A.A. van der Meer
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33 records found
1
Conference paper
(2023)
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Bart van der Holst, Gijs Verhoeven, Edwin Matthijssen, Mark Vrijlandt, Arjen van der Meer, Ruduan Plug, Koen Kok
Due to the increasing penetration of distributed energy resources, congestion problems are already emerging in Dutch distribution grids. The available flexibility of assets in the built environment could have the potential to reduce congestion if prosumers are properly incentivized by distribution grid operators (DSOs). However, it is not yet clear what (combinations of) flexibility a ctivation mechanisms will be effective for congestion management in Dutch Distribution grids. To shed light on this issue, the GO-e consortium aims at performing large-scale agent-based simulations of up to 120 low-voltage networks and a large variety of possible instruments and scenarios. For this reason, we developed a novel scalable time-discrete simulation framework for distributed agent-based simulations of energy systems. We demonstrate the framework on a case-study in which we assess the effectiveness of a dynamic bandwidth tariff instrument on overloading problems in a low-voltage network containing solar panels, batteries, and heat pumps. It was shown that a dynamic bandwidth tariff can successfully resolve forecasted congestion if the associated costs are high enough compared to the day-ahead prices. However, the resulting load shifting can cause new congestion intra-day aswell.
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Due to the increasing penetration of distributed energy resources, congestion problems are already emerging in Dutch distribution grids. The available flexibility of assets in the built environment could have the potential to reduce congestion if prosumers are properly incentivized by distribution grid operators (DSOs). However, it is not yet clear what (combinations of) flexibility a ctivation mechanisms will be effective for congestion management in Dutch Distribution grids. To shed light on this issue, the GO-e consortium aims at performing large-scale agent-based simulations of up to 120 low-voltage networks and a large variety of possible instruments and scenarios. For this reason, we developed a novel scalable time-discrete simulation framework for distributed agent-based simulations of energy systems. We demonstrate the framework on a case-study in which we assess the effectiveness of a dynamic bandwidth tariff instrument on overloading problems in a low-voltage network containing solar panels, batteries, and heat pumps. It was shown that a dynamic bandwidth tariff can successfully resolve forecasted congestion if the associated costs are high enough compared to the day-ahead prices. However, the resulting load shifting can cause new congestion intra-day aswell.
The Illuminator
An Open Source Energy System Integration Development Kit
Conference paper
(2023)
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Aihui Fu, Raghav Saini, Remko Koornneef, Arjen van der Meer, Peter Palensky, Milos Cvetkovic
This paper introduces a flexible and extendable easy-to-use energy system integration development kit: the Illuminator. The Illuminator illustrates challenges arising from the energy transition. Hence, it is suitable in education and for demonstration. It also acts as a sandbox for testing new research concepts, and particularly, distributed energy coordination algorithms in real and non-real time. The Illuminator technology is primarely a modular software platform developed to run on a Raspberry Pi (RasPi) cluster. It is open-source, available at GitHub and developed in Python. The Illuminator comprises models of common energy technologies, such as photovoltaic (PV) panels, wind turbines, batteries, and hydrogen systems. The uniqueness of the Illuminator is in its modularity and flexibility to reconfigure scenarios and cases on the fly, even by non-experts in a plug-and-play fashion. This paper introduces the Illuminator and shows its performance in a simple case study.
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This paper introduces a flexible and extendable easy-to-use energy system integration development kit: the Illuminator. The Illuminator illustrates challenges arising from the energy transition. Hence, it is suitable in education and for demonstration. It also acts as a sandbox for testing new research concepts, and particularly, distributed energy coordination algorithms in real and non-real time. The Illuminator technology is primarely a modular software platform developed to run on a Raspberry Pi (RasPi) cluster. It is open-source, available at GitHub and developed in Python. The Illuminator comprises models of common energy technologies, such as photovoltaic (PV) panels, wind turbines, batteries, and hydrogen systems. The uniqueness of the Illuminator is in its modularity and flexibility to reconfigure scenarios and cases on the fly, even by non-experts in a plug-and-play fashion. This paper introduces the Illuminator and shows its performance in a simple case study.
