Distributed Tracking-ADMM Approach for Chance-Constrained Energy Management with Stochastic Wind Power

This paper proposes a distributed strategy to the chance-constrained energy management for smart grid with penetration of stochastic wind power. This energy management model is constructed including chance constraints of spinning reserves for the sake of guaranteeing the maximum utilization of wind...

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Main Authors: Wenjuan Li, Yungang Liu, Huijun Liang, Yongchao Man, Fengzhong Li
Format: Article
Language:English
Published: China electric power research institute 2025-01-01
Series:CSEE Journal of Power and Energy Systems
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9606955/
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author Wenjuan Li
Yungang Liu
Huijun Liang
Yongchao Man
Fengzhong Li
author_facet Wenjuan Li
Yungang Liu
Huijun Liang
Yongchao Man
Fengzhong Li
author_sort Wenjuan Li
collection DOAJ
description This paper proposes a distributed strategy to the chance-constrained energy management for smart grid with penetration of stochastic wind power. This energy management model is constructed including chance constraints of spinning reserves for the sake of guaranteeing the maximum utilization of wind power on the basis of reliability. With the available wind power characterized by Weibull distribution, the chance constraints can be converted into deterministic ones by the derived analytical form of inverse cumulative distribution function. Although the original problem is transformed into a typical convex optimization problem, the tight coupling of constraints presents challenges to the design of distributed strategy. Therefore, we formulate the problem into a compact form with each generator unit depending on individual decision variables, instead of the common form with a decision vector being the collection of all local decision variables. Then, by developing a new initialization method and an adaptive weight matrix selection method, a distributed strategy based on tracking Alternating Direction Method of Multipliers (ADMM) is proposed to solve the model. The simulation results indicate that the proposed distributed strategy achieves comparable performance to the corresponding centralized scenario, and better performance than distributed consensus-based ADMM in the related literature. Moreover, the validity of the proposed distributed strategy is confirmed in day-ahead chance-constrained energy management with stochastic wind power.
format Article
id doaj-art-30403b01b0d64353a2e400939aa76952
institution OA Journals
issn 2096-0042
language English
publishDate 2025-01-01
publisher China electric power research institute
record_format Article
series CSEE Journal of Power and Energy Systems
spelling doaj-art-30403b01b0d64353a2e400939aa769522025-08-20T02:34:15ZengChina electric power research instituteCSEE Journal of Power and Energy Systems2096-00422025-01-011131154116410.17775/CSEEJPES.2021.005409606955Distributed Tracking-ADMM Approach for Chance-Constrained Energy Management with Stochastic Wind PowerWenjuan Li0Yungang Liu1Huijun Liang2Yongchao Man3Fengzhong Li4School of Control Science and Engineering, Shandong University,Jinan,China,250061School of Control Science and Engineering, Shandong University,Jinan,China,250061School of Information Engineering, Hubei Minzu University,Enshi,China,445000School of Control Science and Engineering, Shandong University,Jinan,China,250061School of Control Science and Engineering, Shandong University,Jinan,China,250061This paper proposes a distributed strategy to the chance-constrained energy management for smart grid with penetration of stochastic wind power. This energy management model is constructed including chance constraints of spinning reserves for the sake of guaranteeing the maximum utilization of wind power on the basis of reliability. With the available wind power characterized by Weibull distribution, the chance constraints can be converted into deterministic ones by the derived analytical form of inverse cumulative distribution function. Although the original problem is transformed into a typical convex optimization problem, the tight coupling of constraints presents challenges to the design of distributed strategy. Therefore, we formulate the problem into a compact form with each generator unit depending on individual decision variables, instead of the common form with a decision vector being the collection of all local decision variables. Then, by developing a new initialization method and an adaptive weight matrix selection method, a distributed strategy based on tracking Alternating Direction Method of Multipliers (ADMM) is proposed to solve the model. The simulation results indicate that the proposed distributed strategy achieves comparable performance to the corresponding centralized scenario, and better performance than distributed consensus-based ADMM in the related literature. Moreover, the validity of the proposed distributed strategy is confirmed in day-ahead chance-constrained energy management with stochastic wind power.https://ieeexplore.ieee.org/document/9606955/ADMMchance-constrained energy managementdistributed strategysmart gridstochastic wind power
spellingShingle Wenjuan Li
Yungang Liu
Huijun Liang
Yongchao Man
Fengzhong Li
Distributed Tracking-ADMM Approach for Chance-Constrained Energy Management with Stochastic Wind Power
CSEE Journal of Power and Energy Systems
ADMM
chance-constrained energy management
distributed strategy
smart grid
stochastic wind power
title Distributed Tracking-ADMM Approach for Chance-Constrained Energy Management with Stochastic Wind Power
title_full Distributed Tracking-ADMM Approach for Chance-Constrained Energy Management with Stochastic Wind Power
title_fullStr Distributed Tracking-ADMM Approach for Chance-Constrained Energy Management with Stochastic Wind Power
title_full_unstemmed Distributed Tracking-ADMM Approach for Chance-Constrained Energy Management with Stochastic Wind Power
title_short Distributed Tracking-ADMM Approach for Chance-Constrained Energy Management with Stochastic Wind Power
title_sort distributed tracking admm approach for chance constrained energy management with stochastic wind power
topic ADMM
chance-constrained energy management
distributed strategy
smart grid
stochastic wind power
url https://ieeexplore.ieee.org/document/9606955/
work_keys_str_mv AT wenjuanli distributedtrackingadmmapproachforchanceconstrainedenergymanagementwithstochasticwindpower
AT yungangliu distributedtrackingadmmapproachforchanceconstrainedenergymanagementwithstochasticwindpower
AT huijunliang distributedtrackingadmmapproachforchanceconstrainedenergymanagementwithstochasticwindpower
AT yongchaoman distributedtrackingadmmapproachforchanceconstrainedenergymanagementwithstochasticwindpower
AT fengzhongli distributedtrackingadmmapproachforchanceconstrainedenergymanagementwithstochasticwindpower