SE4SG '13: "MODAM: A MODular Agent-Based ..."
MODAM: A MODular Agent-Based Modelling Framework
Fanny Boulaire, Mark Utting, and Robin Drogemuller
(QUT, Australia)
Designing the smart grid requires combining varied models. As their number increases, so does the complexity of the software. Having a well thought architecture for the software then becomes crucial. This paper presents MODAM, a framework designed to combine agent-based models in a flexible and extensible manner, using well known software engineering design solutions (OSGI specification [1] and Eclipse plugins [2]). Details on how to build a modular agent-based model for the smart grid are given in this paper, illustrated by an example for a small network.
@InProceedings{SE4SG13p33,
author = {Fanny Boulaire and Mark Utting and Robin Drogemuller},
title = {MODAM: A MODular Agent-Based Modelling Framework},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {33--40},
doi = {},
year = {2013},
}
SE4SG '13: "Towards a Bottom-Up Development ..."
Towards a Bottom-Up Development of Reference Architectures for Smart Energy Systems
Maximilian Irlbeck, Denis Bytschkow, Georg Hackenberg, and Vasileios Koutsoumpas
(TU Munich, Germany; fortiss, Germany)
Smart energy systems seem a promising choice for countries worldwide to realign their power systems to the challenges predicted for the next decades. With the will to participate in this class of systems, many solution providers design custom systems, which sometimes consist of similar parts, but are on the contrary hard to compare to each other. However, a reference describing existing commonalities is needed as a basis for many activities such as regulation design, legislation, national discussion or standardization. This paper illustrates the challenges connected with the creation of reference architectures for smart energy systems, delineates their benefits and suggests a model and method for their incremental, bottom-up development and validation through concrete system architectures.
@InProceedings{SE4SG13p9,
author = {Maximilian Irlbeck and Denis Bytschkow and Georg Hackenberg and Vasileios Koutsoumpas},
title = {Towards a Bottom-Up Development of Reference Architectures for Smart Energy Systems},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {9--16},
doi = {},
year = {2013},
}
SE4SG '13: "Residential Electrical Demand ..."
Residential Electrical Demand Forecasting in Very Small Scale: An Evaluation of Forecasting Methods
Andrei Marinescu, Colin Harris, Ivana Dusparic, Siobhán Clarke, and Vinny Cahill
(Trinity College Dublin, Ireland)
Applications such as generator scheduling, household smart device scheduling, transmission line overload management and microgrid islanding autonomy all play key roles in the smart grid ecosystem. Management of these applications could benefit from short-term load prediction, which has been successfully achieved on large-scale systems such as national grids. However, the scale of the data for analysis is much smaller, similar to the load of a single transformer, making prediction difficult. This paper examines several prediction approaches for day and week ahead electrical load of a community of houses that are supplied by a common residential transformer, in particular: artificial neural networks; fuzzy logic; auto-regression; autoregressive moving average; auto-regressive integrated moving average; and wavelet neural networks. In our evaluation, the methods use pre-recorded electrical load data with added weather information. Data is recorded from a smart-meter trial that took place during 2009-2010 in Ireland, which registered individual household consumption for 17 months. Two different scenarios are investigated, one with 90 houses, and another with 230 houses. Results for the two scenarios are compared and the performances of the evaluated prediction methods are discussed.
@InProceedings{SE4SG13p25,
author = {Andrei Marinescu and Colin Harris and Ivana Dusparic and Siobhán Clarke and Vinny Cahill},
title = {Residential Electrical Demand Forecasting in Very Small Scale: An Evaluation of Forecasting Methods},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {25--32},
doi = {},
year = {2013},
}
SE4SG '13: "A Run-Time Verification Framework ..."
A Run-Time Verification Framework for Smart Grid Applications Implemented on Simulation Frameworks
Selim Ciraci, Hasan Sözer, and Bedir Tekinerdogan
(Pacific Northwest National Laboratory, USA; Özyeğin University, Turkey; Bilkent University, Turkey)
Smart grid applications are implemented and tested with simulation frameworks as the developers usually do not have access to large sensor networks to be used as a test bed. The developers are forced to map the implementation onto these frameworks which results in a deviation between the architecture and the code. On its turn this deviation makes it hard to verify behavioral constraints that are described at the architectural level. We have developed the ConArch toolset to support the automated verification of architecture-level behavioral constraints. A key feature of ConArch is programmable mapping for architecture to the implementation. Here, developers implement queries to identify the points in the target program that correspond to architectural interactions. ConArch generates runtime observers that monitor the flow of execution between these points and verifies whether this flow conforms to the behavioral constraints. We illustrate how the programmable mappings can be exploited for verifying behavioral constraints of a smart grid application that is implemented with two simulation frameworks.