Co-simulation is an important tool to capture the complexity of cyber-physical energy systems. The past decade lead us from command-line simulation orchestration to higher readiness-levels in terms of applicability. The configuration and time-domain initialisation of generic co-simulation setups, however, entail a lot of manual activities, especially when simulation components are tightly coupled. This paper provides a qualitative overview on what initialisation challenges crop up and how tools like mosaik can tackle these. This is illustrated with a multi-domain co-simulation example, in which the same time loop concept is applied to resolve cyclic dependencies between simulators during initialisation. The paper provides conclusions about the applicability of same time loops for initialisation purposes and will provide directions for further research on this topic.
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Co-simulation is an important tool to capture the complexity of cyber-physical energy systems. The past decade lead us from command-line simulation orchestration to higher readiness-levels in terms of applicability. The configuration and time-domain initialisation of generic co-simulation setups, however, entail a lot of manual activities, especially when simulation components are tightly coupled. This paper provides a qualitative overview on what initialisation challenges crop up and how tools like mosaik can tackle these. This is illustrated with a multi-domain co-simulation example, in which the same time loop concept is applied to resolve cyclic dependencies between simulators during initialisation. The paper provides conclusions about the applicability of same time loops for initialisation purposes and will provide directions for further research on this topic.
Journal article
(2021)
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Nakisa Farrokhseresht, Arjen van der Meer, José Rueda Torres, Mart A.M.M. van der Meijden
The grid integration of renewable energy sources interfaced through power electronic converters is undergoing a significant acceleration to meet environmental and political targets. The rapid deployment of converters brings new challenges in ensuring robustness, transient stability, among others. In order to enhance transient stability, transmission system operators established network grid code requirements for converter-based generators to support the primary control task during faults. A critical factor in terms of implementing grid codes is the control strategy of the grid-side converters. Grid-forming converters are a promising solution which could perform properly in a weak-grid condition as well as in an islanded operation. In order to ensure grid code compliance, a wide range of transient stability studies is required. Time-domain simulations are common practice for that purpose. However, performing traditional monolithic time domain simulations (single solver, single domain) on a converter-dominated power system is a very complex and computationally intensive task. In this paper, a co-simulation approach using the MOSAIK framework is applied on a power system with grid-forming converters. A validation workflow is proposed to verify the co-simulation framework. The results of comprehensive simulation studies show a proof of concept for the applicability of this co-simulation approach to evaluate the transient stability of a dominant grid-forming converter-based power system.
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The grid integration of renewable energy sources interfaced through power electronic converters is undergoing a significant acceleration to meet environmental and political targets. The rapid deployment of converters brings new challenges in ensuring robustness, transient stability, among others. In order to enhance transient stability, transmission system operators established network grid code requirements for converter-based generators to support the primary control task during faults. A critical factor in terms of implementing grid codes is the control strategy of the grid-side converters. Grid-forming converters are a promising solution which could perform properly in a weak-grid condition as well as in an islanded operation. In order to ensure grid code compliance, a wide range of transient stability studies is required. Time-domain simulations are common practice for that purpose. However, performing traditional monolithic time domain simulations (single solver, single domain) on a converter-dominated power system is a very complex and computationally intensive task. In this paper, a co-simulation approach using the MOSAIK framework is applied on a power system with grid-forming converters. A validation workflow is proposed to verify the co-simulation framework. The results of comprehensive simulation studies show a proof of concept for the applicability of this co-simulation approach to evaluate the transient stability of a dominant grid-forming converter-based power system.
Book chapter
(2020)
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Arjen A. van der Meer, Rishabh Bhandia, Peter Palensky, Milos Cvetkovic, Edmund Widl, Van Hoa Nguyen, Quoc Tuan Tran, Kai Heussen
This chapter provides a brief overview of modelling and simulation approaches for smart grid systems. A special focus is put onto the coupling of simulation environments; i.e., the co-simulation of power systems and its components. Furthermore, selected implementations of standardized interfaces for domain simulators covering the domains of power systems and ICT are presented.
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This chapter provides a brief overview of modelling and simulation approaches for smart grid systems. A special focus is put onto the coupling of simulation environments; i.e., the co-simulation of power systems and its components. Furthermore, selected implementations of standardized interfaces for domain simulators covering the domains of power systems and ICT are presented.
