Pub Date : 2020-02-01DOI: 10.1109/ICON.2004.1409066
Lawrence W.C. Wong, Lee-Yee Lau, H. Pang, Francis Lee, C. Tham
Cyber-physical energy systems (CPES) use computers and networks to orchestrate energy generation, distribution, and consumption. Such systems challenge existing engineering methods for control systems design, software engineering, and networking systems because of their heterogeneity, very large scale, safety criticality, and vulnerability to security risks. The behavior of such systems is also strongly affected by markets and regulation, factors that don't always manifest easily in engineering design.
{"title":"Message from the chairs","authors":"Lawrence W.C. Wong, Lee-Yee Lau, H. Pang, Francis Lee, C. Tham","doi":"10.1109/ICON.2004.1409066","DOIUrl":"https://doi.org/10.1109/ICON.2004.1409066","url":null,"abstract":"Cyber-physical energy systems (CPES) use computers and networks to orchestrate energy generation, distribution, and consumption. Such systems challenge existing engineering methods for control systems design, software engineering, and networking systems because of their heterogeneity, very large scale, safety criticality, and vulnerability to security risks. The behavior of such systems is also strongly affected by markets and regulation, factors that don't always manifest easily in engineering design.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114436468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115406
B. Kelley, P. Top, Steven G. Smith, C. Woodward, L. Min
This paper introduces a federated simulation toolkit (FSKIT) that couples continuous time and discrete event simula- tions (DES) to perform the co-simulation of electric power grids and communication networks. A High Performance Computing (HPC) oriented power system dynamic simulator, GridDyn, was used for the electric power grid simulation. GridDyn is coupled to the open-source network simulator, ns-3, through FSKIT. FSKIT provides time control for advancing the state of federated simulators, and facilitates communication among objects in the federate. A wide-area communication-based electric transmission protection scheme is simulated with FSKIT, using the IEEE 39- bus test system. A communication network for the 39-bus system is built in ns-3, and basic protection relay logic is added to the power system model in order to perform the co-simulation.
{"title":"A federated simulation toolkit for electric power grid and communication network co-simulation","authors":"B. Kelley, P. Top, Steven G. Smith, C. Woodward, L. Min","doi":"10.1109/MSCPES.2015.7115406","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115406","url":null,"abstract":"This paper introduces a federated simulation toolkit (FSKIT) that couples continuous time and discrete event simula- tions (DES) to perform the co-simulation of electric power grids and communication networks. A High Performance Computing (HPC) oriented power system dynamic simulator, GridDyn, was used for the electric power grid simulation. GridDyn is coupled to the open-source network simulator, ns-3, through FSKIT. FSKIT provides time control for advancing the state of federated simulators, and facilitates communication among objects in the federate. A wide-area communication-based electric transmission protection scheme is simulated with FSKIT, using the IEEE 39- bus test system. A communication network for the 39-bus system is built in ns-3, and basic protection relay logic is added to the power system model in order to perform the co-simulation.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116639371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115412
A. Chhokra, A. Dubey, N. Mahadevan, G. Karsai
Resiliency and reliability is of paramount impor- tance for energy cyber physical systems. Electrical protection systems including detection elements such as Distance Relays and actuation elements such as Breakers are designed to protect the system from abnormal operations and arrest failure propagation by rapidly isolating the faulty components. However, failure in the protection devices themselves can and do lead to major system events and fault cascades, often leading to blackouts. This paper augments our past work on Temporal Causal Diagrams (TCD), a modeling formalism designed to help reason about the failure progressions by (a) describing a way to generate the TCD model from the system specification, and (b) understand the system failure dynamics for TCD reasoners by configuring simulation models.
{"title":"A component-based approach for modeling failure propagations in power systems","authors":"A. Chhokra, A. Dubey, N. Mahadevan, G. Karsai","doi":"10.1109/MSCPES.2015.7115412","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115412","url":null,"abstract":"Resiliency and reliability is of paramount impor- tance for energy cyber physical systems. Electrical protection systems including detection elements such as Distance Relays and actuation elements such as Breakers are designed to protect the system from abnormal operations and arrest failure propagation by rapidly isolating the faulty components. However, failure in the protection devices themselves can and do lead to major system events and fault cascades, often leading to blackouts. This paper augments our past work on Temporal Causal Diagrams (TCD), a modeling formalism designed to help reason about the failure progressions by (a) describing a way to generate the TCD model from the system specification, and (b) understand the system failure dynamics for TCD reasoners by configuring simulation models.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125192230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Demand response (DR) used in smart grid (SG) can enhance the reliability of the power system as well as reduce the energy costs for customers. One of the major consumers of electrical energy is industry. In this study, we develop a hardware-in-the-loop (HIL) simulator to demonstrate how to practically implement DR in industrial facilities. The HIL simulator includes an energy management system (EMS), a monitoring and control system (MCS), an industrial Ethernet backbone network based on RAPIEnet protocol, and a wireless field network based on ISA100.11a protocol. The results show that the electricity demand of industrial facilities can be shifted from peak to off-peak demand periods to improve the reliability of the electrical grid.
