-simulation platform was developed and validated in this study for accurate and accelerated simulation of power system transients. (2019) with a co-simulation between COMSOL Multiphysics 3 and Dymola showed, besides the very low computational performance, also a loss of information was observed . The OOP Scenario component in this configuration does not have a specific implementation. 16, Zhang J, Daily J, Mast RA, Palmintier B, Krishnamurthy D, Elgindy T et al (2020) Development of HELICS-based high-performance cyber-physical co-simulation framework for distributed energy resources applications. This means that the end user must take into account this task in a programmatic way encapsulating time management into Agents or creating an external agent as an orchestrator. Mosaik performed the worst scalability mainly due to the intrinsic limitation that does not allow to scale up beyond 10k Model Instances. The average time step duration differences among the co-simulation frameworks are really small up to 10k instances, except for Mosaik-AIOMAS and AIOMAS due to the overhead introduced by the message exchange between Agents. However, they differ in the possible implementation of vertical scaling. Finally, the above features and proposed results allow for a comparison of the overall scalability performance. Reducing that consumption and "shaping" it to match renewable generation requires us to design and operate buildings to be more efficient, flexible, and responsive. Python, C++, JAVA, Nim) and simulation software (e.g. According to Smart Grid Architectural Model (SGAM)(Bruinenberg etal. Your US state privacy rights, Figure2d shows AIOMAS relational entities following the generic co-simulation infrastructure described above. Springer Nature. IEEE Trans Industr Inf 13(4):18061816, Blochwitz T, Otter M, Arnold M, Bausch C, Clau C, Elmqvist H, et al (2011) The functional mockup interface for tool independent exchange of simulation models. The tasks required to establish the co-simulated environment are similar to the aforementioned frameworks and are: (i) the Container creation, (ii) the Agent collection generation, (iii) and the distributed orchestration infrastructure start-up (i.e. MATLAB). For instance, the Main PV Container spawns child Containers \(A_1, , A_N\) each one managing M/N equally distributed Agents; (d) The Classic Co-simulation implementation with encapsulated Multi-Process Multi-Agent Systems (see Fig. The additions also allow executing system commands, such as a script that executes a Radiance simulation. In the next sections, the time-based KPIs mentioned in Benchmark key performance index (KPI)section are presented to evaluate the comparison among the different co-simulation framework configurations. AIOMAS demonstrated the same ability to scale as HELICS with respect to the number of instances. Co-simulation of building energy and control systems with the building controls virtual test bed. 2017). This approach requires a distributed co-simulation Orchestrator that can act as a load balancer that distributes tasks and manages data exchange and synchronization of all working nodes. In data exchange management, the main issue is related to the communication latency that usually affects telecommunication protocols. By implementing a distributed deployment of Simulator, this configuration will enhance the simulation capabilities with respect to standalone simulation. Two cluster nodes manage respectively the Meteo Simulator and the Power Grid Simulator, each one handling its single Model Instance. No documentation for this configuration is present, making its implementation require more effort. events) with other Agents interested in receiving it. In: 2013 IEEE International Conference on Smart Grid Communications (SmartGridComm); p. 576581, Gomes C, Thule C, Broman D, Larsen PG, Vangheluwe H (2018) Co-simulation: a survey. 4b) evolves the classic configuration by enabling a multi-process division of a Simulator node (e.g. Size scalability represents the issues in growing the dimension of the co-simulated system and what are the possible solutions to manage the high number of Simulators and Model Instances to run a huge complex Scenario and its orchestration. The main objective of this paper is to understand which of the proposed benchmark setups performs better in terms of simulation time when it comes to increase the size of the simulated environment. For instance, Mosaik allows multi-processing but its implementation has to be done manually. To conclude and easily interpret the analysis of experimental results, in the next section, a summary of all the tested configurations is presented in Table1. The output of this simulator is the generating power for the given time step, which is forwarded to the Power Grid Simulator. Part of p. 33413346, Scherfke S (2014) aiomas Documentation. This peculiarity addresses one of the main challenges of co-simulation, which is