Conference paper
(2019)
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Poria Astero, Matti Laukkanen, Anna Kulmala, Kari Maki, Arjen van der Meer, Rishabh Bhandia, Edmund Widl, Cornelius Steinbrink
For smart grid assessment one needs to simulate varieties of components in different software environments. However, the existing simulation tools are domain oriented and cannot fulfil this need natively. Therefore, a smart grid simulation environment has to be established with accordingly accurate models for intra and inter-domain elements as well as interfaces and framework for coordination of those models in a holistic scenario. This paper presents part of the development of this smart grid simulation environment by implementing co-simulation interface for PSCAD using the mosaik framework based on functional mock-up interface (FMI). This co-simulation interface is tested using a modified dynamic model of IEEE 9 bus test system simulated in PSCAD while the wind turbine controller is simulated in MATLAB/Simulink. The results show a significant advantage over alternative methods in terms of a reduction in simulation runtime and compatibility with different simulation environments.
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For smart grid assessment one needs to simulate varieties of components in different software environments. However, the existing simulation tools are domain oriented and cannot fulfil this need natively. Therefore, a smart grid simulation environment has to be established with accordingly accurate models for intra and inter-domain elements as well as interfaces and framework for coordination of those models in a holistic scenario. This paper presents part of the development of this smart grid simulation environment by implementing co-simulation interface for PSCAD using the mosaik framework based on functional mock-up interface (FMI). This co-simulation interface is tested using a modified dynamic model of IEEE 9 bus test system simulated in PSCAD while the wind turbine controller is simulated in MATLAB/Simulink. The results show a significant advantage over alternative methods in terms of a reduction in simulation runtime and compatibility with different simulation environments.
Report
(2019)
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Rishabh Bhandia, Arjen van der Meer, Przemyslaw Chodura, Yvon Besanger, Tung Lam Nguyen, Panagiotis Mantafounis, Andreas Davros, Edmund Widl, Thomas I. Strasser, Kai Heussen, Tue Vissing Jensen, Cornelius Steinbrink, Van Hoa Nguyen, Franck Bourry, Mazheruddin Syed
This report summarizes the work conducted within ERIGrid related to an integrated simulation environment for large-scale systems.The main goal of the JRA2 is to develop advanced simulation-based tools and methods to validate Smart Grid scenarios, configurations and applications in con-text of co-simulation. The work done in D-JRA2.1 involved assessment of specialized simulation packages for Smart Grids and to develop tools to couple these simulation packages for co-simulation. New tools and models were also developed as some of the existing tools were not sufficient enough to achieve the appropriate couplings. In D-JRA2.2 co-simulation-based assessment methods were developed to compare the performance between monolithic and co-simulations. In D-JRA2.3 we aim to combine all the work done under WP JRA2 to present an integrated simulation package that can be applied to Large Scale systems. The assessment methods developed in D-JRA2.2 have been tested initially in small systems to measure the performance and identify possible flaws. How-ever, the complexity increases significantly in large scale realistic systems. This report documents the challenges faced when the systems and their models grow larger (i.e., upscaled) and how different large scale specific phenomena and issues were identified. After the identification of the challenges, the assessment methods were modified and packaged into an in-tegrated simulation environment which can be used for scaled out systems. The simulation pack-ages are provided as an addendum along with this report while their details are concisely docu-mented in this report.
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This report summarizes the work conducted within ERIGrid related to an integrated simulation environment for large-scale systems.The main goal of the JRA2 is to develop advanced simulation-based tools and methods to validate Smart Grid scenarios, configurations and applications in con-text of co-simulation. The work done in D-JRA2.1 involved assessment of specialized simulation packages for Smart Grids and to develop tools to couple these simulation packages for co-simulation. New tools and models were also developed as some of the existing tools were not sufficient enough to achieve the appropriate couplings. In D-JRA2.2 co-simulation-based assessment methods were developed to compare the performance between monolithic and co-simulations. In D-JRA2.3 we aim to combine all the work done under WP JRA2 to present an integrated simulation package that can be applied to Large Scale systems. The assessment methods developed in D-JRA2.2 have been tested initially in small systems to measure the performance and identify possible flaws. How-ever, the complexity increases significantly in large scale realistic systems. This report documents the challenges faced when the systems and their models grow larger (i.e., upscaled) and how different large scale specific phenomena and issues were identified. After the identification of the challenges, the assessment methods were modified and packaged into an in-tegrated simulation environment which can be used for scaled out systems. The simulation pack-ages are provided as an addendum along with this report while their details are concisely docu-mented in this report.
