A computational method for optimizing storage placement to maximize power network reliability

Debarati Bhaumik; Daan Crommelin; Bert Zwart

doi:10.1109/WSC.2016.7822150

A computational method for optimizing storage placement to maximize power network reliability

Debarati Bhaumik, Daan Crommelin, Bert Zwart

Stochastic Operations Research

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

5 Citations (Scopus)

Abstract

The intermittent nature of renewable energy sources challenges the power network reliability. However, these challenges can be alleviated by incorporating energy storage devices into the network. We develop a computational technique which can find the optimal storage placement in the network with stochastic power injections, subject to minimizing a reliability index: The probability of a line current violation. We use the simulated annealing algorithm to minimize this probability under the variation of storage locations and capacities in the network, keeping the total storage capacity constant. In order to estimate the small probabilities of line current violations we use the splitting technique of rare-event simulation. We construct an appropriate importance function for splitting which enhances the efficiency of the probability estimator compared to the conventional Crude Monte Carlo estimator. As an illustration, we apply our method to the IEEE-14 bus network.

Original language	English
Title of host publication	2016 Winter Simulation Conference
Subtitle of host publication	Simulating Complex Service Systems, WSC 2016
Editors	Theresa M. Roeder, Peter I. Frazier, Robert Szechtman, Enlu Zhou
Publisher	Institute of Electrical and Electronics Engineers
Pages	883-894
Number of pages	12
ISBN (Electronic)	9781509044863
DOIs	https://doi.org/10.1109/WSC.2016.7822150
Publication status	Published - 2 Jul 2016
Event	2016 Winter Simulation Conference, WSC 2016 - Washington, D.C., Arlington, United States Duration: 11 Dec 2016 → 14 Dec 2016 http://informs-sim.org/wsc16papers/by_area.html

Conference

Conference	2016 Winter Simulation Conference, WSC 2016
Abbreviated title	WSC 2016
Country/Territory	United States
City	Arlington
Period	11/12/16 → 14/12/16
Internet address	http://informs-sim.org/wsc16papers/by_area.html

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

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

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10.1109/WSC.2016.7822150

Cite this

Bhaumik, D., Crommelin, D., & Zwart, B. (2016). A computational method for optimizing storage placement to maximize power network reliability. In T. M. Roeder, P. I. Frazier, R. Szechtman, & E. Zhou (Eds.), 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016 (pp. 883-894). Article 7822150 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/WSC.2016.7822150

Bhaumik, Debarati ; Crommelin, Daan ; Zwart, Bert. / A computational method for optimizing storage placement to maximize power network reliability. 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016. editor / Theresa M. Roeder ; Peter I. Frazier ; Robert Szechtman ; Enlu Zhou. Institute of Electrical and Electronics Engineers, 2016. pp. 883-894

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abstract = "The intermittent nature of renewable energy sources challenges the power network reliability. However, these challenges can be alleviated by incorporating energy storage devices into the network. We develop a computational technique which can find the optimal storage placement in the network with stochastic power injections, subject to minimizing a reliability index: The probability of a line current violation. We use the simulated annealing algorithm to minimize this probability under the variation of storage locations and capacities in the network, keeping the total storage capacity constant. In order to estimate the small probabilities of line current violations we use the splitting technique of rare-event simulation. We construct an appropriate importance function for splitting which enhances the efficiency of the probability estimator compared to the conventional Crude Monte Carlo estimator. As an illustration, we apply our method to the IEEE-14 bus network.",

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Bhaumik, D, Crommelin, D & Zwart, B 2016, A computational method for optimizing storage placement to maximize power network reliability. in TM Roeder, PI Frazier, R Szechtman & E Zhou (eds), 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016., 7822150, Institute of Electrical and Electronics Engineers, pp. 883-894, 2016 Winter Simulation Conference, WSC 2016, Arlington, District of Columbia, United States, 11/12/16. https://doi.org/10.1109/WSC.2016.7822150

A computational method for optimizing storage placement to maximize power network reliability. / Bhaumik, Debarati; Crommelin, Daan; Zwart, Bert.
2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016. ed. / Theresa M. Roeder; Peter I. Frazier; Robert Szechtman; Enlu Zhou. Institute of Electrical and Electronics Engineers, 2016. p. 883-894 7822150.

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

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AB - The intermittent nature of renewable energy sources challenges the power network reliability. However, these challenges can be alleviated by incorporating energy storage devices into the network. We develop a computational technique which can find the optimal storage placement in the network with stochastic power injections, subject to minimizing a reliability index: The probability of a line current violation. We use the simulated annealing algorithm to minimize this probability under the variation of storage locations and capacities in the network, keeping the total storage capacity constant. In order to estimate the small probabilities of line current violations we use the splitting technique of rare-event simulation. We construct an appropriate importance function for splitting which enhances the efficiency of the probability estimator compared to the conventional Crude Monte Carlo estimator. As an illustration, we apply our method to the IEEE-14 bus network.

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Bhaumik D, Crommelin D, Zwart B. A computational method for optimizing storage placement to maximize power network reliability. In Roeder TM, Frazier PI, Szechtman R, Zhou E, editors, 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016. Institute of Electrical and Electronics Engineers. 2016. p. 883-894. 7822150 doi: 10.1109/WSC.2016.7822150

A computational method for optimizing storage placement to maximize power network reliability

Abstract

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Bibliographical note

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