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Mechatronics Research Lab Publications
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2020
8.
Kevin Vanslette; Abdullatif Al Alsheikh; Kamal Youcef-Toumi
Why simple quadrature is just as good as Monte Carlo Journal Article
In: Monte Carlo Methods and Applications, vol. 26, no. 1, pp. 1–16, 2020, ISSN: 1569-3961.
Abstract | Links | BibTeX | Tags: Computational Intelligence, Control Theory, Experimentation, intelligent systems, Modeling; sizing and control for smart grids, Simulation
@article{MRL_AFM_Quadrature_Monte_Carlo,
title = {Why simple quadrature is just as good as Monte Carlo},
author = {Kevin Vanslette and Abdullatif Al Alsheikh and Kamal Youcef-Toumi},
url = {http://dx.doi.org/10.1515/mcma-2020-2055},
doi = {10.1515/mcma-2020-2055},
issn = {1569-3961},
year = {2020},
date = {2020-03-01},
journal = {Monte Carlo Methods and Applications},
volume = {26},
number = {1},
pages = {1–16},
publisher = {Walter de Gruyter GmbH},
abstract = {We motive and calculate Newton–Cotes quadrature integration variance and compare it directly with Monte Carlo (MC) integration variance. We find an equivalence between deterministic quadrature sampling and random MC sampling by noting that MC random sampling is statistically indistinguishable from a method that uses deterministic sampling on a randomly shuffled (permuted) function. We use this statistical equivalence to regularize the form of permissible Bayesian quadrature integration priors such that they are guaranteed to be objectively comparable with MC. This leads to the proof that simple quadrature methods have expected variances that are less than or equal to their corresponding theoretical MC integration variances. Separately, using Bayesian probability theory, we find that the theoretical standard deviations of the unbiased errors of simple Newton–Cotes composite quadrature integrations improve over their worst case errors by an extra dimension independent factor ∝ N−1/2 This dimension independent factor is validated in our simulations.},
keywords = {Computational Intelligence, Control Theory, Experimentation, intelligent systems, Modeling; sizing and control for smart grids, Simulation},
pubstate = {published},
tppubtype = {article}
}
We motive and calculate Newton–Cotes quadrature integration variance and compare it directly with Monte Carlo (MC) integration variance. We find an equivalence between deterministic quadrature sampling and random MC sampling by noting that MC random sampling is statistically indistinguishable from a method that uses deterministic sampling on a randomly shuffled (permuted) function. We use this statistical equivalence to regularize the form of permissible Bayesian quadrature integration priors such that they are guaranteed to be objectively comparable with MC. This leads to the proof that simple quadrature methods have expected variances that are less than or equal to their corresponding theoretical MC integration variances. Separately, using Bayesian probability theory, we find that the theoretical standard deviations of the unbiased errors of simple Newton–Cotes composite quadrature integrations improve over their worst case errors by an extra dimension independent factor ∝ N−1/2 This dimension independent factor is validated in our simulations.
2016
7.
Aramazd Muzhikyan; Amro M Farid; Kamal Youcef-Toumi
Relative merits of load following reserves & energy storage market integration towards power system imbalances Journal Article
In: International Journal of Electrical Power & Energy Systems, vol. 74, pp. 222-229, 2016, ISSN: 0142-0615.