The complexity of energy systems increases as more renewable generation and energy storage technologies are added to the grid. Diverse energy carriers are becoming interconnected and the grids are getting reliant on communication networks for timely operation. The arising complexity is difficult to model with the existing mathematical models and using existing simulation tools due to confinement of these models and tools to a subset of the interconnected system. To overcome this challenge, combined simulation (co-simulation) methodology is being deployed. In co-simulation, multiple models and tools are being interconnected to truthfully represent reality. In this work, we review several aspects of co-simulation. First, we look at interconnecting transmission and distribution grid simulations in order to enable collaboration between transmission system operators (TSOs) and distribution system operators (DSOs). Next, we investigate co-simulation as means to dynamic model exchange between TSOs. Finally, we analyze co-simulation capabilities for running experiments in remotely connected research labs.
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The complexity of energy systems increases as more renewable generation and energy storage technologies are added to the grid. Diverse energy carriers are becoming interconnected and the grids are getting reliant on communication networks for timely operation. The arising complexity is difficult to model with the existing mathematical models and using existing simulation tools due to confinement of these models and tools to a subset of the interconnected system. To overcome this challenge, combined simulation (co-simulation) methodology is being deployed. In co-simulation, multiple models and tools are being interconnected to truthfully represent reality. In this work, we review several aspects of co-simulation. First, we look at interconnecting transmission and distribution grid simulations in order to enable collaboration between transmission system operators (TSOs) and distribution system operators (DSOs). Next, we investigate co-simulation as means to dynamic model exchange between TSOs. Finally, we analyze co-simulation capabilities for running experiments in remotely connected research labs.
Conference paper
(2019)
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Arjen van der Meer, Rishabh Bhandia, Edmund Widl, Kai Heussen, Cornelius Steinbrink, P. Chodura, Thomas I. Strasser, Peter Palensky
Due to the increased deployment of renewable energy sources and intelligent components the electric power system will exhibit a large degree of heterogeneity, which requires inclusive and multi-disciplinary system assessment. The concept of co-simulation is a very attractive option to achieve this; each domain-specific subsystem can be addressed via its own specialized simulation tool. The applicability, however, depends on aspects like standardised interfaces, automated case creation, initialisation, and the scalability of the co-simulation itself. This work deals with the inclusion of the Functional Mock-up Interface for co-simulation into the DIgSILENT PowerFactory simulator, and tests its accuracy, implementation, and scalability for the grid connection study of a wind power plant. The coupling between the RMS mode of PowerFactory and MATLAB/Simulink in a standardised manner is shown. This approach allows a straightforward inclusion of black-boxed modelling, is easily scalable in size, quantity, and component type.
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Due to the increased deployment of renewable energy sources and intelligent components the electric power system will exhibit a large degree of heterogeneity, which requires inclusive and multi-disciplinary system assessment. The concept of co-simulation is a very attractive option to achieve this; each domain-specific subsystem can be addressed via its own specialized simulation tool. The applicability, however, depends on aspects like standardised interfaces, automated case creation, initialisation, and the scalability of the co-simulation itself. This work deals with the inclusion of the Functional Mock-up Interface for co-simulation into the DIgSILENT PowerFactory simulator, and tests its accuracy, implementation, and scalability for the grid connection study of a wind power plant. The coupling between the RMS mode of PowerFactory and MATLAB/Simulink in a standardised manner is shown. This approach allows a straightforward inclusion of black-boxed modelling, is easily scalable in size, quantity, and component type.
Conference paper
(2019)
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Nakisa Farrokhseresht, Arjen van der Meer, J.R. Torres, Mart van der Meijden, Peter Palensky
The massive integration of wind power plants into the transmission system calls for a careful scrutinization of their dynamic behaviour and the interactions with the power system in the transient stability time-frame of interest. This paper presents a sensitivity analysis based approach to investigate the impact of full converter wind turbine generators on the transient stability of the interconnected power system. A combination of different fault ride through and voltage support mechanisms such as 1) low voltage ride through, 2) voltage-dependent reactive power injection, 3) current limitation strategy during grid faults, and 4) the application of inertia emulation capability are considered for the sensitivity analysis. Critical clearing times are used as the transient stability indicator. The implementation of the wind turbine models are according to IEC 61400-27-1 and the assessment is done through time domain simulations using DIgSILENT PowerFactory. The results on a modified version of the IEEE 9-bus system show that by more effective use of the existing controllers of wind turbines, the share of wind power plants can be increased substantially.
