Bi-Level Distribution Network Planning Integrated with Energy Storage to PV-Connected Network

Ali Ashoor Nejad Moghadam; Hamid Falaghi; Mojtaba Yousefi; Amin Hajizadeh

doi:10.1109/ISIE45063.2020.9152508

Bi-Level Distribution Network Planning Integrated with Energy Storage to PV-Connected Network

Ali Ashoor Nejad Moghadam, Hamid Falaghi, Mojtaba Yousefi, Amin Hajizadeh

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

8 Citations (Scopus)

Abstract

As the penetration of renewable energy resources has been increased in the distribution network, the intermittent and fluctuation of the system parameters have increased highly. Energy Storage Systems (ESSs) is one of the best candidates to overcome this intermittency, especially in the Photovoltaicconnected (PV-connected) distribution network. In this paper, optimal planning of ESSs in a PV-connected distribution network regarding PV and load uncertainties is studied. Operation conditions are considered based on a time-series framework. The Fuzzy Clustering Method (FCM) is adopted to create sample days. Moreover, since the optimization problem is a mixed-integer nonlinear programming problem, Particle Swarm Optimization (PSO) is chosen as a powerful nonlinear optimization solver. A modified 33-bus is employed to verify the proposed method. The PSO determines the optimal size and sites of ESSs in the distribution network which is confirmed in the simulation results. Moreover, the effects of integration ESSs with PVs to support load growth and peak reduction are illustrated.

Original language	English
Title of host publication	29th International Symposium on Industrial Electronics (ISIE)
Number of pages	5
Publisher	IEEE (Institute of Electrical and Electronics Engineers)
Publication date	Jul 2020
Pages	1325-1329
Article number	9152508
ISBN (Electronic)	9781728156354
DOIs	https://doi.org/10.1109/ISIE45063.2020.9152508
Publication status	Published - Jul 2020
Event	29th IEEE International Symposium on Industrial Electronics: online conference hosted in Delft, The Netherlands - Delft, Netherlands Duration: 17 Jun 2020 → 19 Jun 2020 http://isie2020.org/

Conference

Conference	29th IEEE International Symposium on Industrial Electronics
Country/Territory	Netherlands
City	Delft
Period	17/06/2020 → 19/06/2020
Internet address	http://isie2020.org/

Series	Industrial Electronics (ISIE), IEEE International Symposium on
ISSN	2163-5137

Keywords

Bi-level Planning Data clustering
Distribution Network Planning
Energy Storage Systems

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Moghadam, Ali Ashoor Nejad ; Falaghi, Hamid ; Yousefi, Mojtaba et al. / Bi-Level Distribution Network Planning Integrated with Energy Storage to PV-Connected Network. 29th International Symposium on Industrial Electronics (ISIE). IEEE (Institute of Electrical and Electronics Engineers), 2020. pp. 1325-1329 (Industrial Electronics (ISIE), IEEE International Symposium on).

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title = "Bi-Level Distribution Network Planning Integrated with Energy Storage to PV-Connected Network",

abstract = "As the penetration of renewable energy resources has been increased in the distribution network, the intermittent and fluctuation of the system parameters have increased highly. Energy Storage Systems (ESSs) is one of the best candidates to overcome this intermittency, especially in the Photovoltaicconnected (PV-connected) distribution network. In this paper, optimal planning of ESSs in a PV-connected distribution network regarding PV and load uncertainties is studied. Operation conditions are considered based on a time-series framework. The Fuzzy Clustering Method (FCM) is adopted to create sample days. Moreover, since the optimization problem is a mixed-integer nonlinear programming problem, Particle Swarm Optimization (PSO) is chosen as a powerful nonlinear optimization solver. A modified 33-bus is employed to verify the proposed method. The PSO determines the optimal size and sites of ESSs in the distribution network which is confirmed in the simulation results. Moreover, the effects of integration ESSs with PVs to support load growth and peak reduction are illustrated. ",

keywords = "Bi-level Planning Data clustering, Distribution Network Planning, Energy Storage Systems",

author = "Moghadam, {Ali Ashoor Nejad} and Hamid Falaghi and Mojtaba Yousefi and Amin Hajizadeh",