Abstract | Links | BibTeX | Tags: Control Theory, intelligent systems, Modeling; sizing and control for smart grids, Visualization
@article{MRL_Market_Integration_Power_System,
title = {Relative merits of load following reserves & energy storage market integration towards power system imbalances},
author = {Aramazd Muzhikyan and Amro M Farid and Kamal Youcef-Toumi},
url = {https://www.sciencedirect.com/science/article/pii/S0142061515002999},
doi = {https://doi.org/10.1016/j.ijepes.2015.07.013},
issn = {0142-0615},
year = {2016},
date = {2016-01-01},
journal = {International Journal of Electrical Power & Energy Systems},
volume = {74},
pages = {222-229},
publisher = {ScienceDirect},
abstract = {Traditionally, power system balancing operations consist of three consecutive control techniques, namely security-constrained unit commitment (SCUC), security-constrained economic dispatch (SCED), and automatic generation control (AGC). Each of these have their corresponding type of operating reserves. Similarly, energy storage resources (ESRs) may be integrated as energy, load following, or regulation resources. A review of the existing literature shows that most ESR integration studies are focused on a single control function. In contrast, recent work on renewable energy integration has employed the concept of enterprise control where the multiple layers of balancing operations have been integrated into a single model. This paper now uses such an enterprise control model to demonstrate the relative merits of load following reserves and energy storage integrated into the resource scheduling and balancing action layers. The results show that load following reserves and energy storage resources mitigate imbalances in fundamentally different ways. The latter becomes an increasingly effective balancing resource for high net-load variability and small day-ahead market time step.},
keywords = {Control Theory, intelligent systems, Modeling; sizing and control for smart grids, Visualization},
pubstate = {published},
tppubtype = {article}
}
Traditionally, power system balancing operations consist of three consecutive control techniques, namely security-constrained unit commitment (SCUC), security-constrained economic dispatch (SCED), and automatic generation control (AGC). Each of these have their corresponding type of operating reserves. Similarly, energy storage resources (ESRs) may be integrated as energy, load following, or regulation resources. A review of the existing literature shows that most ESR integration studies are focused on a single control function. In contrast, recent work on renewable energy integration has employed the concept of enterprise control where the multiple layers of balancing operations have been integrated into a single model. This paper now uses such an enterprise control model to demonstrate the relative merits of load following reserves and energy storage integrated into the resource scheduling and balancing action layers. The results show that load following reserves and energy storage resources mitigate imbalances in fundamentally different ways. The latter becomes an increasingly effective balancing resource for high net-load variability and small day-ahead market time step.
2015
6.
Amro M Farid; Bo Jiang; Aramazd Muzhikyan; Kamal Youcef-Toumi
The need for holistic enterprise control assessment methods for the future electricity grid Journal Article
In: Renewable and Sustainable Energy Reviews, vol. 56, pp. 669-685, 2015, ISSN: 1364-0321.
Abstract | Links | BibTeX | Tags: Algorithms, Control Theory, Experimentation, intelligent systems, Modeling; sizing and control for smart grids, Physical System Modeling, Simulation
@article{MRL_AFM_Holistic_Assessment_Electricity_Grid,
title = {The need for holistic enterprise control assessment methods for the future electricity grid},
author = {Amro M Farid and Bo Jiang and Aramazd Muzhikyan and Kamal Youcef-Toumi},
url = {https://www.sciencedirect.com/science/article/pii/S1364032115012599},
doi = {https://doi.org/10.1016/j.rser.2015.11.007},
issn = {1364-0321},
year = {2015},
date = {2015-12-17},
journal = {Renewable and Sustainable Energy Reviews},
volume = {56},
pages = {669-685},
publisher = {elsevier},
abstract = {Recently, the academic and industrial literature has coalesced around an enhanced vision of the electric power grid that is responsive, dynamic, adaptive and flexible. As driven by decarbonization, reliability, transportation electrification, consumer participation and deregulation, this future grid will undergo technical, economic and regulatory changes to bring about the incorporation of renewable energy and incentivized demand side management and control. As a result, the power grid will experience fundamental changes in its physical system structure and behavior that will consequently require enhanced and integrated control, automation, and IT-driven management functions in what is called enterprise control. While these requirements will open a plethora of opportunities for new control technologies, many of these solutions are largely overlapping in function. Their overall contribution to holistic techno-economic control objectives and their underlying dynamic properties are less than clear. Piece-meal integration and a lack of coordinated assessment could bring about costly-overbuilt solutions or even worse unintended reliability consequences. This work, thus, reviews these existing trends in the power grid evolution. It then motivates the need for holistic methods of integrated assessment that manage the diversity of control solutions against their many competing objectives and contrasts these requirements to existing variable energy resource integration studies. The work concludes with a holistic framework for “enterprise control” assessment of the future power grid and suggests directions for future work.},