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The massive integration of wind power plants into the transmission system calls for a careful scrutinization of their dynamic behaviour and the interactions with the power system in the transient stability time-frame of interest. This paper presents a sensitivity analysis based approach to investigate the impact of full converter wind turbine generators on the transient stability of the interconnected power system. A combination of different fault ride through and voltage support mechanisms such as 1) low voltage ride through, 2) voltage-dependent reactive power injection, 3) current limitation strategy during grid faults, and 4) the application of inertia emulation capability are considered for the sensitivity analysis. Critical clearing times are used as the transient stability indicator. The implementation of the wind turbine models are according to IEC 61400-27-1 and the assessment is done through time domain simulations using DIgSILENT PowerFactory. The results on a modified version of the IEEE 9-bus system show that by more effective use of the existing controllers of wind turbines, the share of wind power plants can be increased substantially.
Smart grid co-simulation with MOSAIK and HLA
A comparison study
Journal article
(2018)
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C. Steinbrink, A.A. van der Meer, M. Cvetkovic, D. Babazadeh, S. Rohjans, P. Palensky, S. Lehnhoff
Evaluating new technological developments for energy systems is becoming more and more complex. The overall application environment is a continuously growing and interconnected cyber-physical system so that analytical assessment is practically impossible to realize. Consequently, new solutions must be evaluated in simulation studies. Due to the interdisciplinarity of the simulation scenarios, various heterogeneous tools must be connected. This approach is known as co-simulation. During the last years, different approaches have been developed or adapted for applications in energy systems. In this paper, two co-simulation approaches are compared that follow generic, versatile concepts. The tool mosaik, which has been explicitly developed for the purpose of co-simulation in complex energy systems, is compared to the High Level Architecture (HLA), which possesses a domain-independent scope but is often employed in the energy domain. The comparison is twofold, considering the tools’ conceptual architectures as well as results from the simulation of representative test cases. It suggests that mosaik may be the better choice for entry-level, prototypical co-simulation while HLA is more suited for complex and extensive studies.
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Evaluating new technological developments for energy systems is becoming more and more complex. The overall application environment is a continuously growing and interconnected cyber-physical system so that analytical assessment is practically impossible to realize. Consequently, new solutions must be evaluated in simulation studies. Due to the interdisciplinarity of the simulation scenarios, various heterogeneous tools must be connected. This approach is known as co-simulation. During the last years, different approaches have been developed or adapted for applications in energy systems. In this paper, two co-simulation approaches are compared that follow generic, versatile concepts. The tool mosaik, which has been explicitly developed for the purpose of co-simulation in complex energy systems, is compared to the High Level Architecture (HLA), which possesses a domain-independent scope but is often employed in the energy domain. The comparison is twofold, considering the tools’ conceptual architectures as well as results from the simulation of representative test cases. It suggests that mosaik may be the better choice for entry-level, prototypical co-simulation while HLA is more suited for complex and extensive studies.
Journal article
(2018)
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Thomas I. Strasser, F. Pröstl Andrén, E. C.W. De Jong, J. E. Rodriguez, A. van der Meer, R. Bhandia, G. Arnold, Q. T. Tran, V. H. Nguyen, More authors...
A driving force for the realization of a sustainable energy supply in Europe is the integration of distributed, renewable energy resources. Due to their dynamic and stochastic generation behaviour, utilities and network operators are confronted with a more complex operation of the underlying distribution grids. Additionally, due to the higher flexibility on the consumer side through partly controllable loads, ongoing changes of regulatory rules, technology developments, and the liberalization of energy markets, the system’s operation needs adaptation. Sophisticated design approaches together with proper operational concepts and intelligent automation provide the basis to turn the existing power system into an intelligent entity, a so-called smart grid. While reaping the benefits that come along with those intelligent behaviours, it is expected that the system-level testing will play a significantly larger role in the development of future solutions and technologies. Proper validation approaches, concepts, and corresponding tools are partly missing until now. This paper addresses these issues by discussing the progress in the integrated Pan-European research infrastructure project ERIGrid where proper validation methods and tools are currently being developed for validating smart grid systems and solutions.
