Natural Genetics Adapted Control for an Autonomous Wind-Battery Based Microgrid

Farheen Chishti; Shadab Murshid; Bhim Singh

doi:10.1109/IICPE.2018.8709460

Natural Genetics Adapted Control for an Autonomous Wind-Battery Based Microgrid

Farheen Chishti
, Shadab Murshid
, Bhim Singh

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

3 Scopus citations

Abstract

This paper proposes a natural genetics and evolution based control strategy for adjusting the gains of the proportional and integral (PI) controller meant for regulating the speed of the generator of an autonomous microgrid system using wind energy generation and a battery energy storage (BES). The variable wind speed operation leads to the dereliction of the fixed gain PI controller as it is sensitive to parameter variations and load disturbances. The genetic algorithm (GA) is implemented for adapting the gains of PI controller according to the changing operating conditions. It avoids the entrapments of the optimal solution in the local search space. The optimal solution is selected on the basis of best fit candidate. The synchronous generator (SG) reference speed is obtained using perturb and observe (PO) maximum power extraction scheme. The flexible power flow control is obtained using a BES with a bidirectional converter. A prototype of the microgrid is developed in the laboratory and tested in accordance to the IEEE-519 standard under steady state and dynamic conditions including variable wind speeds and load removal.

Original language	English
Title of host publication	8th IEEE India International Conference on Power Electronics, IICPE 2018
Publisher	IEEE Computer Society
ISBN (Electronic)	9781538649961
DOIs	https://doi.org/10.1109/IICPE.2018.8709460
State	Published - 2 Jul 2018
Externally published	Yes
Event	8th IEEE India International Conference on Power Electronics, IICPE 2018 - Jaipur, India Duration: 13 Dec 2018 → 15 Dec 2018

Publication series

Name	India International Conference on Power Electronics, IICPE
Volume	2018-December
ISSN (Print)	2160-3162
ISSN (Electronic)	2160-3170

Conference

Conference	8th IEEE India International Conference on Power Electronics, IICPE 2018
Country/Territory	India
City	Jaipur
Period	13/12/18 → 15/12/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Battery
Bidirectional Converter
GA tuned PI controller
Microgrid and Power Quality
Wind Turbine Driven SG

ASJC Scopus subject areas

Energy Engineering and Power Technology
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/IICPE.2018.8709460

Cite this

@inproceedings{64a7250a12f349238254311fc1395141,

title = "Natural Genetics Adapted Control for an Autonomous Wind-Battery Based Microgrid",

abstract = "This paper proposes a natural genetics and evolution based control strategy for adjusting the gains of the proportional and integral (PI) controller meant for regulating the speed of the generator of an autonomous microgrid system using wind energy generation and a battery energy storage (BES). The variable wind speed operation leads to the dereliction of the fixed gain PI controller as it is sensitive to parameter variations and load disturbances. The genetic algorithm (GA) is implemented for adapting the gains of PI controller according to the changing operating conditions. It avoids the entrapments of the optimal solution in the local search space. The optimal solution is selected on the basis of best fit candidate. The synchronous generator (SG) reference speed is obtained using perturb and observe (PO) maximum power extraction scheme. The flexible power flow control is obtained using a BES with a bidirectional converter. A prototype of the microgrid is developed in the laboratory and tested in accordance to the IEEE-519 standard under steady state and dynamic conditions including variable wind speeds and load removal.",

keywords = "Battery, Bidirectional Converter, GA tuned PI controller, Microgrid and Power Quality, Wind Turbine Driven SG",

author = "Farheen Chishti and Shadab Murshid and Bhim Singh",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 8th IEEE India International Conference on Power Electronics, IICPE 2018 ; Conference date: 13-12-2018 Through 15-12-2018",