{"title":"A hardware-in-the-loop simulator for demand response energy management in industrial facilities","authors":"Zhe Luo, Musharraf Alam, S. Hong, Yuemin Ding, Aidong Xu, Daehyun Kwon","doi":"10.1109/MSCPES.2015.7115396","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115396","url":null,"abstract":"Demand response (DR) used in smart grid (SG) can enhance the reliability of the power system as well as reduce the energy costs for customers. One of the major consumers of electrical energy is industry. In this study, we develop a hardware-in-the-loop (HIL) simulator to demonstrate how to practically implement DR in industrial facilities. The HIL simulator includes an energy management system (EMS), a monitoring and control system (MCS), an industrial Ethernet backbone network based on RAPIEnet protocol, and a wireless field network based on ISA100.11a protocol. The results show that the electricity demand of industrial facilities can be shifted from peak to off-peak demand periods to improve the reliability of the electrical grid.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129359359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115395
R. Liu, A. Srivastava
With the development of the smart grid technology, Information and Communication Technology (ICT) plays a sig- nificant role in the smart grid. ICT enables to realize the smart grid, but also brings cyber vulnerabilities. It is important to analyze the impact of possible cyber-attacks on the power grid. In this paper, a real-time, cyber-physical co-simulation testbed with hardware-in-the-loop capability is discussed. Real-time Digital Simulator (RTDS), Synchrophasor devices, DeterLab, and a wide- area monitoring application with closed-loop control are utilized in the developed testbed. Two different real life cyber-attacks, including TCP SYN flood attack, and man-in-the-middle attack, are simulated on an IEEE standard power system test case to analyze the the impact of these cyber-attacks on the power grid.
随着智能电网技术的发展，信息通信技术(ICT)在智能电网中发挥着重要的作用。信息通信技术使智能电网得以实现，但也带来了网络漏洞。分析可能的网络攻击对电网的影响是很重要的。本文讨论了一种具有硬件在环能力的实时网络物理联合仿真试验台。该试验台采用实时数字模拟器(RTDS)、同步相量装置、检测实验室和具有闭环控制的广域监测应用程序。在IEEE标准电力系统测试用例上，模拟了TCP SYN flood攻击和中间人攻击两种不同的现实网络攻击，分析了网络攻击对电网的影响。
{"title":"Integrated simulation to analyze the impact of cyber-attacks on the power grid","authors":"R. Liu, A. Srivastava","doi":"10.1109/MSCPES.2015.7115395","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115395","url":null,"abstract":"With the development of the smart grid technology, Information and Communication Technology (ICT) plays a sig- nificant role in the smart grid. ICT enables to realize the smart grid, but also brings cyber vulnerabilities. It is important to analyze the impact of possible cyber-attacks on the power grid. In this paper, a real-time, cyber-physical co-simulation testbed with hardware-in-the-loop capability is discussed. Real-time Digital Simulator (RTDS), Synchrophasor devices, DeterLab, and a wide- area monitoring application with closed-loop control are utilized in the developed testbed. Two different real life cyber-attacks, including TCP SYN flood attack, and man-in-the-middle attack, are simulated on an IEEE standard power system test case to analyze the the impact of these cyber-attacks on the power grid.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"500 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134190122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115394
Eman M. Hammad, Abdallah K. Farraj, D. Kundur
We study the effect of control area design on the performance of distributed control. Specifically, we consider distributed implementations of parametric feedback linearization (PFL) control for efficient transient stability after the occurrence of a power system disturbance. We employ hierarchical spectral clustering and k-mean spectral clustering techniques to design control areas with high physical coupling within the power system. We address three distributed control scenarios: (i) distributed control applied to all generators of a control area, (ii) distributed control applied only to the largest inertia generator within a control area, and (iii) hierarchical distributed control where all generators apply distributed control and lead generators within a control area have centralized control. We investigate the effect of area clustering outcomes and compare the performance of the three control approaches for various power system faults.