@InProceedings{SE4SG13p1,
author = {Selim Ciraci and Hasan Sözer and Bedir Tekinerdogan},
title = {A Run-Time Verification Framework for Smart Grid Applications Implemented on Simulation Frameworks},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {1--8},
doi = {},
year = {2013},
}
SE4SG '13: "Residential Electrical Demand ..."
Residential Electrical Demand Forecasting in Very Small Scale: An Evaluation of Forecasting Methods
Andrei Marinescu, Colin Harris, Ivana Dusparic, Siobhán Clarke, and Vinny Cahill
(Trinity College Dublin, Ireland)
Applications such as generator scheduling, household smart device scheduling, transmission line overload management and microgrid islanding autonomy all play key roles in the smart grid ecosystem. Management of these applications could benefit from short-term load prediction, which has been successfully achieved on large-scale systems such as national grids. However, the scale of the data for analysis is much smaller, similar to the load of a single transformer, making prediction difficult. This paper examines several prediction approaches for day and week ahead electrical load of a community of houses that are supplied by a common residential transformer, in particular: artificial neural networks; fuzzy logic; auto-regression; autoregressive moving average; auto-regressive integrated moving average; and wavelet neural networks. In our evaluation, the methods use pre-recorded electrical load data with added weather information. Data is recorded from a smart-meter trial that took place during 2009-2010 in Ireland, which registered individual household consumption for 17 months. Two different scenarios are investigated, one with 90 houses, and another with 230 houses. Results for the two scenarios are compared and the performances of the evaluated prediction methods are discussed.
@InProceedings{SE4SG13p25,
author = {Andrei Marinescu and Colin Harris and Ivana Dusparic and Siobhán Clarke and Vinny Cahill},
title = {Residential Electrical Demand Forecasting in Very Small Scale: An Evaluation of Forecasting Methods},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {25--32},
doi = {},
year = {2013},
}
SE4SG '13: "MODAM: A MODular Agent-Based ..."
MODAM: A MODular Agent-Based Modelling Framework
Fanny Boulaire, Mark Utting, and Robin Drogemuller
(QUT, Australia)
Designing the smart grid requires combining varied models. As their number increases, so does the complexity of the software. Having a well thought architecture for the software then becomes crucial. This paper presents MODAM, a framework designed to combine agent-based models in a flexible and extensible manner, using well known software engineering design solutions (OSGI specification [1] and Eclipse plugins [2]). Details on how to build a modular agent-based model for the smart grid are given in this paper, illustrated by an example for a small network.
@InProceedings{SE4SG13p33,
author = {Fanny Boulaire and Mark Utting and Robin Drogemuller},
title = {MODAM: A MODular Agent-Based Modelling Framework},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {33--40},
doi = {},
year = {2013},
}
SE4SG '13: "Residential Electrical Demand ..."
Residential Electrical Demand Forecasting in Very Small Scale: An Evaluation of Forecasting Methods
Andrei Marinescu, Colin Harris, Ivana Dusparic, Siobhán Clarke, and Vinny Cahill
(Trinity College Dublin, Ireland)
Applications such as generator scheduling, household smart device scheduling, transmission line overload management and microgrid islanding autonomy all play key roles in the smart grid ecosystem. Management of these applications could benefit from short-term load prediction, which has been successfully achieved on large-scale systems such as national grids. However, the scale of the data for analysis is much smaller, similar to the load of a single transformer, making prediction difficult. This paper examines several prediction approaches for day and week ahead electrical load of a community of houses that are supplied by a common residential transformer, in particular: artificial neural networks; fuzzy logic; auto-regression; autoregressive moving average; auto-regressive integrated moving average; and wavelet neural networks. In our evaluation, the methods use pre-recorded electrical load data with added weather information. Data is recorded from a smart-meter trial that took place during 2009-2010 in Ireland, which registered individual household consumption for 17 months. Two different scenarios are investigated, one with 90 houses, and another with 230 houses. Results for the two scenarios are compared and the performances of the evaluated prediction methods are discussed.
@InProceedings{SE4SG13p25,
author = {Andrei Marinescu and Colin Harris and Ivana Dusparic and Siobhán Clarke and Vinny Cahill},
title = {Residential Electrical Demand Forecasting in Very Small Scale: An Evaluation of Forecasting Methods},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {25--32},
doi = {},
year = {2013},
}
SE4SG '13: "Towards a Constraint Based ..."
