Robust Optimal Microgrid Management using a Virtual Battery System for Application to Unit Commitments

Harun Or Rashid Howlader; Hasan Masrur; Md Rabiul Islam; Kashem M. Muttaqi; Ryuto Shigenobu; Tomonobu Senjyu

doi:10.1109/IAS48185.2021.9677211

Robust Optimal Microgrid Management using a Virtual Battery System for Application to Unit Commitments

Harun Or Rashid Howlader^*, Hasan Masrur, Md Rabiul Islam, Kashem M. Muttaqi, Ryuto Shigenobu, Tomonobu Senjyu

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

A virtual battery (VB) model is proposed in this paper to facilitate in the management of a smart microgrid. A cluster of controllable load and generations (CLGs) is referred to as VB, and it operates similarly as the battery storage that reduces the size of the energy storage device (ESS). Aggregators use the VB to distribute power among CLGs when the grid has excess or shortage capacity. The management of a microgrid with renewable energy instability and VB is a difficult problem; as a result, this proposed study introduces adaptive robust optimization (ARO) for unit commitment (UC) problems in microgrids that takes VB into account. Three separate UC cases are depicted in the proposed scheme. Case 1 treats only optimization and deterministic UC problem for the day ahead forecasted load; Case 2 discloses the UC with treating robust optimization, which considers forested reference day ahead load utilizing robust constraints. Case 3 emphasizes real-time load considering the worst uncertainty/prediction error of renewables and virtual battery for polishing the actual load. A neural network is adopted to forecast variable renewable generations (VRGs) output power. MATLAB® simulation with Mixed Integer Linear Programming (MILP) has been utilized for solving the ARO UC problem with VB.

Original language	English
Title of host publication	2021 IEEE Industry Applications Society Annual Meeting, IAS 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728164014
DOIs	https://doi.org/10.1109/IAS48185.2021.9677211
State	Published - 2021
Externally published	Yes

Publication series

Name	Conference Record - IAS Annual Meeting (IEEE Industry Applications Society)
Volume	2021-October
ISSN (Print)	0197-2618

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

Robust unit commitment
Smart microgrid
Uncertainty
Variable renewable
Virtual battery

ASJC Scopus subject areas

Control and Systems Engineering
Industrial and Manufacturing Engineering
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/IAS48185.2021.9677211

Cite this

Howlader, H. O. R., Masrur, H., Islam, M. R., Muttaqi, K. M., Shigenobu, R., & Senjyu, T. (2021). Robust Optimal Microgrid Management using a Virtual Battery System for Application to Unit Commitments. In 2021 IEEE Industry Applications Society Annual Meeting, IAS 2021 (Conference Record - IAS Annual Meeting (IEEE Industry Applications Society); Vol. 2021-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IAS48185.2021.9677211

Howlader, Harun Or Rashid ; Masrur, Hasan ; Islam, Md Rabiul et al. / Robust Optimal Microgrid Management using a Virtual Battery System for Application to Unit Commitments. 2021 IEEE Industry Applications Society Annual Meeting, IAS 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (Conference Record - IAS Annual Meeting (IEEE Industry Applications Society)).

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title = "Robust Optimal Microgrid Management using a Virtual Battery System for Application to Unit Commitments",

abstract = "A virtual battery (VB) model is proposed in this paper to facilitate in the management of a smart microgrid. A cluster of controllable load and generations (CLGs) is referred to as VB, and it operates similarly as the battery storage that reduces the size of the energy storage device (ESS). Aggregators use the VB to distribute power among CLGs when the grid has excess or shortage capacity. The management of a microgrid with renewable energy instability and VB is a difficult problem; as a result, this proposed study introduces adaptive robust optimization (ARO) for unit commitment (UC) problems in microgrids that takes VB into account. Three separate UC cases are depicted in the proposed scheme. Case 1 treats only optimization and deterministic UC problem for the day ahead forecasted load; Case 2 discloses the UC with treating robust optimization, which considers forested reference day ahead load utilizing robust constraints. Case 3 emphasizes real-time load considering the worst uncertainty/prediction error of renewables and virtual battery for polishing the actual load. A neural network is adopted to forecast variable renewable generations (VRGs) output power. MATLAB{\textregistered} simulation with Mixed Integer Linear Programming (MILP) has been utilized for solving the ARO UC problem with VB.",