keywords = {Algorithms, Control Theory, Experimentation, intelligent systems, Modeling; sizing and control for smart grids, Physical System Modeling, Simulation},
pubstate = {published},
tppubtype = {article}
}
Recently, the academic and industrial literature has coalesced around an enhanced vision of the electric power grid that is responsive, dynamic, adaptive and flexible. As driven by decarbonization, reliability, transportation electrification, consumer participation and deregulation, this future grid will undergo technical, economic and regulatory changes to bring about the incorporation of renewable energy and incentivized demand side management and control. As a result, the power grid will experience fundamental changes in its physical system structure and behavior that will consequently require enhanced and integrated control, automation, and IT-driven management functions in what is called enterprise control. While these requirements will open a plethora of opportunities for new control technologies, many of these solutions are largely overlapping in function. Their overall contribution to holistic techno-economic control objectives and their underlying dynamic properties are less than clear. Piece-meal integration and a lack of coordinated assessment could bring about costly-overbuilt solutions or even worse unintended reliability consequences. This work, thus, reviews these existing trends in the power grid evolution. It then motivates the need for holistic methods of integrated assessment that manage the diversity of control solutions against their many competing objectives and contrasts these requirements to existing variable energy resource integration studies. The work concludes with a holistic framework for “enterprise control” assessment of the future power grid and suggests directions for future work.
5.
Sabrina Titri; Cherif Larbes; Kamal Youcef-Toumi
Rapid prototyping of PVS into FPGA: From model based design to FPGA/ASICs implementation Proceedings Article
In: 2014 9th International Design and Test Symposium (IDT), pp. 162-167, IEEE IEEE, 2015, ISBN: 978-1-4799-8200-4.
Abstract | Links | BibTeX | Tags: Algorithms, intelligent systems, Modeling; sizing and control for smart grids, Physical System Modeling, Simulation
@inproceedings{MRL_SG_PVS_MPPT_Optimization,
title = {Rapid prototyping of PVS into FPGA: From model based design to FPGA/ASICs implementation},
author = {Sabrina Titri and Cherif Larbes and Kamal Youcef-Toumi},
url = {https://ieeexplore.ieee.org/document/7038606},
doi = {10.1109/IDT.2014.7038606},
isbn = {978-1-4799-8200-4},
year = {2015},
date = {2015-02-15},
booktitle = {2014 9th International Design and Test Symposium (IDT)},
pages = {162-167},
publisher = {IEEE},
organization = {IEEE},
abstract = {A wide variety of maximum power point tracking (MPPT) algorithms for photovoltaic systems (PVS) have been proposed and developed. These MPPT algorithms vary in many aspects such as the selected criteria and techniques used. In this paper, we propose an effective design methodology for hardware implementation of PVS into FPGA/ASICs. To achieve our goal, we propose the application of the model based design at high level using the Matlab/Simulink which includes the HDL Coder Tool. The approach will assist the designer to develop and prototype in a relatively short time by eliminating time consuming and error prone due to manual coding. The proposed design methodology has been applied to the well know Pertub and Observe (P&O) MPPT controller. The Matlab/Simulink model of the P&O controller is optimized and converted to target, Hardware Description Language (HDL) code for FPGA/ASIC. The whole architecture of the P&O controller has been implemented on a Xilinx Spartan 3E prototyping board. We demonstrate that the generated RTL code can be easily mapped into FPGA/ASICs, which allow the rapid prototyping of PVS with more complex algorithms.},
keywords = {Algorithms, intelligent systems, Modeling; sizing and control for smart grids, Physical System Modeling, Simulation},
pubstate = {published},
tppubtype = {inproceedings}
}
A wide variety of maximum power point tracking (MPPT) algorithms for photovoltaic systems (PVS) have been proposed and developed. These MPPT algorithms vary in many aspects such as the selected criteria and techniques used. In this paper, we propose an effective design methodology for hardware implementation of PVS into FPGA/ASICs. To achieve our goal, we propose the application of the model based design at high level using the Matlab/Simulink which includes the HDL Coder Tool. The approach will assist the designer to develop and prototype in a relatively short time by eliminating time consuming and error prone due to manual coding. The proposed design methodology has been applied to the well know Pertub and Observe (P&O) MPPT controller. The Matlab/Simulink model of the P&O controller is optimized and converted to target, Hardware Description Language (HDL) code for FPGA/ASIC. The whole architecture of the P&O controller has been implemented on a Xilinx Spartan 3E prototyping board. We demonstrate that the generated RTL code can be easily mapped into FPGA/ASICs, which allow the rapid prototyping of PVS with more complex algorithms.