Towards a Constraint Based Approach for Self-Healing Smart Grids
Vasileios Koutsoumpas and Pragya K. Gupta
(TU Munich, Germany; fortiss, Germany)
One of the most important functional requirements of an electrical grid is the balance between consumption and production of power and due to the centralized structure of grids, this balance is currently achieved through central power generation. However, the increased usage of decentralized renewable energy sources in combination with the Information and Communication Technology (ICT) applied to the grid tends to result in a global reformation of the current electrical grid. During this reformation new features will occur such as the handling of bidirectional energy flows, automatic fault detection, self-healing of the network, demand-side management, load adjustment, smart sensing and measurement to name only a few. Due to the increased complexity associated with the requirements of this features there is a high need for capturing, modeling, specifying and formalizing them. Thus, predicate logic plays a significant role for the logical specification of system behavior. This paper provides an insight into the current- and future grid. A 3-tier architecture is introduced specialized on the aspects of a smart grid. A show case demonstrates how this architecture assist us by understanding the reformation process of the basic electrical grid to a cellular smart grid. Thus, we introduce the concept of cellular composition and decomposition. For the formalization of the above concepts we propose a constraint based engineering method based on FOCUS theory which also aims to assist engineers from multiple disciplines during the entire phase of reformation. Finally we apply the method to describe Self-Healing Smart Grids and present a model for fault-detection and restoration.
@InProceedings{SE4SG13p17,
author = {Vasileios Koutsoumpas and Pragya K. Gupta},
title = {Towards a Constraint Based Approach for Self-Healing Smart Grids},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {17--24},
doi = {},
year = {2013},
}
SE4SG '13: "Towards a Bottom-Up Development ..."
Towards a Bottom-Up Development of Reference Architectures for Smart Energy Systems
Maximilian Irlbeck, Denis Bytschkow, Georg Hackenberg, and Vasileios Koutsoumpas
(TU Munich, Germany; fortiss, Germany)
Smart energy systems seem a promising choice for countries worldwide to realign their power systems to the challenges predicted for the next decades. With the will to participate in this class of systems, many solution providers design custom systems, which sometimes consist of similar parts, but are on the contrary hard to compare to each other. However, a reference describing existing commonalities is needed as a basis for many activities such as regulation design, legislation, national discussion or standardization. This paper illustrates the challenges connected with the creation of reference architectures for smart energy systems, delineates their benefits and suggests a model and method for their incremental, bottom-up development and validation through concrete system architectures.
@InProceedings{SE4SG13p9,
author = {Maximilian Irlbeck and Denis Bytschkow and Georg Hackenberg and Vasileios Koutsoumpas},
title = {Towards a Bottom-Up Development of Reference Architectures for Smart Energy Systems},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {9--16},
doi = {},
year = {2013},
}
SE4SG '13: "Residential Electrical Demand ..."
Residential Electrical Demand Forecasting in Very Small Scale: An Evaluation of Forecasting Methods
Andrei Marinescu, Colin Harris, Ivana Dusparic, Siobhán Clarke, and Vinny Cahill
(Trinity College Dublin, Ireland)
Applications such as generator scheduling, household smart device scheduling, transmission line overload management and microgrid islanding autonomy all play key roles in the smart grid ecosystem. Management of these applications could benefit from short-term load prediction, which has been successfully achieved on large-scale systems such as national grids. However, the scale of the data for analysis is much smaller, similar to the load of a single transformer, making prediction difficult. This paper examines several prediction approaches for day and week ahead electrical load of a community of houses that are supplied by a common residential transformer, in particular: artificial neural networks; fuzzy logic; auto-regression; autoregressive moving average; auto-regressive integrated moving average; and wavelet neural networks. In our evaluation, the methods use pre-recorded electrical load data with added weather information. Data is recorded from a smart-meter trial that took place during 2009-2010 in Ireland, which registered individual household consumption for 17 months. Two different scenarios are investigated, one with 90 houses, and another with 230 houses. Results for the two scenarios are compared and the performances of the evaluated prediction methods are discussed.
@InProceedings{SE4SG13p25,
author = {Andrei Marinescu and Colin Harris and Ivana Dusparic and Siobhán Clarke and Vinny Cahill},
title = {Residential Electrical Demand Forecasting in Very Small Scale: An Evaluation of Forecasting Methods},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {25--32},
doi = {},
year = {2013},
}
SE4SG '13: "Towards a Bottom-Up Development ..."