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author = "Howlader, \{Harun Or Rashid\} and Hasan Masrur and Islam, \{Md Rabiul\} and Muttaqi, \{Kashem M.\} and Ryuto Shigenobu and Tomonobu Senjyu",

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year = "2021",

doi = "10.1109/IAS48185.2021.9677211",

language = "English",

series = "Conference Record - IAS Annual Meeting (IEEE Industry Applications Society)",

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Howlader, HOR, Masrur, H, Islam, MR, Muttaqi, KM, Shigenobu, R & Senjyu, T 2021, Robust Optimal Microgrid Management using a Virtual Battery System for Application to Unit Commitments. in 2021 IEEE Industry Applications Society Annual Meeting, IAS 2021. Conference Record - IAS Annual Meeting (IEEE Industry Applications Society), vol. 2021-October, Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/IAS48185.2021.9677211

Robust Optimal Microgrid Management using a Virtual Battery System for Application to Unit Commitments. / Howlader, Harun Or Rashid; Masrur, Hasan; Islam, Md Rabiul et al.
2021 IEEE Industry Applications Society Annual Meeting, IAS 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (Conference Record - IAS Annual Meeting (IEEE Industry Applications Society); Vol. 2021-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Howlader, Harun Or Rashid

AU - Masrur, Hasan

AU - Islam, Md Rabiul

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AU - Shigenobu, Ryuto

AU - Senjyu, Tomonobu

PY - 2021

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N2 - A virtual battery (VB) model is proposed in this paper to facilitate in the management of a smart microgrid. A cluster of controllable load and generations (CLGs) is referred to as VB, and it operates similarly as the battery storage that reduces the size of the energy storage device (ESS). Aggregators use the VB to distribute power among CLGs when the grid has excess or shortage capacity. The management of a microgrid with renewable energy instability and VB is a difficult problem; as a result, this proposed study introduces adaptive robust optimization (ARO) for unit commitment (UC) problems in microgrids that takes VB into account. Three separate UC cases are depicted in the proposed scheme. Case 1 treats only optimization and deterministic UC problem for the day ahead forecasted load; Case 2 discloses the UC with treating robust optimization, which considers forested reference day ahead load utilizing robust constraints. Case 3 emphasizes real-time load considering the worst uncertainty/prediction error of renewables and virtual battery for polishing the actual load. A neural network is adopted to forecast variable renewable generations (VRGs) output power. MATLAB® simulation with Mixed Integer Linear Programming (MILP) has been utilized for solving the ARO UC problem with VB.

AB - A virtual battery (VB) model is proposed in this paper to facilitate in the management of a smart microgrid. A cluster of controllable load and generations (CLGs) is referred to as VB, and it operates similarly as the battery storage that reduces the size of the energy storage device (ESS). Aggregators use the VB to distribute power among CLGs when the grid has excess or shortage capacity. The management of a microgrid with renewable energy instability and VB is a difficult problem; as a result, this proposed study introduces adaptive robust optimization (ARO) for unit commitment (UC) problems in microgrids that takes VB into account. Three separate UC cases are depicted in the proposed scheme. Case 1 treats only optimization and deterministic UC problem for the day ahead forecasted load; Case 2 discloses the UC with treating robust optimization, which considers forested reference day ahead load utilizing robust constraints. Case 3 emphasizes real-time load considering the worst uncertainty/prediction error of renewables and virtual battery for polishing the actual load. A neural network is adopted to forecast variable renewable generations (VRGs) output power. MATLAB® simulation with Mixed Integer Linear Programming (MILP) has been utilized for solving the ARO UC problem with VB.

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AN - SCOPUS:85124685080

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BT - 2021 IEEE Industry Applications Society Annual Meeting, IAS 2021

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Howlader HOR, Masrur H, Islam MR, Muttaqi KM, Shigenobu R, Senjyu T. Robust Optimal Microgrid Management using a Virtual Battery System for Application to Unit Commitments. In 2021 IEEE Industry Applications Society Annual Meeting, IAS 2021. Institute of Electrical and Electronics Engineers Inc. 2021. (Conference Record - IAS Annual Meeting (IEEE Industry Applications Society)). doi: 10.1109/IAS48185.2021.9677211

Robust Optimal Microgrid Management using a Virtual Battery System for Application to Unit Commitments

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this