Design and Cosimulation of Hierarchical Architecture for Demand Response Control and Coordination

Bhattarai, Bishnu P.; Levesque, Martin; Bak-Jensen, Birgitte; Pillai, Jaykrishnan R.; Maier, Martin; Tipper, David; Myers, Kurt S.

doi:10.1109/TII.2016.2634582

Title: Design and Cosimulation of Hierarchical Architecture for Demand Response Control and Coordination

Abstract

Demand response (DR) plays a key role for optimum asset utilization and to avoid or delay the need of new infrastructure investment. However, coordinated execution of multiple DRs is desired to maximize the DR benefits. In this paper, we propose a hierarchical DR architecture (HDRA) to control and coordinate the performance of various DR categories such that the operation of every DR category is backed-up by time delayed action of the others. A reliable, cost-effective communication infrastructure based on ZigBee, WiMAX, and fibers is designed to facilitate the HDRA execution. The performance of the proposed HDRA is demonstrated from the power system and communication perspectives in a cosimulation environment applied to a 0.4 kV/400 kVA real distribution network considering electric vehicles as a potential DR resource (DRR). The power simulation is performed employing a real time digital simulator whereas the communication simulation is performed using OMNeT++. Finally, the HDRA performance demonstrated the maximum utilization of available DR potential by facilitating simultaneous execution of multiple DRs and enabling participation of single DRR for multiple grid applications.

Authors:

Bhattarai, Bishnu P. ^[1]; Levesque, Martin ^[2]; Bak-Jensen, Birgitte ^[3]; Pillai, Jaykrishnan R. ^[3]; Maier, Martin ^[4]; Tipper, David ^[2]; Myers, Kurt S. ^[1]

Idaho National Lab. (INL), Idaho Falls, ID (United States)
Univ. of Pittsburgh, PA (United States)
Aalborg Univ. (Denmark)
National Inst. of Scientific Research (INRS), Montreal, QC (Canada)

Publication Date:: Wed Dec 07 00:00:00 EST 2016

Research Org.:: Idaho National Lab. (INL), Idaho Falls, ID (United States)

Sponsoring Org.:: USDOE; INL Laboratory Directed Research and Development (LDRD) Program

OSTI Identifier:: 1367538

Report Number(s):: INL/JOU-16-39167
Journal ID: ISSN 1551-3203

Grant/Contract Number:: AC07-05ID14517

Resource Type:: Accepted Manuscript

Journal Name:: IEEE Transactions on Industrial Informatics

Additional Journal Information:: Journal Volume: 13; Journal Issue: 4; Journal ID: ISSN 1551-3203

Publisher:: IEEE

Country of Publication:: United States

Language:: English

Subject:: 24 POWER TRANSMISSION AND DISTRIBUTION; electric potential; load management; frequency control; time factors; reliability; picture archiving and communication systems; informatics; demand side management; digital simulation; electric vehicles; optical fibre communication; power distribution control; real-time systems; cosimulation; demand dispatch; demand response; energy management; hierarchical control

Citation Formats


                    Bhattarai, Bishnu P., Levesque, Martin, Bak-Jensen, Birgitte, Pillai, Jaykrishnan R., Maier, Martin, Tipper, David, and Myers, Kurt S. Design and Cosimulation of Hierarchical Architecture for Demand Response Control and Coordination.  United States: N. p., 2016. 
Web.  doi:10.1109/TII.2016.2634582.

Copy to clipboard


                    Bhattarai, Bishnu P., Levesque, Martin, Bak-Jensen, Birgitte, Pillai, Jaykrishnan R., Maier, Martin, Tipper, David, & Myers, Kurt S. Design and Cosimulation of Hierarchical Architecture for Demand Response Control and Coordination.  United States.  https://doi.org/10.1109/TII.2016.2634582

Copy to clipboard


                    Bhattarai, Bishnu P., Levesque, Martin, Bak-Jensen, Birgitte, Pillai, Jaykrishnan R., Maier, Martin, Tipper, David, and Myers, Kurt S. Wed .  
"Design and Cosimulation of Hierarchical Architecture for Demand Response Control and Coordination".  United States.  https://doi.org/10.1109/TII.2016.2634582.  https://www.osti.gov/servlets/purl/1367538.

Copy to clipboard


                    
@article{osti_1367538,

  title        = {Design and Cosimulation of Hierarchical Architecture for Demand Response Control and Coordination},

  author       = {Bhattarai, Bishnu P. and Levesque, Martin and Bak-Jensen, Birgitte and Pillai, Jaykrishnan R. and Maier, Martin and Tipper, David and Myers, Kurt S.},

  abstractNote = {Demand response (DR) plays a key role for optimum asset utilization and to avoid or delay the need of new infrastructure investment. However, coordinated execution of multiple DRs is desired to maximize the DR benefits. In this paper, we propose a hierarchical DR architecture (HDRA) to control and coordinate the performance of various DR categories such that the operation of every DR category is backed-up by time delayed action of the others. A reliable, cost-effective communication infrastructure based on ZigBee, WiMAX, and fibers is designed to facilitate the HDRA execution. The performance of the proposed HDRA is demonstrated from the power system and communication perspectives in a cosimulation environment applied to a 0.4 kV/400 kVA real distribution network considering electric vehicles as a potential DR resource (DRR). The power simulation is performed employing a real time digital simulator whereas the communication simulation is performed using OMNeT++. Finally, the HDRA performance demonstrated the maximum utilization of available DR potential by facilitating simultaneous execution of multiple DRs and enabling participation of single DRR for multiple grid applications.},

  doi          = {10.1109/TII.2016.2634582},

  journal      = {IEEE Transactions on Industrial Informatics},

  number       = 4,

  volume       = 13,

  place        = {United States},

  year         = {Wed Dec 07 00:00:00 EST 2016},

  month        = {Wed Dec 07 00:00:00 EST 2016}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (DOE)

