Chance-constrained two-stage energy hub cluster configuration for integrated demand response considering multi-energy load uncertainty

Jingdong Wei; Yao Zhang; Jianxue Wang; Lei Wu; Qingtao Li

doi:10.1109/PESGM41954.2020.9282018

Chance-constrained two-stage energy hub cluster configuration for integrated demand response considering multi-energy load uncertainty

Jingdong Wei
, Yao Zhang
, Jianxue Wang
, Lei Wu
, Qingtao Li

Department of Electrical and Computer Engineering

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

3 Scopus citations

Abstract

In this paper, we study the configuration problem of Energy Hub cluster for integrated demand response (IDR) while considering multi-energy load (i.e., electricity/heat load) uncertainty. We first present a chance-constrained two-stage model for energy hub cluster configuration based on bilinear reformulation using a finite number of stochastic scenarios. Then, bilinear terms are exactly linearized to derive a mixed integer linear programming (MILP) model. Finally, the bilinear Benders decomposition (BBD) algorithm is utilized to compute the proposed MILP model. Numerical results demonstrate that our proposed model can effectively manage the multi-energy load uncertainty for energy hub cluster configuration and improve the performance of IDR. BBD algorithm is also computationally efficient than commercial solvers (such as CPLEX).

Original language	English
Title of host publication	2020 IEEE Power and Energy Society General Meeting, PESGM 2020
ISBN (Electronic)	9781728155081
DOIs	https://doi.org/10.1109/PESGM41954.2020.9282018
State	Published - 2 Aug 2020
Event	2020 IEEE Power and Energy Society General Meeting, PESGM 2020 - Montreal, Canada Duration: 2 Aug 2020 → 6 Aug 2020

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2020-August
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2020 IEEE Power and Energy Society General Meeting, PESGM 2020
Country/Territory	Canada
City	Montreal
Period	2/08/20 → 6/08/20

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Bilinear Benders Decomposition
Chance constraint
Energy Hub
Integrated Demand Response
Load Uncertaitny

Access to Document

10.1109/PESGM41954.2020.9282018

Cite this

Wei, J., Zhang, Y., Wang, J., Wu, L., & Li, Q. (2020). Chance-constrained two-stage energy hub cluster configuration for integrated demand response considering multi-energy load uncertainty. In 2020 IEEE Power and Energy Society General Meeting, PESGM 2020 Article 9282018 (IEEE Power and Energy Society General Meeting; Vol. 2020-August). https://doi.org/10.1109/PESGM41954.2020.9282018

@inproceedings{832e28b3f4b64030a019a4855d8e6222,

title = "Chance-constrained two-stage energy hub cluster configuration for integrated demand response considering multi-energy load uncertainty",

abstract = "In this paper, we study the configuration problem of Energy Hub cluster for integrated demand response (IDR) while considering multi-energy load (i.e., electricity/heat load) uncertainty. We first present a chance-constrained two-stage model for energy hub cluster configuration based on bilinear reformulation using a finite number of stochastic scenarios. Then, bilinear terms are exactly linearized to derive a mixed integer linear programming (MILP) model. Finally, the bilinear Benders decomposition (BBD) algorithm is utilized to compute the proposed MILP model. Numerical results demonstrate that our proposed model can effectively manage the multi-energy load uncertainty for energy hub cluster configuration and improve the performance of IDR. BBD algorithm is also computationally efficient than commercial solvers (such as CPLEX).",

keywords = "Bilinear Benders Decomposition, Chance constraint, Energy Hub, Integrated Demand Response, Load Uncertaitny",

author = "Jingdong Wei and Yao Zhang and Jianxue Wang and Lei Wu and Qingtao Li",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE Power and Energy Society General Meeting, PESGM 2020 ; Conference date: 02-08-2020 Through 06-08-2020",

year = "2020",

month = aug,

day = "2",

doi = "10.1109/PESGM41954.2020.9282018",

language = "English",

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

booktitle = "2020 IEEE Power and Energy Society General Meeting, PESGM 2020",

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Wei, J, Zhang, Y, Wang, J, Wu, L & Li, Q 2020, Chance-constrained two-stage energy hub cluster configuration for integrated demand response considering multi-energy load uncertainty. in 2020 IEEE Power and Energy Society General Meeting, PESGM 2020., 9282018, IEEE Power and Energy Society General Meeting, vol. 2020-August, 2020 IEEE Power and Energy Society General Meeting, PESGM 2020, Montreal, Canada, 2/08/20. https://doi.org/10.1109/PESGM41954.2020.9282018

Chance-constrained two-stage energy hub cluster configuration for integrated demand response considering multi-energy load uncertainty. / Wei, Jingdong; Zhang, Yao; Wang, Jianxue et al.
2020 IEEE Power and Energy Society General Meeting, PESGM 2020. 2020. 9282018 (IEEE Power and Energy Society General Meeting; Vol. 2020-August).

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

TY - GEN

T1 - Chance-constrained two-stage energy hub cluster configuration for integrated demand response considering multi-energy load uncertainty

AU - Wei, Jingdong

AU - Zhang, Yao

AU - Wang, Jianxue

AU - Wu, Lei

AU - Li, Qingtao

PY - 2020/8/2

Y1 - 2020/8/2

N2 - In this paper, we study the configuration problem of Energy Hub cluster for integrated demand response (IDR) while considering multi-energy load (i.e., electricity/heat load) uncertainty. We first present a chance-constrained two-stage model for energy hub cluster configuration based on bilinear reformulation using a finite number of stochastic scenarios. Then, bilinear terms are exactly linearized to derive a mixed integer linear programming (MILP) model. Finally, the bilinear Benders decomposition (BBD) algorithm is utilized to compute the proposed MILP model. Numerical results demonstrate that our proposed model can effectively manage the multi-energy load uncertainty for energy hub cluster configuration and improve the performance of IDR. BBD algorithm is also computationally efficient than commercial solvers (such as CPLEX).

AB - In this paper, we study the configuration problem of Energy Hub cluster for integrated demand response (IDR) while considering multi-energy load (i.e., electricity/heat load) uncertainty. We first present a chance-constrained two-stage model for energy hub cluster configuration based on bilinear reformulation using a finite number of stochastic scenarios. Then, bilinear terms are exactly linearized to derive a mixed integer linear programming (MILP) model. Finally, the bilinear Benders decomposition (BBD) algorithm is utilized to compute the proposed MILP model. Numerical results demonstrate that our proposed model can effectively manage the multi-energy load uncertainty for energy hub cluster configuration and improve the performance of IDR. BBD algorithm is also computationally efficient than commercial solvers (such as CPLEX).

KW - Bilinear Benders Decomposition

KW - Chance constraint

KW - Energy Hub

KW - Integrated Demand Response

KW - Load Uncertaitny

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U2 - 10.1109/PESGM41954.2020.9282018

DO - 10.1109/PESGM41954.2020.9282018

M3 - Conference contribution

AN - SCOPUS:85099137710

T3 - IEEE Power and Energy Society General Meeting

BT - 2020 IEEE Power and Energy Society General Meeting, PESGM 2020

T2 - 2020 IEEE Power and Energy Society General Meeting, PESGM 2020

Y2 - 2 August 2020 through 6 August 2020

ER -

Chance-constrained two-stage energy hub cluster configuration for integrated demand response considering multi-energy load uncertainty

Abstract

Publication series

Conference

UN SDGs

Keywords

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