2014
4.
Reshma C Francy; Amro M Farid; Kamal Youcef-Toumi
Event triggered state estimation techniques for power systems with integrated variable energy resources Journal Article
In: ISA transactions, vol. 56, pp. 165—172, 2014, ISSN: 0019-0578.
Abstract | Links | BibTeX | Tags: Control Theory, Experimentation, intelligent systems, Modeling; sizing and control for smart grids, Physical System Modeling, Simulation
@article{MRL_AFM_State_Estimation_Power,
title = {Event triggered state estimation techniques for power systems with integrated variable energy resources},
author = {Reshma C Francy and Amro M Farid and Kamal Youcef-Toumi},
url = {https://doi.org/10.1016/j.isatra.2014.11.001},
doi = {10.1016/j.isatra.2014.11.001},
issn = {0019-0578},
year = {2014},
date = {2014-11-24},
journal = {ISA transactions},
volume = {56},
pages = {165—172},
abstract = {For many decades, state estimation (SE) has been a critical technology for energy management systems utilized by power system operators. Over time, it has become a mature technology that provides an accurate representation of system state under fairly stable and well understood system operation. The integration of variable energy resources (VERs) such as wind and solar generation, however, introduces new fast frequency dynamics and uncertainties into the system. Furthermore, such renewable energy is often integrated into the distribution system thus requiring real-time monitoring all the way to the periphery of the power grid topology and not just the (central) transmission system. The conventional solution is two fold: solve the SE problem (1) at a faster rate in accordance with the newly added VER dynamics and (2) for the entire power grid topology including the transmission and distribution systems. Such an approach results in exponentially growing problem sets which need to be solver at faster rates. This work seeks to address these two simultaneous requirements and builds upon two recent SE methods which incorporate event-triggering such that the state estimator is only called in the case of considerable novelty in the evolution of the system state. The first method incorporates only event-triggering while the second adds the concept of tracking. Both SE methods are demonstrated on the standard IEEE 14-bus system and the results are observed for a specific bus for two difference scenarios: (1) a spike in the wind power injection and (2) ramp events with higher variability. Relative to traditional state estimation, the numerical case studies showed that the proposed methods can result in computational time reductions of 90. These results were supported by a theoretical discussion of the computational complexity of three SE techniques. The work concludes that the proposed SE techniques demonstrate practical improvements to the computational complexity of classical state estimation. In such a way, state estimation can continue to support the necessary control actions to mitigate the imbalances resulting from the uncertainties in renewables.},
keywords = {Control Theory, Experimentation, intelligent systems, Modeling; sizing and control for smart grids, Physical System Modeling, Simulation},
pubstate = {published},
tppubtype = {article}
}
For many decades, state estimation (SE) has been a critical technology for energy management systems utilized by power system operators. Over time, it has become a mature technology that provides an accurate representation of system state under fairly stable and well understood system operation. The integration of variable energy resources (VERs) such as wind and solar generation, however, introduces new fast frequency dynamics and uncertainties into the system. Furthermore, such renewable energy is often integrated into the distribution system thus requiring real-time monitoring all the way to the periphery of the power grid topology and not just the (central) transmission system. The conventional solution is two fold: solve the SE problem (1) at a faster rate in accordance with the newly added VER dynamics and (2) for the entire power grid topology including the transmission and distribution systems. Such an approach results in exponentially growing problem sets which need to be solver at faster rates. This work seeks to address these two simultaneous requirements and builds upon two recent SE methods which incorporate event-triggering such that the state estimator is only called in the case of considerable novelty in the evolution of the system