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Moghadam, AAN, Falaghi, H, Yousefi, M & Hajizadeh, A 2020, Bi-Level Distribution Network Planning Integrated with Energy Storage to PV-Connected Network. in 29th International Symposium on Industrial Electronics (ISIE)., 9152508, IEEE (Institute of Electrical and Electronics Engineers), Industrial Electronics (ISIE), IEEE International Symposium on, pp. 1325-1329, 29th IEEE International Symposium on Industrial Electronics, Delft, Netherlands, 17/06/2020. https://doi.org/10.1109/ISIE45063.2020.9152508

Bi-Level Distribution Network Planning Integrated with Energy Storage to PV-Connected Network. / Moghadam, Ali Ashoor Nejad; Falaghi, Hamid; Yousefi, Mojtaba et al.
29th International Symposium on Industrial Electronics (ISIE). IEEE (Institute of Electrical and Electronics Engineers), 2020. p. 1325-1329 9152508 (Industrial Electronics (ISIE), IEEE International Symposium on).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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AU - Moghadam, Ali Ashoor Nejad

AU - Falaghi, Hamid

AU - Yousefi, Mojtaba

AU - Hajizadeh, Amin

PY - 2020/7

Y1 - 2020/7

N2 - As the penetration of renewable energy resources has been increased in the distribution network, the intermittent and fluctuation of the system parameters have increased highly. Energy Storage Systems (ESSs) is one of the best candidates to overcome this intermittency, especially in the Photovoltaicconnected (PV-connected) distribution network. In this paper, optimal planning of ESSs in a PV-connected distribution network regarding PV and load uncertainties is studied. Operation conditions are considered based on a time-series framework. The Fuzzy Clustering Method (FCM) is adopted to create sample days. Moreover, since the optimization problem is a mixed-integer nonlinear programming problem, Particle Swarm Optimization (PSO) is chosen as a powerful nonlinear optimization solver. A modified 33-bus is employed to verify the proposed method. The PSO determines the optimal size and sites of ESSs in the distribution network which is confirmed in the simulation results. Moreover, the effects of integration ESSs with PVs to support load growth and peak reduction are illustrated.

AB - As the penetration of renewable energy resources has been increased in the distribution network, the intermittent and fluctuation of the system parameters have increased highly. Energy Storage Systems (ESSs) is one of the best candidates to overcome this intermittency, especially in the Photovoltaicconnected (PV-connected) distribution network. In this paper, optimal planning of ESSs in a PV-connected distribution network regarding PV and load uncertainties is studied. Operation conditions are considered based on a time-series framework. The Fuzzy Clustering Method (FCM) is adopted to create sample days. Moreover, since the optimization problem is a mixed-integer nonlinear programming problem, Particle Swarm Optimization (PSO) is chosen as a powerful nonlinear optimization solver. A modified 33-bus is employed to verify the proposed method. The PSO determines the optimal size and sites of ESSs in the distribution network which is confirmed in the simulation results. Moreover, the effects of integration ESSs with PVs to support load growth and peak reduction are illustrated.

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ER -

Moghadam AAN, Falaghi H, Yousefi M, Hajizadeh A. Bi-Level Distribution Network Planning Integrated with Energy Storage to PV-Connected Network. In 29th International Symposium on Industrial Electronics (ISIE). IEEE (Institute of Electrical and Electronics Engineers). 2020. p. 1325-1329. 9152508. (Industrial Electronics (ISIE), IEEE International Symposium on). doi: 10.1109/ISIE45063.2020.9152508

Bi-Level Distribution Network Planning Integrated with Energy Storage to PV-Connected Network

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