Publisher's Version of Record

https://doi.org/10.1109/TII.2016.2634582

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 30 works

Citation information provided by
Web of Science

Save / Share:

Export Metadata

Save to My Library

Works referencing / citing this record:

Modeling a Hybrid Microgrid Using Probabilistic Reconfiguration under System Uncertainties
journal, September 2017

Moradi, Hadis; Esfahanian, Mahdi; Abtahi, Amir
Energies, Vol. 10, Issue 9
DOI: 10.3390/en10091430

A Flexible Responsive Load Economic Model for Industrial Demands
journal, March 2019

Sharifi, Reza; Anvari-Moghaddam, Amjad; Fathi, S.
Processes, Vol. 7, Issue 3
DOI: 10.3390/pr7030147

Similar Records in DOE PAGES and OSTI.GOV collections:

A Power Hardware-in-the-Loop Platform with Remote Distribution Circuit Cosimulation

Journal Article Palmintier, Bryan ; Lundstrom, Blake ; Chakraborty, Sudipta ; ... - IEEE Transactions on Industrial Electronics, 62(4):2236-2245

This paper demonstrates the use of a novel cosimulation architecture that integrates hardware testing using Power Hardware-in-the-Loop (PHIL) with larger-scale electric grid models using off-the-shelf, non-PHIL software tools. This architecture enables utilities to study the impacts of emerging energy technologies on their system and manufacturers to explore the interactions of new devices with existing and emerging devices on the power system, both without the need to convert existing grid models to a new platform or to conduct in-field trials. The paper describes an implementation of this architecture for testing two residential-scale advanced solar inverters at separate points of common coupling.more »« less
https://doi.org/10.1109/TIE.2014.2367462
Modular Controllable Transformers (MCT)

Technical Report Kandula, Rajendra Prasad ; Divan, Deepak ; Jinsiwale, Rohit ; ...

Large Power Transformers (LPTs) are at the heart of the electricity infrastructure and are critical pieces in today’s grid. Aging assets, long turn-around times, transportation delays and dependence on foreign manufacturing for these components have created conditions for points of failure across the system. Moreover, there is no available dynamic control on these passive sections of the grid. For all the automation embedded on the low voltage side of the low voltage side of the system there is absolutely no flexibility on the high voltage side. Changes in power flow patterns are brought about by altering dispatch patterns for generatorsmore »« less
https://doi.org/10.2172/1488762

Full Text Available
SEAS Communication Engine: An Extensible, Flexible Wrapper for Cosimulation Agents

Conference Helman, Sam ; Panda, Kinshuk ; Vaidhynathan, Deepthi ; ...

When modeling and analyzing the power grid and other large scale systems, researchers often express scenarios as optimization problems and feed them into advanced software solvers. In order to allow multiple solvers to communicate with each other and share data from different domains, the National Renewable Energy Laboratory (NREL) and associated Department of Energy (DOE) labs have developed a software framework called the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS). HELICS allows cosimulation via a collection of client libraries for different languages that can be called from the appropriate optimization software. However, these client libraries do not provide a highermore »« less
https://doi.org/10.1109/ISGT59692.2024.10454190
A Data-Driven, Distributed Game-Theoretic Transactional Control Approach for Hierarchical Demand Response

Journal Article Amasyali, Kadir ; Chen, Yang ; Olama, Mohammed - IEEE Access

Modern power systems require flexible demand-side resources to maintain the balance between electricity supply and demand. Building thermostatically controlled loads (TCLs) are great flexible assets, as they account for a significant portion of electricity consumption in buildings. In this regard, demand response (DR) programs have long been used by grid operators to enable the coordination of TCLs to reveal and utilize this demand flexibility. Existing efforts in DR are mostly model-based, which is not scalable because gathering the physical parameters and developing an accurate model for each participating load is impractical. To address this limitation, this paper proposes a data-driven,more »« less
https://doi.org/10.1109/ACCESS.2022.3188642
Dynamic traffic routing in a network with adaptive signal control

Journal Article Chai, Huajun ; Zhang, H. M. ; Ghosal, Dipak ; ... - Transportation Research Part C: Emerging Technologies

In real traffic networks, travellers’ route choice is affected by traffic control strategies. In this work, we capture the interaction between travellers’ route choice and traffic signal control in a coherent framework. For travellers’ route choice, a VANET (Vehicular Ad hoc NETwork) is considered, where travellers have access to the real-time traffic information through V2V/V2I (Vehicle to Vehicle/Vehicle to Infrastructure) infrastructures and make route choice decisions at each intersection using hyper-path trees. We test our algorithm and control strategy by simulation in OmNet++ (A network communication simulator) and SUMO (Simulation of Urban MObility) under several scenarios. The simulation results showmore »« less
https://doi.org/10.1016/j.trc.2017.08.017

Full Text Available

Similar Records

Title: Design and Cosimulation of Hierarchical Architecture for Demand Response Control and Coordination

Abstract

Citation Formats

Modeling a Hybrid Microgrid Using Probabilistic Reconfiguration under System Uncertainties journal, September 2017

A Flexible Responsive Load Economic Model for Industrial Demands journal, March 2019

Modeling a Hybrid Microgrid Using Probabilistic Reconfiguration under System Uncertainties
journal, September 2017

A Flexible Responsive Load Economic Model for Industrial Demands
journal, March 2019