state. The first method incorporates only event-triggering while the second adds the concept of tracking. Both SE methods are demonstrated on the standard IEEE 14-bus system and the results are observed for a specific bus for two difference scenarios: (1) a spike in the wind power injection and (2) ramp events with higher variability. Relative to traditional state estimation, the numerical case studies showed that the proposed methods can result in computational time reductions of 90. These results were supported by a theoretical discussion of the computational complexity of three SE techniques. The work concludes that the proposed SE techniques demonstrate practical improvements to the computational complexity of classical state estimation. In such a way, state estimation can continue to support the necessary control actions to mitigate the imbalances resulting from the uncertainties in renewables.
3.
William Lubega; Apoorva Santhosh; Amro M Farid; Kamal Youcef-Toumi
An Integrated Energy and Water Market for the Supply Side of the Energy-Water Nexus in the Engineered Infrastructure Proceedings Article
In: ASME 2014 Power Conference, 2014, ISBN: 978-0-7918-4609-4.
Abstract | Links | BibTeX | Tags: Algorithms, intelligent systems, Modeling; sizing and control for smart grids, Physical System Modeling, Simulation
@inproceedings{MRL_SG_Integrated_Electric_Water,
title = {An Integrated Energy and Water Market for the Supply Side of the Energy-Water Nexus in the Engineered Infrastructure},
author = {William Lubega and Apoorva Santhosh and Amro M Farid and Kamal Youcef-Toumi},
url = {https://asmedigitalcollection.asme.org/POWER/proceedings/POWER2014/46094/V002T10A003/282270},
doi = {10.1115/POWER2014-32075},
isbn = {978-0-7918-4609-4},
year = {2014},
date = {2014-11-19},
booktitle = {ASME 2014 Power Conference},
abstract = {In regions that utilize thermal desalination as part of their water supply portfolio, the cogeneration of water and power in cogeneration desalination plants couples the supply sides of the electricity and water grids. For a fixed plant design, there is a limited range of ratios of generated electric power to produced water at any given time. Due to this coupling, electricity and water require co-optimization. In an environment in which electricity supply is determined by deregulated wholesale markets, this need for co-optimization suggests a need for integrated electricity and water markets. In this market, independent power producers, independent water producers and independent cogeneration plants would submit bids to satisfy demand over a time horizon to a clearing mechanism, indicating relevant physical constraints. The mechanism would then optimize supply of both electricity and water over the time horizon of interest. Recently, a simultaneous co-optimization method has been contributed for the economic dispatch of networks that include water, power and cogeneration facilities in such an integrated market. This paper builds upon this foundation with the introduction of the corresponding unit commitment problem.},
keywords = {Algorithms, intelligent systems, Modeling; sizing and control for smart grids, Physical System Modeling, Simulation},
pubstate = {published},
tppubtype = {inproceedings}
}
In regions that utilize thermal desalination as part of their water supply portfolio, the cogeneration of water and power in cogeneration desalination plants couples the supply sides of the electricity and water grids. For a fixed plant design, there is a limited range of ratios of generated electric power to produced water at any given time. Due to this coupling, electricity and water require co-optimization. In an environment in which electricity supply is determined by deregulated wholesale markets, this need for co-optimization suggests a need for integrated electricity and water markets. In this market, independent power producers, independent water producers and independent cogeneration plants would submit bids to satisfy demand over a time horizon to a clearing mechanism, indicating relevant physical constraints. The mechanism would then optimize supply of both electricity and water over the time horizon of interest. Recently, a simultaneous co-optimization method has been contributed for the economic dispatch of networks that include water, power and cogeneration facilities in such an integrated market. This paper builds upon this foundation with the introduction of the corresponding unit commitment problem.
