Wind power generation planning by utilizing the reactive power capabilities of generators

Nand K. Meena; Anil Swarnkar; Nikhil Gupta; K. R. Niazi

doi:10.1109/ACEPT.2017.8168611

Wind power generation planning by utilizing the reactive power capabilities of generators

Nand K. Meena^*, Anil Swarnkar, Nikhil Gupta, K. R. Niazi

^*Corresponding author for this work

College of Engineering and Physical Sciences

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

The paper presents a new wind power generation planning framework by considering the reactive power capabilities of generators. The motivation is to maximize the utilization of renewable power hosting capacity without violating the security constraints of distribution networks. The objective is to maximize the net present value of the investment considering the cost of grid energy transaction, initial investment of wind turbines, operation and maintenance etc. The problem is developed as the mixed-integer, non-linear and non-convex optimization problem; therefore, an improved variant of genetic algorithm has been adopted. The proposed generation planning model is implemented on a benchmark test distribution system of 33 buses and the simulation results are compared with the same obtained from the traditional planning models. The comparison shows that the proposed approach effectively maximize the net present value of the investment as compared to tradition planning models.

Original language	English
Title of host publication	2017 Asian Conference on Energy, Power and Transportation Electrification, ACEPT 2017
Publisher	IEEE
Pages	1-6
Number of pages	6
Volume	2017-December
ISBN (Electronic)	9781538609712
DOIs	https://doi.org/10.1109/ACEPT.2017.8168611
Publication status	Published - 5 Dec 2017
Event	2017 Asian Conference on Energy, Power and Transportation Electrification, ACEPT 2017 - Singapore, Singapore Duration: 24 Oct 2017 → 26 Oct 2017

Conference

Conference	2017 Asian Conference on Energy, Power and Transportation Electrification, ACEPT 2017
Country/Territory	Singapore
City	Singapore
Period	24/10/17 → 26/10/17

Keywords

Distributed generation
distribution systems
genetic algorithm
mixed-integer
wind power

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10.1109/ACEPT.2017.8168611

Cite this

@inproceedings{06d3579bcfa84a3ebc0758aff1871f51,

title = "Wind power generation planning by utilizing the reactive power capabilities of generators",

abstract = "The paper presents a new wind power generation planning framework by considering the reactive power capabilities of generators. The motivation is to maximize the utilization of renewable power hosting capacity without violating the security constraints of distribution networks. The objective is to maximize the net present value of the investment considering the cost of grid energy transaction, initial investment of wind turbines, operation and maintenance etc. The problem is developed as the mixed-integer, non-linear and non-convex optimization problem; therefore, an improved variant of genetic algorithm has been adopted. The proposed generation planning model is implemented on a benchmark test distribution system of 33 buses and the simulation results are compared with the same obtained from the traditional planning models. The comparison shows that the proposed approach effectively maximize the net present value of the investment as compared to tradition planning models.",

keywords = "Distributed generation, distribution systems, genetic algorithm, mixed-integer, wind power",

author = "Meena, {Nand K.} and Anil Swarnkar and Nikhil Gupta and Niazi, {K. R.}",

year = "2017",

month = dec,

day = "5",

doi = "10.1109/ACEPT.2017.8168611",

language = "English",

volume = "2017-December",

pages = "1--6",

booktitle = "2017 Asian Conference on Energy, Power and Transportation Electrification, ACEPT 2017",

publisher = "IEEE",

address = "United States",

note = "2017 Asian Conference on Energy, Power and Transportation Electrification, ACEPT 2017 ; Conference date: 24-10-2017 Through 26-10-2017",

}

Meena, NK, Swarnkar, A, Gupta, N & Niazi, KR 2017, Wind power generation planning by utilizing the reactive power capabilities of generators. in 2017 Asian Conference on Energy, Power and Transportation Electrification, ACEPT 2017. vol. 2017-December, IEEE, pp. 1-6, 2017 Asian Conference on Energy, Power and Transportation Electrification, ACEPT 2017, Singapore, Singapore, 24/10/17. https://doi.org/10.1109/ACEPT.2017.8168611

TY - GEN

T1 - Wind power generation planning by utilizing the reactive power capabilities of generators

AU - Meena, Nand K.

AU - Swarnkar, Anil

AU - Gupta, Nikhil

AU - Niazi, K. R.

PY - 2017/12/5

Y1 - 2017/12/5

N2 - The paper presents a new wind power generation planning framework by considering the reactive power capabilities of generators. The motivation is to maximize the utilization of renewable power hosting capacity without violating the security constraints of distribution networks. The objective is to maximize the net present value of the investment considering the cost of grid energy transaction, initial investment of wind turbines, operation and maintenance etc. The problem is developed as the mixed-integer, non-linear and non-convex optimization problem; therefore, an improved variant of genetic algorithm has been adopted. The proposed generation planning model is implemented on a benchmark test distribution system of 33 buses and the simulation results are compared with the same obtained from the traditional planning models. The comparison shows that the proposed approach effectively maximize the net present value of the investment as compared to tradition planning models.

AB - The paper presents a new wind power generation planning framework by considering the reactive power capabilities of generators. The motivation is to maximize the utilization of renewable power hosting capacity without violating the security constraints of distribution networks. The objective is to maximize the net present value of the investment considering the cost of grid energy transaction, initial investment of wind turbines, operation and maintenance etc. The problem is developed as the mixed-integer, non-linear and non-convex optimization problem; therefore, an improved variant of genetic algorithm has been adopted. The proposed generation planning model is implemented on a benchmark test distribution system of 33 buses and the simulation results are compared with the same obtained from the traditional planning models. The comparison shows that the proposed approach effectively maximize the net present value of the investment as compared to tradition planning models.

KW - Distributed generation

KW - distribution systems

KW - genetic algorithm

KW - mixed-integer

KW - wind power

UR - http://www.scopus.com/inward/record.url?scp=85045926856&partnerID=8YFLogxK

UR - https://ieeexplore.ieee.org/document/8168611

U2 - 10.1109/ACEPT.2017.8168611

DO - 10.1109/ACEPT.2017.8168611

M3 - Conference publication

AN - SCOPUS:85045926856

VL - 2017-December

SP - 1

EP - 6

BT - 2017 Asian Conference on Energy, Power and Transportation Electrification, ACEPT 2017

PB - IEEE

T2 - 2017 Asian Conference on Energy, Power and Transportation Electrification, ACEPT 2017

Y2 - 24 October 2017 through 26 October 2017

ER -

Wind power generation planning by utilizing the reactive power capabilities of generators

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