Towards a Bottom-Up Development of Reference Architectures for Smart Energy Systems
Maximilian Irlbeck, Denis Bytschkow, Georg Hackenberg, and Vasileios Koutsoumpas
(TU Munich, Germany; fortiss, Germany)
Smart energy systems seem a promising choice for countries worldwide to realign their power systems to the challenges predicted for the next decades. With the will to participate in this class of systems, many solution providers design custom systems, which sometimes consist of similar parts, but are on the contrary hard to compare to each other. However, a reference describing existing commonalities is needed as a basis for many activities such as regulation design, legislation, national discussion or standardization. This paper illustrates the challenges connected with the creation of reference architectures for smart energy systems, delineates their benefits and suggests a model and method for their incremental, bottom-up development and validation through concrete system architectures.
@InProceedings{SE4SG13p9,
author = {Maximilian Irlbeck and Denis Bytschkow and Georg Hackenberg and Vasileios Koutsoumpas},
title = {Towards a Bottom-Up Development of Reference Architectures for Smart Energy Systems},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {9--16},
doi = {},
year = {2013},
}
SE4SG '13: "Towards a Constraint Based ..."
Towards a Constraint Based Approach for Self-Healing Smart Grids
Vasileios Koutsoumpas and Pragya K. Gupta
(TU Munich, Germany; fortiss, Germany)
One of the most important functional requirements of an electrical grid is the balance between consumption and production of power and due to the centralized structure of grids, this balance is currently achieved through central power generation. However, the increased usage of decentralized renewable energy sources in combination with the Information and Communication Technology (ICT) applied to the grid tends to result in a global reformation of the current electrical grid. During this reformation new features will occur such as the handling of bidirectional energy flows, automatic fault detection, self-healing of the network, demand-side management, load adjustment, smart sensing and measurement to name only a few. Due to the increased complexity associated with the requirements of this features there is a high need for capturing, modeling, specifying and formalizing them. Thus, predicate logic plays a significant role for the logical specification of system behavior. This paper provides an insight into the current- and future grid. A 3-tier architecture is introduced specialized on the aspects of a smart grid. A show case demonstrates how this architecture assist us by understanding the reformation process of the basic electrical grid to a cellular smart grid. Thus, we introduce the concept of cellular composition and decomposition. For the formalization of the above concepts we propose a constraint based engineering method based on FOCUS theory which also aims to assist engineers from multiple disciplines during the entire phase of reformation. Finally we apply the method to describe Self-Healing Smart Grids and present a model for fault-detection and restoration.
@InProceedings{SE4SG13p17,
author = {Vasileios Koutsoumpas and Pragya K. Gupta},
title = {Towards a Constraint Based Approach for Self-Healing Smart Grids},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {17--24},
doi = {},
year = {2013},
}
SE4SG '13: "Towards a Bottom-Up Development ..."
Towards a Bottom-Up Development of Reference Architectures for Smart Energy Systems
Maximilian Irlbeck, Denis Bytschkow, Georg Hackenberg, and Vasileios Koutsoumpas
(TU Munich, Germany; fortiss, Germany)
Smart energy systems seem a promising choice for countries worldwide to realign their power systems to the challenges predicted for the next decades. With the will to participate in this class of systems, many solution providers design custom systems, which sometimes consist of similar parts, but are on the contrary hard to compare to each other. However, a reference describing existing commonalities is needed as a basis for many activities such as regulation design, legislation, national discussion or standardization. This paper illustrates the challenges connected with the creation of reference architectures for smart energy systems, delineates their benefits and suggests a model and method for their incremental, bottom-up development and validation through concrete system architectures.
@InProceedings{SE4SG13p9,
author = {Maximilian Irlbeck and Denis Bytschkow and Georg Hackenberg and Vasileios Koutsoumpas},
title = {Towards a Bottom-Up Development of Reference Architectures for Smart Energy Systems},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {9--16},
doi = {},
year = {2013},
}
SE4SG '13: "Residential Electrical Demand ..."
Residential Electrical Demand Forecasting in Very Small Scale: An Evaluation of Forecasting Methods
Andrei Marinescu, Colin Harris, Ivana Dusparic, Siobhán Clarke, and Vinny Cahill
(Trinity College Dublin, Ireland)
Applications such as generator scheduling, household smart device scheduling, transmission line overload management and microgrid islanding autonomy all play key roles in the smart grid ecosystem. Management of these applications could benefit from short-term load prediction, which has been successfully achieved on large-scale systems such as national grids. However, the scale of the data for analysis is much smaller, similar to the load of a single transformer, making prediction difficult. This paper examines several prediction approaches for day and week ahead electrical load of a community of houses that are supplied by a common residential transformer, in particular: artificial neural networks; fuzzy logic; auto-regression; autoregressive moving average; auto-regressive integrated moving average; and wavelet neural networks. In our evaluation, the methods use pre-recorded electrical load data with added weather information. Data is recorded from a smart-meter trial that took place during 2009-2010 in Ireland, which registered individual household consumption for 17 months. Two different scenarios are investigated, one with 90 houses, and another with 230 houses. Results for the two scenarios are compared and the performances of the evaluated prediction methods are discussed.