2.
Apoorva Santhosh; Amro M Farid; Kamal Youcef-Toumi
Optimal network flow for the supply side of the energy-water nexus Proceedings Article
In: 2013 IEEE International Workshop on Inteligent Energy Systems (IWIES), pp. 155-160, IEEE IEEE, 2014, ISBN: 978-1-4799-1135-6.
Abstract | Links | BibTeX | Tags: Algorithms, intelligent systems, Modeling; sizing and control for smart grids, Physical System Modeling, Simulation
@inproceedings{MRL_SG_Water_Plant_Sustainability,
title = {Optimal network flow for the supply side of the energy-water nexus},
author = {Apoorva Santhosh and Amro M Farid and Kamal Youcef-Toumi},
url = {https://ieeexplore.ieee.org/document/6698578},
doi = {10.1109/IWIES.2013.6698578},
isbn = {978-1-4799-1135-6},
year = {2014},
date = {2014-01-06},
booktitle = {2013 IEEE International Workshop on Inteligent Energy Systems (IWIES)},
pages = {155-160},
publisher = {IEEE},
organization = {IEEE},
abstract = {Clean energy and water are two essential resources that any society must securely deliver. Their usage raises sustainability issues and questions of nations' resilience in face of global changes and mega-trends such as population growth, global climate change, and economic growth. Recently, attention has been paid to the infrastructure systems for water distribution and power transmission and the coupling between them in what is commonly known as the energy-water nexus. Although numerous policy and regulatory agencies have addressed the subject, rarely is it holistically addressed in terms of an integrated engineering system for its management, planning, and regulation as an interdisciplinary concern. This work specifically addresses the supply side of this integrated engineering system framework. It takes as its subject the real-time optimal flows in power and water networks. Significant background literature is brought to bear on this topic including the emerging co-dispatch of power and water and the more well established optimizations for power and water networks individually. The work presents a mathematical optimization program for the co-dispatch of the two commodities for three types of plants: power generation plants, co-production facilities and water production plants. Production costs are minimized subject to capacity, demand and transmission constraints and demonstrated on an illustrative example of modest size developed from standard test cases. On a practical basis, the program can be applied directly in middle eastern countries where water and power distribution are typically under the responsibility of a single utility. Furthermore, the program provides a systematic method of achieving optimal results and can serve as a basis for set-points upon which individual plants can implement their optimal control. In so doing, it makes a supply-side contribution to the ongoing grand-challenge of improving the sustainability of the energy-water nexus.},
keywords = {Algorithms, intelligent systems, Modeling; sizing and control for smart grids, Physical System Modeling, Simulation},
pubstate = {published},
tppubtype = {inproceedings}
}
Clean energy and water are two essential resources that any society must securely deliver. Their usage raises sustainability issues and questions of nations' resilience in face of global changes and mega-trends such as population growth, global climate change, and economic growth. Recently, attention has been paid to the infrastructure systems for water distribution and power transmission and the coupling between them in what is commonly known as the energy-water nexus. Although numerous policy and regulatory agencies have addressed the subject, rarely is it holistically addressed in terms of an integrated engineering system for its management, planning, and regulation as an interdisciplinary concern. This work specifically addresses the supply side of this integrated engineering system framework. It takes as its subject the real-time optimal flows in power and water networks. Significant background literature is brought to bear on this topic including the emerging co-dispatch of power and water and the more well established optimizations for power and water networks individually. The work presents a mathematical optimization program for the co-dispatch of the two commodities for three types of plants: power generation plants, co-production facilities and water production plants. Production costs are minimized subject to capacity, demand and transmission constraints and demonstrated on an illustrative example of modest size developed from standard test cases. On a practical basis, the program can be applied directly in middle eastern countries where water and power distribution are typically under the responsibility of a single utility. Furthermore, the program provides a systematic method of achieving optimal results and can serve as a basis for set-points upon which individual plants can implement their optimal control. In so doing, it makes a supply-side contribution to the ongoing grand-challenge of improving the sustainability of the energy-water nexus.