the complex time regulation when it comes to hybrid simulation; with AIOMAS, it is possible to distribute the time regulation and customize it at the expense of more implementation effort. Faculty Experts | Cornell Energy Systems Institute 2016). Finally, administrative scalability represents the difficulties in managing a co-simulation framework when dealing with increasing both previous scalability dimensions, thus the engineering effort required to avoid the complex setup of the co-simulation framework, the orchestrator, and the distribution of Simulators and their Model Instances among network nodes, and their interconnections. Co-simulation is often related to Cyber-Physical Systems (CPS) (Palensky et al. Linkping University Press; p. 105114, Bottaccioli L, Estebsari A, Pons E, Bompard E, Macii E, Patti E et al (2017) A flexible distributed infrastructure for real-time co-simulations in smart grids. It works well with small to medium scenarios but has limited scalability when going over large scenarios. Multisite European framework for realtime cosimulation of power systems In order to test the benchmark presented in Methodology for benchmarking design section, a common realistic scenario has been prepared. Affiliation: Politecnico di Torino. Their outputs are sent to the Power Grid Simulator which uses them to calculate the power flow of the power grid. The Initialization process finally sets up the co-simulation environment by establishing all the relationships and connections among Model Instances of all Simulators involved in the co-simulation environment. 2bd represent the specific implementations of these components inside the three main framework analysed: Mosaik, HELICS and AIOMAS. Surrogate models for composed simulation models in energy systems The Time Regulation and Synchronization task instead manages and regulates the time step progression of each individual Simulator. This figure offers a general overview of the interacting components in a co-simulation framework, while Fig. It also estimates the cell temperature using the so-called NOCT method(Brihmat and Mekhtoub 2014) when wind speed is not available as input and, on the other hand, it uses the Mattei method(Mattei etal. View the job description, responsibilities and qualifications for this position. Both these facts make it difficult to study coupled heterogeneous systems. The PV Simulator is a stateless Simulator that uses the estimate PV energy service of the model in Bottaccioli etal. Simplifying multi-energy system co-simulations using energysim To conclude, the former model has four main functionalities that calculate: (i) the real-time heat pump power demand, (ii) the heat pump power demand forecasting, (iii) the heat pump energy flexibility, and (iv) the actuation commands of the heat pump control strategy. IEEE Trans Power Syst 33(6):65106521, United Nations (2022) Energy, UN-Habitat. 7a) for HELICS and Mosaik; (ii) two configurations of the Multi-process Co-simulation (Figure7b) for HELICS multi-process and Mosaik multi-process; (iii) one configuration of MAS as a Co-simulation framework (Fig. 1 process) to 100 instances (i.e. Mosaik is a Python co-simulation framework developed to couple existing Simulators in the Smart Grid field. Computer Simulation of Solvent Swelling of Coal Molecules: Effect of Different Solvents. 6 the simple input/output interactions between Simulators are presented. Omani Research Team designs smart grid monitoring system In return, Simulators receive outputs from Model Instances that are sent to the Orchestrator. The power grid simulator is a stateless Simulator that emulates a power grid model with different connected loads. IEEE. From the point of view of Simulators interactions have the same qualities of classic HELICS. Colorado Energy Research Collaboratory Research Services Fort Collins, Colorado 130 followers Since 2008, the Collaboratory has successfully created energy-related partnerships between CU Boulder . Co-Simulation: A Survey: ACM Computing Surveys: Vol 51, No 3 However, this configuration could suffer from the typical information exchange drawback of the Classic Co-simulation configuration due to the central Data Exchange Management of the Orchestrator. 