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A driving force for the realization of a sustainable energy supply in Europe is the integration of distributed, renewable energy resources. Due to their dynamic and stochastic generation behaviour, utilities and network operators are confronted with a more complex operation of the underlying distribution grids. Additionally, due to the higher flexibility on the consumer side through partly controllable loads, ongoing changes of regulatory rules, technology developments, and the liberalization of energy markets, the system’s operation needs adaptation. Sophisticated design approaches together with proper operational concepts and intelligent automation provide the basis to turn the existing power system into an intelligent entity, a so-called smart grid. While reaping the benefits that come along with those intelligent behaviours, it is expected that the system-level testing will play a significantly larger role in the development of future solutions and technologies. Proper validation approaches, concepts, and corresponding tools are partly missing until now. This paper addresses these issues by discussing the progress in the integrated Pan-European research infrastructure project ERIGrid where proper validation methods and tools are currently being developed for validating smart grid systems and solutions.
Conference paper
(2018)
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Arjen A. van der Meer, Cornelius Steinbrink, Kai Heussen, Daniel E. Morales Bondy, Merkebu Z. Degefa, Filip Pröstl Andrén, Thomas I. Strasser, Sebastian Lehnhoff, Peter Palensky
The complex and often safety-critical nature of cyber-physical energy systems makes validation a key challenge in facilitating the energy transition, especially when it comes to the testing on system level. Reliable and reproducible validation experiments can be guided by the concept of design of experiments, which is, however, so far not fully adopted by researchers. This paper suggests a structured guideline for design of experiments application within the holistic testing procedure suggested by the European ERIGrid project. In this paper, a general workflow as well as a practical example are provided with the aim to give domain experts a basic understanding of design of experiments compliant testing.
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The complex and often safety-critical nature of cyber-physical energy systems makes validation a key challenge in facilitating the energy transition, especially when it comes to the testing on system level. Reliable and reproducible validation experiments can be guided by the concept of design of experiments, which is, however, so far not fully adopted by researchers. This paper suggests a structured guideline for design of experiments application within the holistic testing procedure suggested by the European ERIGrid project. In this paper, a general workflow as well as a practical example are provided with the aim to give domain experts a basic understanding of design of experiments compliant testing.
Conference paper
(2017)
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A.D. Perilla Guerra, J.L. Rueda Torres, A.A. van der Meer, M.A.M.M. van der Meijden
This paper presents a frequency stability analysis of two power systems coupled by a high-voltage direct current (HVDC) system, based on modular multilevel converter (MMC) technology. The effect of the active power gradient (APG) control scheme attached to MMC on the long-term frequency response (time frame of 1 s to 2 min) of the AC synchronous areas is analyzed by considering a typical disturbance like a load shedding, which helps in clearly observing the frequency deviation produced in the power systems considered. The frequency
responses are assessed through deterministic software experiments in the time domain, focusing on 1) power systems with similar and different inertias and 2) the effect of varying the APG of the MMC-HVDC system. The simulation results reveal a correlation between APG and the long term frequency response, which becomes more prominent for low-inertia systems. ...
responses are assessed through deterministic software experiments in the time domain, focusing on 1) power systems with similar and different inertias and 2) the effect of varying the APG of the MMC-HVDC system. The simulation results reveal a correlation between APG and the long term frequency response, which becomes more prominent for low-inertia systems. ...
This paper presents a frequency stability analysis of two power systems coupled by a high-voltage direct current (HVDC) system, based on modular multilevel converter (MMC) technology. The effect of the active power gradient (APG) control scheme attached to MMC on the long-term frequency response (time frame of 1 s to 2 min) of the AC synchronous areas is analyzed by considering a typical disturbance like a load shedding, which helps in clearly observing the frequency deviation produced in the power systems considered. The frequency
responses are assessed through deterministic software experiments in the time domain, focusing on 1) power systems with similar and different inertias and 2) the effect of varying the APG of the MMC-HVDC system. The simulation results reveal a correlation between APG and the long term frequency response, which becomes more prominent for low-inertia systems.
responses are assessed through deterministic software experiments in the time domain, focusing on 1) power systems with similar and different inertias and 2) the effect of varying the APG of the MMC-HVDC system. The simulation results reveal a correlation between APG and the long term frequency response, which becomes more prominent for low-inertia systems.
