Application of Optimization for Daily Scheduling of Renewable Distributed Generations Considering Market Profits in Distribution Networks

Paul Okunade; Meisam Ansari; Arash Asrari; Javad Khazaei

doi:10.1109/NAPS.2018.8600654

Application of Optimization for Daily Scheduling of Renewable Distributed Generations Considering Market Profits in Distribution Networks

Paul Okunade
, Meisam Ansari
, Arash Asrari
, Javad Khazaei

School of Science, Engineering & Technology (Harrisburg)

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

5 Scopus citations

Abstract

In a deregulated electricity market, power system operator should systematically identify the optimal schedule of renewable distributed generation (DG) units to not only optimize the market profits but also improve the network conditions. This paper proposes a parallel computation-based methodology using fuzzy logic designed in the structure of a genetic algorithm (GA). Due to the efficient communication among the processors during the optimization, the proposed fuzzy-based parallel computation GA (FPCGA) addresses the shortcoming of the classic GA in convergence speed and quality of results. The proposed optimization algorithm is utilized in this paper to identify the optimal daily schedule for the system operator including the energy purchased from 1) the power grid, 2) each wind turbine DG, and 3) each photovoltaic DG. The efficiency of the proposed method is verified by its implementation on a 136-bus distribution system and its effectiveness is compared with similar methods.

Original language	English (US)
Title of host publication	2018 North American Power Symposium, NAPS 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538671382
DOIs	https://doi.org/10.1109/NAPS.2018.8600654
State	Published - Jul 2 2018
Event	2018 North American Power Symposium, NAPS 2018 - Fargo, United States Duration: Sep 9 2018 → Sep 11 2018

Publication series

Name	2018 North American Power Symposium, NAPS 2018

Conference

Conference	2018 North American Power Symposium, NAPS 2018
Country/Territory	United States
City	Fargo
Period	9/9/18 → 9/11/18

UN SDGs

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

SDG 7 Affordable and Clean Energy

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Energy Engineering and Power Technology
Electrical and Electronic Engineering
Control and Optimization

Access to Document

10.1109/NAPS.2018.8600654

Cite this

Okunade, P., Ansari, M., Asrari, A., & Khazaei, J. (2018). Application of Optimization for Daily Scheduling of Renewable Distributed Generations Considering Market Profits in Distribution Networks. In 2018 North American Power Symposium, NAPS 2018 Article 8600654 (2018 North American Power Symposium, NAPS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NAPS.2018.8600654

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title = "Application of Optimization for Daily Scheduling of Renewable Distributed Generations Considering Market Profits in Distribution Networks",

abstract = "In a deregulated electricity market, power system operator should systematically identify the optimal schedule of renewable distributed generation (DG) units to not only optimize the market profits but also improve the network conditions. This paper proposes a parallel computation-based methodology using fuzzy logic designed in the structure of a genetic algorithm (GA). Due to the efficient communication among the processors during the optimization, the proposed fuzzy-based parallel computation GA (FPCGA) addresses the shortcoming of the classic GA in convergence speed and quality of results. The proposed optimization algorithm is utilized in this paper to identify the optimal daily schedule for the system operator including the energy purchased from 1) the power grid, 2) each wind turbine DG, and 3) each photovoltaic DG. The efficiency of the proposed method is verified by its implementation on a 136-bus distribution system and its effectiveness is compared with similar methods.",

author = "Paul Okunade and Meisam Ansari and Arash Asrari and Javad Khazaei",

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Okunade, P, Ansari, M, Asrari, A & Khazaei, J 2018, Application of Optimization for Daily Scheduling of Renewable Distributed Generations Considering Market Profits in Distribution Networks. in 2018 North American Power Symposium, NAPS 2018., 8600654, 2018 North American Power Symposium, NAPS 2018, Institute of Electrical and Electronics Engineers Inc., 2018 North American Power Symposium, NAPS 2018, Fargo, United States, 9/9/18. https://doi.org/10.1109/NAPS.2018.8600654

Application of Optimization for Daily Scheduling of Renewable Distributed Generations Considering Market Profits in Distribution Networks. / Okunade, Paul; Ansari, Meisam; Asrari, Arash et al.
2018 North American Power Symposium, NAPS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8600654 (2018 North American Power Symposium, NAPS 2018).

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

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AU - Okunade, Paul

AU - Ansari, Meisam

AU - Asrari, Arash

AU - Khazaei, Javad

PY - 2018/7/2

Y1 - 2018/7/2

N2 - In a deregulated electricity market, power system operator should systematically identify the optimal schedule of renewable distributed generation (DG) units to not only optimize the market profits but also improve the network conditions. This paper proposes a parallel computation-based methodology using fuzzy logic designed in the structure of a genetic algorithm (GA). Due to the efficient communication among the processors during the optimization, the proposed fuzzy-based parallel computation GA (FPCGA) addresses the shortcoming of the classic GA in convergence speed and quality of results. The proposed optimization algorithm is utilized in this paper to identify the optimal daily schedule for the system operator including the energy purchased from 1) the power grid, 2) each wind turbine DG, and 3) each photovoltaic DG. The efficiency of the proposed method is verified by its implementation on a 136-bus distribution system and its effectiveness is compared with similar methods.

AB - In a deregulated electricity market, power system operator should systematically identify the optimal schedule of renewable distributed generation (DG) units to not only optimize the market profits but also improve the network conditions. This paper proposes a parallel computation-based methodology using fuzzy logic designed in the structure of a genetic algorithm (GA). Due to the efficient communication among the processors during the optimization, the proposed fuzzy-based parallel computation GA (FPCGA) addresses the shortcoming of the classic GA in convergence speed and quality of results. The proposed optimization algorithm is utilized in this paper to identify the optimal daily schedule for the system operator including the energy purchased from 1) the power grid, 2) each wind turbine DG, and 3) each photovoltaic DG. The efficiency of the proposed method is verified by its implementation on a 136-bus distribution system and its effectiveness is compared with similar methods.

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M3 - Conference contribution

AN - SCOPUS:85061796330

T3 - 2018 North American Power Symposium, NAPS 2018

BT - 2018 North American Power Symposium, NAPS 2018

PB - Institute of Electrical and Electronics Engineers Inc.

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Okunade P, Ansari M, Asrari A, Khazaei J. Application of Optimization for Daily Scheduling of Renewable Distributed Generations Considering Market Profits in Distribution Networks. In 2018 North American Power Symposium, NAPS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8600654. (2018 North American Power Symposium, NAPS 2018). doi: 10.1109/NAPS.2018.8600654

Application of Optimization for Daily Scheduling of Renewable Distributed Generations Considering Market Profits in Distribution Networks

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

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