@InProceedings{SE4SG13p25,
author = {Andrei Marinescu and Colin Harris and Ivana Dusparic and Siobhán Clarke and Vinny Cahill},
title = {Residential Electrical Demand Forecasting in Very Small Scale: An Evaluation of Forecasting Methods},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {25--32},
doi = {},
year = {2013},
}
SE4SG '13: "A Run-Time Verification Framework ..."
A Run-Time Verification Framework for Smart Grid Applications Implemented on Simulation Frameworks
Selim Ciraci, Hasan Sözer, and Bedir Tekinerdogan
(Pacific Northwest National Laboratory, USA; Özyeğin University, Turkey; Bilkent University, Turkey)
Smart grid applications are implemented and tested with simulation frameworks as the developers usually do not have access to large sensor networks to be used as a test bed. The developers are forced to map the implementation onto these frameworks which results in a deviation between the architecture and the code. On its turn this deviation makes it hard to verify behavioral constraints that are described at the architectural level. We have developed the ConArch toolset to support the automated verification of architecture-level behavioral constraints. A key feature of ConArch is programmable mapping for architecture to the implementation. Here, developers implement queries to identify the points in the target program that correspond to architectural interactions. ConArch generates runtime observers that monitor the flow of execution between these points and verifies whether this flow conforms to the behavioral constraints. We illustrate how the programmable mappings can be exploited for verifying behavioral constraints of a smart grid application that is implemented with two simulation frameworks.
@InProceedings{SE4SG13p1,
author = {Selim Ciraci and Hasan Sözer and Bedir Tekinerdogan},
title = {A Run-Time Verification Framework for Smart Grid Applications Implemented on Simulation Frameworks},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {1--8},
doi = {},
year = {2013},
}
SE4SG '13: "A Run-Time Verification Framework ..."
A Run-Time Verification Framework for Smart Grid Applications Implemented on Simulation Frameworks
Selim Ciraci, Hasan Sözer, and Bedir Tekinerdogan
(Pacific Northwest National Laboratory, USA; Özyeğin University, Turkey; Bilkent University, Turkey)
Smart grid applications are implemented and tested with simulation frameworks as the developers usually do not have access to large sensor networks to be used as a test bed. The developers are forced to map the implementation onto these frameworks which results in a deviation between the architecture and the code. On its turn this deviation makes it hard to verify behavioral constraints that are described at the architectural level. We have developed the ConArch toolset to support the automated verification of architecture-level behavioral constraints. A key feature of ConArch is programmable mapping for architecture to the implementation. Here, developers implement queries to identify the points in the target program that correspond to architectural interactions. ConArch generates runtime observers that monitor the flow of execution between these points and verifies whether this flow conforms to the behavioral constraints. We illustrate how the programmable mappings can be exploited for verifying behavioral constraints of a smart grid application that is implemented with two simulation frameworks.
@InProceedings{SE4SG13p1,
author = {Selim Ciraci and Hasan Sözer and Bedir Tekinerdogan},
title = {A Run-Time Verification Framework for Smart Grid Applications Implemented on Simulation Frameworks},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {1--8},
doi = {},
year = {2013},
}
SE4SG '13: "MODAM: A MODular Agent-Based ..."
MODAM: A MODular Agent-Based Modelling Framework
Fanny Boulaire, Mark Utting, and Robin Drogemuller
(QUT, Australia)
Designing the smart grid requires combining varied models. As their number increases, so does the complexity of the software. Having a well thought architecture for the software then becomes crucial. This paper presents MODAM, a framework designed to combine agent-based models in a flexible and extensible manner, using well known software engineering design solutions (OSGI specification [1] and Eclipse plugins [2]). Details on how to build a modular agent-based model for the smart grid are given in this paper, illustrated by an example for a small network.
@InProceedings{SE4SG13p33,
author = {Fanny Boulaire and Mark Utting and Robin Drogemuller},
title = {MODAM: A MODular Agent-Based Modelling Framework},
booktitle = {Proc.\ SE4SG},
publisher = {IEEE},
pages = {33--40},
doi = {},
year = {2013},
}