year = "2018",

month = jul,

day = "2",

doi = "10.1109/IICPE.2018.8709460",

language = "English",

series = "India International Conference on Power Electronics, IICPE",

publisher = "IEEE Computer Society",

booktitle = "8th IEEE India International Conference on Power Electronics, IICPE 2018",

address = "United States",

}

Chishti, F, Murshid, S & Singh, B 2018, Natural Genetics Adapted Control for an Autonomous Wind-Battery Based Microgrid. in 8th IEEE India International Conference on Power Electronics, IICPE 2018., 8709460, India International Conference on Power Electronics, IICPE, vol. 2018-December, IEEE Computer Society, 8th IEEE India International Conference on Power Electronics, IICPE 2018, Jaipur, India, 13/12/18. https://doi.org/10.1109/IICPE.2018.8709460

Natural Genetics Adapted Control for an Autonomous Wind-Battery Based Microgrid. / Chishti, Farheen; Murshid, Shadab; Singh, Bhim.
8th IEEE India International Conference on Power Electronics, IICPE 2018. IEEE Computer Society, 2018. 8709460 (India International Conference on Power Electronics, IICPE; Vol. 2018-December).

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

TY - GEN

T1 - Natural Genetics Adapted Control for an Autonomous Wind-Battery Based Microgrid

AU - Chishti, Farheen

AU - Murshid, Shadab

AU - Singh, Bhim

PY - 2018/7/2

Y1 - 2018/7/2

N2 - This paper proposes a natural genetics and evolution based control strategy for adjusting the gains of the proportional and integral (PI) controller meant for regulating the speed of the generator of an autonomous microgrid system using wind energy generation and a battery energy storage (BES). The variable wind speed operation leads to the dereliction of the fixed gain PI controller as it is sensitive to parameter variations and load disturbances. The genetic algorithm (GA) is implemented for adapting the gains of PI controller according to the changing operating conditions. It avoids the entrapments of the optimal solution in the local search space. The optimal solution is selected on the basis of best fit candidate. The synchronous generator (SG) reference speed is obtained using perturb and observe (PO) maximum power extraction scheme. The flexible power flow control is obtained using a BES with a bidirectional converter. A prototype of the microgrid is developed in the laboratory and tested in accordance to the IEEE-519 standard under steady state and dynamic conditions including variable wind speeds and load removal.

AB - This paper proposes a natural genetics and evolution based control strategy for adjusting the gains of the proportional and integral (PI) controller meant for regulating the speed of the generator of an autonomous microgrid system using wind energy generation and a battery energy storage (BES). The variable wind speed operation leads to the dereliction of the fixed gain PI controller as it is sensitive to parameter variations and load disturbances. The genetic algorithm (GA) is implemented for adapting the gains of PI controller according to the changing operating conditions. It avoids the entrapments of the optimal solution in the local search space. The optimal solution is selected on the basis of best fit candidate. The synchronous generator (SG) reference speed is obtained using perturb and observe (PO) maximum power extraction scheme. The flexible power flow control is obtained using a BES with a bidirectional converter. A prototype of the microgrid is developed in the laboratory and tested in accordance to the IEEE-519 standard under steady state and dynamic conditions including variable wind speeds and load removal.

KW - Battery

KW - Bidirectional Converter

KW - GA tuned PI controller

KW - Microgrid and Power Quality

KW - Wind Turbine Driven SG

UR - https://www.scopus.com/pages/publications/85065881549

U2 - 10.1109/IICPE.2018.8709460

DO - 10.1109/IICPE.2018.8709460

M3 - Conference contribution

AN - SCOPUS:85065881549

T3 - India International Conference on Power Electronics, IICPE

BT - 8th IEEE India International Conference on Power Electronics, IICPE 2018

PB - IEEE Computer Society

T2 - 8th IEEE India International Conference on Power Electronics, IICPE 2018

Y2 - 13 December 2018 through 15 December 2018

ER -

Natural Genetics Adapted Control for an Autonomous Wind-Battery Based Microgrid

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this