{"title":"On the effects of distributed control area design for the stabilization of cyber-enabled smart grids","authors":"Eman M. Hammad, Abdallah K. Farraj, D. Kundur","doi":"10.1109/MSCPES.2015.7115394","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115394","url":null,"abstract":"We study the effect of control area design on the performance of distributed control. Specifically, we consider distributed implementations of parametric feedback linearization (PFL) control for efficient transient stability after the occurrence of a power system disturbance. We employ hierarchical spectral clustering and k-mean spectral clustering techniques to design control areas with high physical coupling within the power system. We address three distributed control scenarios: (i) distributed control applied to all generators of a control area, (ii) distributed control applied only to the largest inertia generator within a control area, and (iii) hierarchical distributed control where all generators apply distributed control and lead generators within a control area have centralized control. We investigate the effect of area clustering outcomes and compare the performance of the three control approaches for various power system faults.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133498534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115393
T. Ryutov, Anas AlMajali, C. Neuman
While demand response programs achieve energy efficiency and quality objectives, they bring potential security threats into the Smart Grid. An ability to influence load in the system provides the capability for an attacker to cause system failures and impacts the quality and integrity of the power delivered to customers. This paper presents a security mechanism that monitors and controls load according to security policies during normal system operation. The mechanism monitors, detects, and responds to load altering attacks. The authors examined security requirements of Smart Grid stakeholders and constructed a set of load control policies enforced by the mechanism. A proof of concept prototype was implemented and tested using the simulation environment. By enforcing the proposed policies in this prototype, the system is maintained in a safe state in the presence of load drop attacks.
{"title":"Modeling security policies for mitigating the risk of load altering attacks on smart grid systems","authors":"T. Ryutov, Anas AlMajali, C. Neuman","doi":"10.1109/MSCPES.2015.7115393","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115393","url":null,"abstract":"While demand response programs achieve energy efficiency and quality objectives, they bring potential security threats into the Smart Grid. An ability to influence load in the system provides the capability for an attacker to cause system failures and impacts the quality and integrity of the power delivered to customers. This paper presents a security mechanism that monitors and controls load according to security policies during normal system operation. The mechanism monitors, detects, and responds to load altering attacks. The authors examined security requirements of Smart Grid stakeholders and constructed a set of load control policies enforced by the mechanism. A proof of concept prototype was implemented and tested using the simulation environment. By enforcing the proposed policies in this prototype, the system is maintained in a safe state in the presence of load drop attacks.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128026788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115410
S. Lehnhoff, Okko Nannen, S. Rohjans, Florian Schlogl, Stefan Dalhues, L. Robitzky, U. Hager, C. Rehtanz
Power flow simulators are indispensible when simulating and assessing future energy system scenarios potentially comprising vast numbers of actors, devices, markets, environmental phenomena etc. While open source power flow simulators are an appealing choice - as they come free of charge - commercially available power flow simulation and optimization suites have the clear benefit of being well established and trusted by the industry. Open source implementations often lack validation against these “trusted” outputs. In this paper we will demonstrate and discuss the integration and exchange of different (commercial as well as open source) power flow simulators with the co-simulation framework mosaik for the sake of comparing and possibly benchmarking the output of open source simulators.
{"title":"Exchangeability of power flow simulators in smart grid co-simulations with mosaik","authors":"S. Lehnhoff, Okko Nannen, S. Rohjans, Florian Schlogl, Stefan Dalhues, L. Robitzky, U. Hager, C. Rehtanz","doi":"10.1109/MSCPES.2015.7115410","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115410","url":null,"abstract":"Power flow simulators are indispensible when simulating and assessing future energy system scenarios potentially comprising vast numbers of actors, devices, markets, environmental phenomena etc. While open source power flow simulators are an appealing choice - as they come free of charge - commercially available power flow simulation and optimization suites have the clear benefit of being well established and trusted by the industry. Open source implementations often lack validation against these “trusted” outputs. In this paper we will demonstrate and discuss the integration and exchange of different (commercial as well as open source) power flow simulators with the co-simulation framework mosaik for the sake of comparing and possibly benchmarking the output of open source simulators.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131259320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115400
K. Sedzro, M. Chuah, A. Lamadrid
Reducing peak demand is critically important in smartgrid as a significant fraction of the electric grids capital and operational expenses is affected by the peak power demands. Time of Use (ToU) and Real Time Pricing (RTP) pricing schemes have been used by power system operators to incentivize cus- tomers to reduce their peak energy demands during peak hours. However, ToU only provides a weak incentive for customers and does not promote adoption at scale. Similarly, day-ahead Real- Time Pricing (RTP) scheme might create peaks in previoulsy off-peak periods and causes some ping-pong effect in next day prices. In this paper, we introduce a new incentive-driven scheme called Minimax which encourages customers to flatten their daily load profiles such that they can reduce their electricity bill and help lowering the aggregate peak power demands. Using two real life energy usage datasets, we show via simulations how the peak energy usage and load factor vary with different choices of parameter values we select for the Minimax scheme. In addition, we present our optimal scheduling policy which yields the minimum energy bill assuming a certain percentage of load demands is schedulable. Our results using energy usage data of 100 homes from the UMASS dataset show that customers can save 13-17% of their electricity bills if the Minimax scheme is used but only about 2-3% if RTP or TOU scheme is used. Furthermore, the power system operators see a 10% reduction in peak power demand if appropriate parameter values are used for the Minimax scheme while the peak demands increase by more than 70% using RTP or TOU schemes.
