Multi-time scale control of demand flexibility in smart distribution networks

Bhattarai, Bishnu; Myers, Kurt; Bak-Jensen, Birgitte; Paudyal, Sumit

doi:10.3390/en10010037

Title: Multi-time scale control of demand flexibility in smart distribution networks

Abstract

This study presents a multi-timescale control strategy to deploy demand flexibilities of electric vehicles (EV) for providing system balancing and local congestion management by simultaneously ensuring economic benefits to participating actors. First, the EV charging problem from consumer, aggregator, and grid operator’s perspective is investigated. A hierarchical control architecture (HCA) comprising scheduling, coordinative, and adaptive layers is then designed to realize their coordinative goal. This is realized by integrating a multi-time scale control, which works from a day-ahead scheduling up to real-time adaptive control. The performance of the developed method is investigated with high EV penetration in a typical distribution network. The simulation results demonstrates that HCA exploit EV flexibility to solve grid unbalancing and congestions with simultaneous maximization of economic benefits by ensuring EV participation to day-ahead, balancing, and regulation markets. For the given network configuration and pricing structure, HCA ensures the EV owners to get paid up to 5 times the cost they were paying without control.

Authors:

Bhattarai, Bishnu ^[1]; Myers, Kurt ^[1];

^[2]; Paudyal, Sumit ^[3]

Idaho National Lab. (INL), Idaho Falls, ID (United States)
Aalborg Univ., Aalborg (Denmark)
Michigan Technological Univ., Houghton, MI (United States)

Publication Date:: Sun Jan 01 00:00:00 EST 2017

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

Sponsoring Org.:: USDOE Office of Nuclear Energy (NE)

OSTI Identifier:: 1357777

Report Number(s):: INL/JOU-16-40003
Journal ID: ISSN 1996-1073; ENERGA; PII: en10010037

Grant/Contract Number:: AC07-05ID14517

Resource Type:: Accepted Manuscript

Journal Name:: Energies (Basel)

Additional Journal Information:: Journal Name: Energies (Basel); Journal Volume: 10; Journal Issue: 1; Journal ID: ISSN 1996-1073

Publisher:: MDPI AG

Country of Publication:: United States

Language:: English

Subject:: 25 ENERGY STORAGE; 24 POWER TRANSMISSION AND DISTRIBUTION; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; congestion management; demand response; electric vehicle; hierarchical charging; smart charging; smart grid; hierarchical control; microgrid

Citation Formats


                    Bhattarai, Bishnu, Myers, Kurt, Bak-Jensen, Birgitte, and Paudyal, Sumit. Multi-time scale control of demand flexibility in smart distribution networks.  United States: N. p., 2017. 
Web.  doi:10.3390/en10010037.

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                    Bhattarai, Bishnu, Myers, Kurt, Bak-Jensen, Birgitte, & Paudyal, Sumit. Multi-time scale control of demand flexibility in smart distribution networks.  United States.  https://doi.org/10.3390/en10010037

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                    Bhattarai, Bishnu, Myers, Kurt, Bak-Jensen, Birgitte, and Paudyal, Sumit. Sun .  
"Multi-time scale control of demand flexibility in smart distribution networks".  United States.  https://doi.org/10.3390/en10010037.  https://www.osti.gov/servlets/purl/1357777.

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@article{osti_1357777,

  title        = {Multi-time scale control of demand flexibility in smart distribution networks},

  author       = {Bhattarai, Bishnu and Myers, Kurt and Bak-Jensen, Birgitte and Paudyal, Sumit},

  abstractNote = {This study presents a multi-timescale control strategy to deploy demand flexibilities of electric vehicles (EV) for providing system balancing and local congestion management by simultaneously ensuring economic benefits to participating actors. First, the EV charging problem from consumer, aggregator, and grid operator’s perspective is investigated. A hierarchical control architecture (HCA) comprising scheduling, coordinative, and adaptive layers is then designed to realize their coordinative goal. This is realized by integrating a multi-time scale control, which works from a day-ahead scheduling up to real-time adaptive control. The performance of the developed method is investigated with high EV penetration in a typical distribution network. The simulation results demonstrates that HCA exploit EV flexibility to solve grid unbalancing and congestions with simultaneous maximization of economic benefits by ensuring EV participation to day-ahead, balancing, and regulation markets. For the given network configuration and pricing structure, HCA ensures the EV owners to get paid up to 5 times the cost they were paying without control.},

  doi          = {10.3390/en10010037},

  journal      = {Energies (Basel)},

  number       = 1,

  volume       = 10,

  place        = {United States},

  year         = {Sun Jan 01 00:00:00 EST 2017},

  month        = {Sun Jan 01 00:00:00 EST 2017}

}

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https://doi.org/10.3390/en10010037

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Works referenced in this record:

Day-Ahead Energy Planning with 100% Electric Vehicle Penetration in the Nordic Region by 2050
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Bhattarai, Bishnu P.; Levesque, Martin; Maier, Martin
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Supplementary Load Frequency Control by Use of a Number of Both Electric Vehicles and Heat Pump Water Heaters
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Masuta, Taisuke; Yokoyama, Akihiko
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Probabilistic Agent-Based Model of Electric Vehicle Charging Demand to Analyse the Impact on Distribution Networks
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Local Versus Centralized Charging Strategies for Electric Vehicles in Low Voltage Distribution Systems
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Works referencing / citing this record:

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

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Title: Multi-time scale control of demand flexibility in smart distribution networks

Abstract

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