Conference paper
(2017)
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Claudio David López, Arjen A. van der Meer, Miloš Cvetković, Peter Palensky
The unprecedented complexity of modern power systems has created a need for analyzing the interactions between different power system areas, which requires detailed physical models of all involved grids. However, a single institution seldom has access to enough information to build a complete model of a multi-area system. Additionally, such a model would be too labor-intensive to build and too computationally expensive to simulate. Co-simulation is an alternative that allows different institutions (TSOs, DSOs, research institutes, etc.) to simulate cooperatively by interconnecting their simulation tools, without having to disclose their grid models, and while sharing both the burden of model development and the computational load of the co-simulation. We present a co-simulation environment designed for researching the variable-rate (variable time step size) synchronization methods needed in a multi-institution setting. The environment can couple an arbitrary number of instances of DIgSILENT PowerFactory running on different virtual servers, at different rates, each representing a different area. An example use case with a three area system illustrates some of the main features of this environment. Errors bellow 5 % are evidence that this type of co-simulation is feasible, but long execution times point to additional challenges.
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The unprecedented complexity of modern power systems has created a need for analyzing the interactions between different power system areas, which requires detailed physical models of all involved grids. However, a single institution seldom has access to enough information to build a complete model of a multi-area system. Additionally, such a model would be too labor-intensive to build and too computationally expensive to simulate. Co-simulation is an alternative that allows different institutions (TSOs, DSOs, research institutes, etc.) to simulate cooperatively by interconnecting their simulation tools, without having to disclose their grid models, and while sharing both the burden of model development and the computational load of the co-simulation. We present a co-simulation environment designed for researching the variable-rate (variable time step size) synchronization methods needed in a multi-institution setting. The environment can couple an arbitrary number of instances of DIgSILENT PowerFactory running on different virtual servers, at different rates, each representing a different area. An example use case with a three area system illustrates some of the main features of this environment. Errors bellow 5 % are evidence that this type of co-simulation is feasible, but long execution times point to additional challenges.
Applied Cosimulation of Intelligent Power Systems
Implementing Hybrid Simulators for Complex Power Systems
Journal article
(2017)
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Peter Palensky, Arjen A. Van Der Meer, Claudio David López, Arun Joseph, Kaikai Pan
Smart grids link various types of energy technologies, such as power electronics, machines, grids, and markets, via communication technology, which leads to transdisciplinary, multidomain systems. Simulation packages for assessing the system integration of components typically cover only one subdomain, while greatly simplifying the others. Cosimulation overcomes this by coupling subdomain models that are described and solved within their native environments, using specialized solvers and validated libraries. This article discusses the state of the art and conceptually describes the main challenges for simulating intelligent power systems. The article "Cosimulation of Intelligent Power Systems: Fundamentals, Software Architecture, Numerics, and Coupling," published in the March 2017 issue of this magazine [88], covered the fundamental concepts of this topic, and this follow-up article covers the applied aspects of the subject.
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Smart grids link various types of energy technologies, such as power electronics, machines, grids, and markets, via communication technology, which leads to transdisciplinary, multidomain systems. Simulation packages for assessing the system integration of components typically cover only one subdomain, while greatly simplifying the others. Cosimulation overcomes this by coupling subdomain models that are described and solved within their native environments, using specialized solvers and validated libraries. This article discusses the state of the art and conceptually describes the main challenges for simulating intelligent power systems. The article "Cosimulation of Intelligent Power Systems: Fundamentals, Software Architecture, Numerics, and Coupling," published in the March 2017 issue of this magazine [88], covered the fundamental concepts of this topic, and this follow-up article covers the applied aspects of the subject.
Report
(2017)
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Edmund Widl, Michael Spiegel, D. E. Morales Bondy, C Steinbrink, M. Blank, A. Stathakis, T. Sarris, Panos Kotsampopoulos, N. Akroud, I. O. Sagarduy, V. H. Nguyen, D. Moneta, Cyndi Moyo, C. Sandroni, S. Corti, S. Uski, L. Matti, P. Chodura, R. Brandl, Q. T. Tran, B. Lazpita, T. Delaplagne, Thomas Strasser, Arjen van der Meer, Peter Palensky, Rishabh Bhandia, A. Emhemed, M. Syed, Oliver Gehrke
Work package JRA2 focuses on the development of advanced simulation-based methods to checkand validate smart grid scenarios, configurations and corresponding applications. The main aim isto employ offline simulation of scenarios where a combination of parallel processing, advanced optimization techniques, and design-of-experiments is used to master the system complexity. Secondary targets include the development of methods for HIL application as well as for the assessment of cyber-security concepts. This assessment will cover the following smart grid properties:system stability, system scalability, component interoperability, and information security. Eventuallyit is the goal to explore the operational limits and the sensitivity of these system properties towardssystem parameters.