{"title":"Minimax: an incentive-driven pricing scheme in the electricity retail market","authors":"K. Sedzro, M. Chuah, A. Lamadrid","doi":"10.1109/MSCPES.2015.7115400","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115400","url":null,"abstract":"Reducing peak demand is critically important in smartgrid as a significant fraction of the electric grids capital and operational expenses is affected by the peak power demands. Time of Use (ToU) and Real Time Pricing (RTP) pricing schemes have been used by power system operators to incentivize cus- tomers to reduce their peak energy demands during peak hours. However, ToU only provides a weak incentive for customers and does not promote adoption at scale. Similarly, day-ahead Real- Time Pricing (RTP) scheme might create peaks in previoulsy off-peak periods and causes some ping-pong effect in next day prices. In this paper, we introduce a new incentive-driven scheme called Minimax which encourages customers to flatten their daily load profiles such that they can reduce their electricity bill and help lowering the aggregate peak power demands. Using two real life energy usage datasets, we show via simulations how the peak energy usage and load factor vary with different choices of parameter values we select for the Minimax scheme. In addition, we present our optimal scheduling policy which yields the minimum energy bill assuming a certain percentage of load demands is schedulable. Our results using energy usage data of 100 homes from the UMASS dataset show that customers can save 13-17% of their electricity bills if the Minimax scheme is used but only about 2-3% if RTP or TOU scheme is used. Furthermore, the power system operators see a 10% reduction in peak power demand if appropriate parameter values are used for the Minimax scheme while the peak demands increase by more than 70% using RTP or TOU schemes.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124043933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115404
Mario Faschang, F. Kupzog, E. Widl, S. Rohjans, S. Lehnhoff
Modeling and simulation are essential for the development and assessment of new technologies for complex cyber-physical systems, both in academia and industry. One particular instance of such complex systems are novel energy systems. They comprise a variety of heterogeneous physical domains (electricity, thermal, gas, etc.), modeled as time continuous dynamic systems, and time discrete communication and control systems. Tools and solutions based on co-simulation concepts for such cyber-physical energy systems (CPES) have been developed in recent years. This paper focuses on the need for real-time hardware integration into CPES simulation, identified from recently conducted research projects. From those projects - presented as use cases - relevant actors are identified and their interaction and data exchange is discussed. Resulting requirements are presented for the CPES simulation and the hardware to be integrated. The handling of heterogeneous laboratory hardware is discussed and a simplification in the form of a hardware abstraction layer is proposed.
{"title":"Requirements for real-time hardware integration into cyber-physical energy system simulation","authors":"Mario Faschang, F. Kupzog, E. Widl, S. Rohjans, S. Lehnhoff","doi":"10.1109/MSCPES.2015.7115404","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115404","url":null,"abstract":"Modeling and simulation are essential for the development and assessment of new technologies for complex cyber-physical systems, both in academia and industry. One particular instance of such complex systems are novel energy systems. They comprise a variety of heterogeneous physical domains (electricity, thermal, gas, etc.), modeled as time continuous dynamic systems, and time discrete communication and control systems. Tools and solutions based on co-simulation concepts for such cyber-physical energy systems (CPES) have been developed in recent years. This paper focuses on the need for real-time hardware integration into CPES simulation, identified from recently conducted research projects. From those projects - presented as use cases - relevant actors are identified and their interaction and data exchange is discussed. Resulting requirements are presented for the CPES simulation and the hardware to be integrated. The handling of heterogeneous laboratory hardware is discussed and a simplification in the form of a hardware abstraction layer is proposed.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124522504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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