Analytical method for energy storage sizing and reliability assessment for power systems with variable generation

Abdullah Alamri; Maad AlOwaifeer; A. P.Sakis Meliopoulos

Analytical method for energy storage sizing and reliability assessment for power systems with variable generation

Abdullah Alamri
, Maad AlOwaifeer
, A. P.Sakis Meliopoulos

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

Abstract

This paper presents a mixed integer linear program (MILP) to optimally size power and energy of energy storage systems (ESSs). The sizing model takes into account conventional generation (CG) operation constraints in addition to seasonal and locational wind speed and solar radiation variations, and variable generation (wind turbine systems (WTSs) and solar cell generators (SCGs)) forced outages. Subsequently, the outcomes of the ESS sizing model are inputted to the probabilistic production method (PCC) to assess the reliability of the integrated system. All aforementioned analyses have been applied to a system with different penetration levels. The method is demonstrated with case studies on a system consisting of 10 CG units and VG penetration levels of 20% and 30%. For each penetration level, ESS sizing is computed and then reliability assessment is performed.

Original language	English
Title of host publication	Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020
Editors	Tung X. Bui
Publisher	IEEE Computer Society
Pages	2981-2990
Number of pages	10
ISBN (Electronic)	9780998133133
State	Published - 2020
Externally published	Yes

Publication series

Name	Proceedings of the Annual Hawaii International Conference on System Sciences
Volume	2020-January
ISSN (Print)	1530-1605

Bibliographical note

Publisher Copyright:
© 2020 IEEE Computer Society. All rights reserved.

UN SDGs

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

SDG 7 Affordable and Clean Energy

ASJC Scopus subject areas

General Engineering

Cite this

Alamri, A., AlOwaifeer, M., & Meliopoulos, A. P. S. (2020). Analytical method for energy storage sizing and reliability assessment for power systems with variable generation. In T. X. Bui (Ed.), Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020 (pp. 2981-2990). (Proceedings of the Annual Hawaii International Conference on System Sciences; Vol. 2020-January). IEEE Computer Society.

Alamri, Abdullah ; AlOwaifeer, Maad ; Meliopoulos, A. P.Sakis. / Analytical method for energy storage sizing and reliability assessment for power systems with variable generation. Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020. editor / Tung X. Bui. IEEE Computer Society, 2020. pp. 2981-2990 (Proceedings of the Annual Hawaii International Conference on System Sciences).

@inproceedings{9c6f6bef5abe4215821994044b8ea45a,

title = "Analytical method for energy storage sizing and reliability assessment for power systems with variable generation",

abstract = "This paper presents a mixed integer linear program (MILP) to optimally size power and energy of energy storage systems (ESSs). The sizing model takes into account conventional generation (CG) operation constraints in addition to seasonal and locational wind speed and solar radiation variations, and variable generation (wind turbine systems (WTSs) and solar cell generators (SCGs)) forced outages. Subsequently, the outcomes of the ESS sizing model are inputted to the probabilistic production method (PCC) to assess the reliability of the integrated system. All aforementioned analyses have been applied to a system with different penetration levels. The method is demonstrated with case studies on a system consisting of 10 CG units and VG penetration levels of 20\% and 30\%. For each penetration level, ESS sizing is computed and then reliability assessment is performed.",

author = "Abdullah Alamri and Maad AlOwaifeer and Meliopoulos, \{A. P.Sakis\}",

year = "2020",

language = "English",

series = "Proceedings of the Annual Hawaii International Conference on System Sciences",

publisher = "IEEE Computer Society",

pages = "2981--2990",

editor = "Bui, \{Tung X.\}",

booktitle = "Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020",

address = "United States",

}

Alamri, A, AlOwaifeer, M & Meliopoulos, APS 2020, Analytical method for energy storage sizing and reliability assessment for power systems with variable generation. in TX Bui (ed.), Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020. Proceedings of the Annual Hawaii International Conference on System Sciences, vol. 2020-January, IEEE Computer Society, pp. 2981-2990.

Analytical method for energy storage sizing and reliability assessment for power systems with variable generation. / Alamri, Abdullah; AlOwaifeer, Maad; Meliopoulos, A. P.Sakis.
Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020. ed. / Tung X. Bui. IEEE Computer Society, 2020. p. 2981-2990 (Proceedings of the Annual Hawaii International Conference on System Sciences; Vol. 2020-January).

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

TY - GEN

T1 - Analytical method for energy storage sizing and reliability assessment for power systems with variable generation

AU - Alamri, Abdullah

AU - AlOwaifeer, Maad

AU - Meliopoulos, A. P.Sakis

PY - 2020

Y1 - 2020

N2 - This paper presents a mixed integer linear program (MILP) to optimally size power and energy of energy storage systems (ESSs). The sizing model takes into account conventional generation (CG) operation constraints in addition to seasonal and locational wind speed and solar radiation variations, and variable generation (wind turbine systems (WTSs) and solar cell generators (SCGs)) forced outages. Subsequently, the outcomes of the ESS sizing model are inputted to the probabilistic production method (PCC) to assess the reliability of the integrated system. All aforementioned analyses have been applied to a system with different penetration levels. The method is demonstrated with case studies on a system consisting of 10 CG units and VG penetration levels of 20% and 30%. For each penetration level, ESS sizing is computed and then reliability assessment is performed.

AB - This paper presents a mixed integer linear program (MILP) to optimally size power and energy of energy storage systems (ESSs). The sizing model takes into account conventional generation (CG) operation constraints in addition to seasonal and locational wind speed and solar radiation variations, and variable generation (wind turbine systems (WTSs) and solar cell generators (SCGs)) forced outages. Subsequently, the outcomes of the ESS sizing model are inputted to the probabilistic production method (PCC) to assess the reliability of the integrated system. All aforementioned analyses have been applied to a system with different penetration levels. The method is demonstrated with case studies on a system consisting of 10 CG units and VG penetration levels of 20% and 30%. For each penetration level, ESS sizing is computed and then reliability assessment is performed.

UR - https://www.scopus.com/pages/publications/85108170146

M3 - Conference contribution

AN - SCOPUS:85108170146

T3 - Proceedings of the Annual Hawaii International Conference on System Sciences

SP - 2981

EP - 2990

BT - Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020

A2 - Bui, Tung X.

PB - IEEE Computer Society

ER -

Alamri A, AlOwaifeer M, Meliopoulos APS. Analytical method for energy storage sizing and reliability assessment for power systems with variable generation. In Bui TX, editor, Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020. IEEE Computer Society. 2020. p. 2981-2990. (Proceedings of the Annual Hawaii International Conference on System Sciences).

Analytical method for energy storage sizing and reliability assessment for power systems with variable generation

Abstract

Publication series

Bibliographical note

UN SDGs

ASJC Scopus subject areas

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Cite this