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Work package JRA2 focuses on the development of advanced simulation-based methods to checkand validate smart grid scenarios, configurations and corresponding applications. The main aim isto employ offline simulation of scenarios where a combination of parallel processing, advanced optimization techniques, and design-of-experiments is used to master the system complexity. Secondary targets include the development of methods for HIL application as well as for the assessment of cyber-security concepts. This assessment will cover the following smart grid properties:system stability, system scalability, component interoperability, and information security. Eventuallyit is the goal to explore the operational limits and the sensitivity of these system properties towardssystem parameters.
Cosimulation of Intelligent Power Systems
Fundamentals, Software Architecture, Numerics, and Coupling
Smart grids link various types of energy technologies-such as power electronics, machines, grids, and markets-via communication technology, which leads to a transdisciplinary, multidomain system. Simulation packages for assessing system integration of components typically cover only one subdomain, while simplifying the others. Cosimulation overcomes this by coupling subdomain models that are described and solved within their native environments, using specialized solvers and validated libraries. This article discusses the state of the art and conceptually describes the main challenges for simulating intelligent power systems. This article, part 1 of 2 on this subject, covers fundamental concepts. Part 2 will appear in a future issue of IEEE Electrification Magazine and cover applications.
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Smart grids link various types of energy technologies-such as power electronics, machines, grids, and markets-via communication technology, which leads to a transdisciplinary, multidomain system. Simulation packages for assessing system integration of components typically cover only one subdomain, while simplifying the others. Cosimulation overcomes this by coupling subdomain models that are described and solved within their native environments, using specialized solvers and validated libraries. This article discusses the state of the art and conceptually describes the main challenges for simulating intelligent power systems. This article, part 1 of 2 on this subject, covers fundamental concepts. Part 2 will appear in a future issue of IEEE Electrification Magazine and cover applications.
Conference paper
(2017)
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V. H. Nguyen, Y. Besanger, E. Guillo-Sansano, Georg Lauss, Thomas Strasser, K. Heussen, Q. T. Tran, T.L. Nguyen, C. Boudinet, R. Brandl, F. Marten, A. Markou, Panos Kotsampopoulos, Arjen van der Meer
Conference paper
(2017)
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A.A. van der Meer, P. Palensky, T.I. Strasser, V. H. Nguyen, N. Akroud, M.H. Syed, A. Emhemed, S. Rohjans, R. Brandl, A.M. Khavari, K. Heussen, D.E. Morales Bondy, O. Gehrke, C. Steinbrink, M. Blank, S. Lehnhoff, E. Widl, C. Moyo
The gradual deployment of intelligent and coordinated devices in the electrical power system needs careful investigation of the interactions between the various domains involved. Especially due to the coupling between ICT and power systems a holistic approach for testing and validating is required. Taking existing (quasi-) standardised smart grid system and test specification methods as a starting point, we are developing a holistic testing and validation approach that allows a very flexible way of assessing the system level aspects by various types of experiments (including virtual, real, and mixed lab settings). This paper describes the formal holistic test case specification method and applies it to a particular co-simulation experimental setup. The various building blocks of such a simulation (i.e., FMI, mosaik, domain-specific simulation federates) are covered in more detail. The presented method addresses most modeling and specification challenges in cyber-physical energy systems and is extensible for future additions such as uncertainty quantification.
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The gradual deployment of intelligent and coordinated devices in the electrical power system needs careful investigation of the interactions between the various domains involved. Especially due to the coupling between ICT and power systems a holistic approach for testing and validating is required. Taking existing (quasi-) standardised smart grid system and test specification methods as a starting point, we are developing a holistic testing and validation approach that allows a very flexible way of assessing the system level aspects by various types of experiments (including virtual, real, and mixed lab settings). This paper describes the formal holistic test case specification method and applies it to a particular co-simulation experimental setup. The various building blocks of such a simulation (i.e., FMI, mosaik, domain-specific simulation federates) are covered in more detail. The presented method addresses most modeling and specification challenges in cyber-physical energy systems and is extensible for future additions such as uncertainty quantification.