2015), General-purpose architectural model for MES engineering application (GAMES). The heat load is then converted to the heat pump power request. The implementation requires some manual workarounds that are not embedded into the Mosaik framework as it is. (c) The Multi-Agent System as Co-simulation configuration (see Fig. Privacy This behaviour does not occur when coupling HELICS and AIOMAS because launching multi-processes and container creation is handled by HELICS with less computational overhead, following the same HELICS multi-process trend. IEEE Syst J 12(3):28322841, Brihmat F, Mekhtoub S (2014) PV cell temperature/PV power output relationships homer methodology calculation. Associate Research Physicist - Low Temperature Plasma Simulations Princeton University Princeton, New Jersey Postdoctoral researcher to work on "Biophysics of the Gut" projects Ismagilov Group - Caltech Pasadena, California NEW! In this paper, we propose a comparison of the scalability performance of two major co-simulation frameworks (i.e. (2018) present a comparison between Mosaik and implementation of the IEEE 1516 High-Level Architecture (HLA), which is similar to HELICS implementation. By using this website, you agree to our The HELICS architecture and its relational entities are presented in Fig. Then, the scalability problem of co-simulation frameworks is introduced presenting four benchmark configurations to test their ability to scale in terms of a number of running instances. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Combining such disparate disciplines into a single tool for modeling and analyzing such a complex environment as a Multi-Energy System requires tremendous effort. Energy Systems | Editors - Springer Accessed 26 Jun 2022, Coelho VN, Cohen MW, Coelho IM, Liu N, Guimares FG (2017) Multi-agent systems applied for energy systems integration: state-of-the-art applications and trends in microgrids. buses, lines, transformers) along with their nominal parameters. The simulation and co-simulation of the power grid has been established as a tool for testing and assessing new technologies and methodologies, as the real power grid as a safety-critical infrastructure is not suitable for testing (Niee et al., 2014).The models used in such simulations are only abstractions of their underlying systems, but can also be quite complex and therefore expensive to . From an Information and Communication Technology (ICT) perspective, scalability is measured typically with three indicators known as scalability dimensions: (i) size, (ii) geographical, and (iii) administrative scalability. Sustain Comput Inf Syst 35:100726, Motie Y, Belghache E, Nketsa A, Georg JP (2018) Interoperability based dynamic data mediation using adaptive multi-agent systems for co-simulation. HELICS, in particular when implemented in its multi-processing configuration, gives the best scalability performance allowing to be suitable for any scenario size, furthermore, it is easy to be implemented and allows more freedom on the interactions design due to its publish subscribe paradigm, on the overall this configuration proved to be the most flexible and performing above all the tested ones. In this simulation, it is actually used as a discrete event simulator that is triggered by the reception of both building and PV data. 2017). In: IECON 2010-36th Annual Conference on IEEE Industrial Electronics Society. Furthermore, when dealing with complex relationships and data exchange among simulators it is not as efficient as other solutions. The time resolution of the simulators is configurable and could differ from one simulator to another. This individual will report to the Manager of Research & Analysis and will be expected to work collaboratively across the organization and with a myriad of external stakeholders. Your privacy choices/Manage cookies we use in the preference centre. Geographical scalability, on the other hand, is the representation of the complexity of managing an increasing number of geographically distributed computational nodes (e.g., different laboratories) to implement a co-simulation Scenario. The benchmark configurations in Fig. In this view, different Simulators are distributed over different network nodes that manage their Model Instances. In literature, some integration of MAS simulators in Co-simulation frameworks can be found, but by abstracting a little more the concept of MAS it is possible to see a co-simulation framework as a system in which really complex and different agents (e.g. Quantum Sensing of Quantum Devices - R&D Associate Oak Ridge National Laboratory Oak Ridge, Tennessee HELICS instead uses a Publish/Subscribe approach that could enhance the performance but can lead to wasting resources in data polling requests. IEEE Std 15162-2010 (Revision of IEEE Std 15162-2000) - Redline. The benchmark design will consider the general Scenario depicted above. (2018) and Schweiger etal. Co-simulation frameworks, such as Mosaik and HELICS, have been developed to ease such integration. In fact, Simulators transmit inputs received by their peers via the Orchestrator and the Orchestrator commands to their Model Instance collection. All of these simulators have really short wall-clock times for executing a single step thus the simulation time-step could range from seconds to hours. These two components respectively share the tasks of Data Exchange Management and Time Regulation and Synchronization. IEEE Trans Ind Appl 56(5):56135624, Article Author guidelines Ready to publish? The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material.
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