Estimation of ESS and DR Requirements Based on Stocastic Reliability Analysis

Yi Syuan Wu; Jian Tang Liao; Hong Tzer Yang

doi:10.1109/PESGM46819.2021.9638010

Estimation of ESS and DR Requirements Based on Stocastic Reliability Analysis

Yi Syuan Wu
, Jian Tang Liao
, Hong Tzer Yang

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

Abstract

Probabilistic models of renewable energy (RE) generation have been adopted to evaluate reliability indices using the Monte Carlo (MC) stochastic simulation method over the past years. However, with an increasing number of new energy sources injected into the future grid, the existing analysis methods are obsolete. This paper integrates the decision operating model of energy storage systems (ESS) and demand response (DR) behavior model into the existing probabilistic reliability analysis method. According to respective ESS owners, ESSs are divided into grid type and user type. Furthermore, the price-incentive DR load model is combined in the method to simulate consumer behaviors. The Taiwan Power system, which is an isolated grid with a 37 GW peak load and expected 20% RE penetration, is employed as a case study. According to the proposed method, the most suitable DR compensation price and ESS installed capacity are analyzed to decrease system investment and maintain system reliability in this paper.

Original language	English
Title of host publication	2021 IEEE Power and Energy Society General Meeting, PESGM 2021
Publisher	IEEE Computer Society
ISBN (Electronic)	9781665405072
DOIs	https://doi.org/10.1109/PESGM46819.2021.9638010
Publication status	Published - 2021
Event	2021 IEEE Power and Energy Society General Meeting, PESGM 2021 - Washington, United States Duration: 2021 Jul 26 → 2021 Jul 29

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2021-July
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2021 IEEE Power and Energy Society General Meeting, PESGM 2021
Country/Territory	United States
City	Washington
Period	21-07-26 → 21-07-29

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

Energy Engineering and Power Technology
Nuclear Energy and Engineering
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering

Access to Document

10.1109/PESGM46819.2021.9638010

Cite this

@inproceedings{76c02c80febd47ca89b9606e958ebd02,

title = "Estimation of ESS and DR Requirements Based on Stocastic Reliability Analysis",

abstract = "Probabilistic models of renewable energy (RE) generation have been adopted to evaluate reliability indices using the Monte Carlo (MC) stochastic simulation method over the past years. However, with an increasing number of new energy sources injected into the future grid, the existing analysis methods are obsolete. This paper integrates the decision operating model of energy storage systems (ESS) and demand response (DR) behavior model into the existing probabilistic reliability analysis method. According to respective ESS owners, ESSs are divided into grid type and user type. Furthermore, the price-incentive DR load model is combined in the method to simulate consumer behaviors. The Taiwan Power system, which is an isolated grid with a 37 GW peak load and expected 20\% RE penetration, is employed as a case study. According to the proposed method, the most suitable DR compensation price and ESS installed capacity are analyzed to decrease system investment and maintain system reliability in this paper.",

author = "Wu, \{Yi Syuan\} and Liao, \{Jian Tang\} and Yang, \{Hong Tzer\}",

note = "Funding Information: This work was supported by the Ministry of Science and Technology, Taiwan, under Grant MOST l09-3116-F-006-017-CC2. Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE Power and Energy Society General Meeting, PESGM 2021 ; Conference date: 26-07-2021 Through 29-07-2021",

year = "2021",

doi = "10.1109/PESGM46819.2021.9638010",

language = "English",

series = "IEEE Power and Energy Society General Meeting",

publisher = "IEEE Computer Society",

booktitle = "2021 IEEE Power and Energy Society General Meeting, PESGM 2021",

address = "United States",

}

Wu, YS, Liao, JT & Yang, HT 2021, Estimation of ESS and DR Requirements Based on Stocastic Reliability Analysis. in 2021 IEEE Power and Energy Society General Meeting, PESGM 2021. IEEE Power and Energy Society General Meeting, vol. 2021-July, IEEE Computer Society, 2021 IEEE Power and Energy Society General Meeting, PESGM 2021, Washington, United States, 21-07-26. https://doi.org/10.1109/PESGM46819.2021.9638010

Estimation of ESS and DR Requirements Based on Stocastic Reliability Analysis. / Wu, Yi Syuan; Liao, Jian Tang; Yang, Hong Tzer.
2021 IEEE Power and Energy Society General Meeting, PESGM 2021. IEEE Computer Society, 2021. (IEEE Power and Energy Society General Meeting; Vol. 2021-July).

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

TY - GEN

T1 - Estimation of ESS and DR Requirements Based on Stocastic Reliability Analysis

AU - Wu, Yi Syuan

AU - Liao, Jian Tang

AU - Yang, Hong Tzer

PY - 2021

Y1 - 2021

N2 - Probabilistic models of renewable energy (RE) generation have been adopted to evaluate reliability indices using the Monte Carlo (MC) stochastic simulation method over the past years. However, with an increasing number of new energy sources injected into the future grid, the existing analysis methods are obsolete. This paper integrates the decision operating model of energy storage systems (ESS) and demand response (DR) behavior model into the existing probabilistic reliability analysis method. According to respective ESS owners, ESSs are divided into grid type and user type. Furthermore, the price-incentive DR load model is combined in the method to simulate consumer behaviors. The Taiwan Power system, which is an isolated grid with a 37 GW peak load and expected 20% RE penetration, is employed as a case study. According to the proposed method, the most suitable DR compensation price and ESS installed capacity are analyzed to decrease system investment and maintain system reliability in this paper.

AB - Probabilistic models of renewable energy (RE) generation have been adopted to evaluate reliability indices using the Monte Carlo (MC) stochastic simulation method over the past years. However, with an increasing number of new energy sources injected into the future grid, the existing analysis methods are obsolete. This paper integrates the decision operating model of energy storage systems (ESS) and demand response (DR) behavior model into the existing probabilistic reliability analysis method. According to respective ESS owners, ESSs are divided into grid type and user type. Furthermore, the price-incentive DR load model is combined in the method to simulate consumer behaviors. The Taiwan Power system, which is an isolated grid with a 37 GW peak load and expected 20% RE penetration, is employed as a case study. According to the proposed method, the most suitable DR compensation price and ESS installed capacity are analyzed to decrease system investment and maintain system reliability in this paper.

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UR - https://www.scopus.com/pages/publications/85124140687#tab=citedBy

U2 - 10.1109/PESGM46819.2021.9638010

DO - 10.1109/PESGM46819.2021.9638010

M3 - Conference contribution

AN - SCOPUS:85124140687

T3 - IEEE Power and Energy Society General Meeting

BT - 2021 IEEE Power and Energy Society General Meeting, PESGM 2021

PB - IEEE Computer Society

T2 - 2021 IEEE Power and Energy Society General Meeting, PESGM 2021

Y2 - 26 July 2021 through 29 July 2021

ER -

Estimation of ESS and DR Requirements Based on Stocastic Reliability Analysis

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

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