2013
1.
Aramazd Muzhikyan; Amro M Farid; Kamal Youcef-Toumi
Variable energy resource induced power system imbalances: Mitigation by increased system flexibility, spinning reserves and regulation Proceedings Article
In: 2013 1st IEEE Conference on Technologies for Sustainability (SusTech), pp. 15-22, IEEE IEEE, 2013, ISBN: 978-1-4673-4630-6.
Abstract | Links | BibTeX | Tags: Algorithms, intelligent systems, Modeling; sizing and control for smart grids, Physical System Modeling, Simulation
@inproceedings{MRL_SG_Generalized_Reserve_Analysis,
title = {Variable energy resource induced power system imbalances: Mitigation by increased system flexibility, spinning reserves and regulation},
author = {Aramazd Muzhikyan and Amro M Farid and Kamal Youcef-Toumi},
url = {https://ieeexplore.ieee.org/document/6617292},
doi = {10.1109/SusTech.2013.6617292},
isbn = {978-1-4673-4630-6},
year = {2013},
date = {2013-10-03},
booktitle = {2013 1st IEEE Conference on Technologies for Sustainability (SusTech)},
pages = {15-22},
publisher = {IEEE},
organization = {IEEE},
abstract = {The impact of variable energy resources (VER) on power system reserve and regulation requirements has been a subject of extensive research in recent years. However, the conclusions about the scale of the impact diverge, since most of the results are obtained from specific case studies. This paper proposes a generalized approach to the assessment of power system reserve and regulation requirements. It uses a power system enterprise model that consists of three layers: the physical grid, resource scheduling and balancing operations. Resource scheduling is modeled as a security-constrained unit-commitment (SCUC) problem. The balancing layer consists of three components, namely the regulation service, the real-time market and operator manual actions. The real-time market is implemented as a security-constrained economic dispatch (SCED) problem. The IEEE RTS96 reliability test system is used for the physical layer. Three main resources contributing to the balancing of power system are studied: reserves, regulation and generator ramping rates. Their impacts on power system imbalance mitigation in the presence of VER is studied.},
keywords = {Algorithms, intelligent systems, Modeling; sizing and control for smart grids, Physical System Modeling, Simulation},
pubstate = {published},
tppubtype = {inproceedings}
}
The impact of variable energy resources (VER) on power system reserve and regulation requirements has been a subject of extensive research in recent years. However, the conclusions about the scale of the impact diverge, since most of the results are obtained from specific case studies. This paper proposes a generalized approach to the assessment of power system reserve and regulation requirements. It uses a power system enterprise model that consists of three layers: the physical grid, resource scheduling and balancing operations. Resource scheduling is modeled as a security-constrained unit-commitment (SCUC) problem. The balancing layer consists of three components, namely the regulation service, the real-time market and operator manual actions. The real-time market is implemented as a security-constrained economic dispatch (SCED) problem. The IEEE RTS96 reliability test system is used for the physical layer. Three main resources contributing to the balancing of power system are studied: reserves, regulation and generator ramping rates. Their impacts on power system imbalance mitigation in the presence of VER is studied.