Demand Response Strategy Considering Industrial Loads and Energy Storage with High Proportion of Wind-Power Integration

To address the challenges of reduced grid stability and wind curtailment caused by high penetration of wind energy, this paper proposes a demand response strategy that considers industrial loads and energy storage under high wind-power integration. Firstly, the adjustable characteristics of controll...

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Main Authors: Chongyi Tian, Julin Li, Chunyu Wang, Longlong Lin, Yi Yan
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/24/22/7335
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author Chongyi Tian
Julin Li
Chunyu Wang
Longlong Lin
Yi Yan
author_facet Chongyi Tian
Julin Li
Chunyu Wang
Longlong Lin
Yi Yan
author_sort Chongyi Tian
collection DOAJ
description To address the challenges of reduced grid stability and wind curtailment caused by high penetration of wind energy, this paper proposes a demand response strategy that considers industrial loads and energy storage under high wind-power integration. Firstly, the adjustable characteristics of controllable resources in the power system are analyzed, and a demand response scheduling framework based on energy storage systems and industrial loads is established. Building on this foundation, a multi-scenario stochastic programming approach is employed to develop a day-ahead and intra-day multi-time-scale optimization scheduling model, aimed at maximizing economic benefits. In response to the challenges of wind-power fluctuations with high temporal resolution, a strategy for smoothing intra-day wind-power variability is further proposed. Finally, simulations are conducted to derive optimal demand response strategies for different stages. As verified by the comparison of different scheduling strategies, the demand response strategy proposed in this paper can reduce wind curtailment when there is sufficient wind power and reduce load shedding when there is insufficient wind power, which effectively reduces the system operation cost.
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institution OA Journals
issn 1424-8220
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publishDate 2024-11-01
publisher MDPI AG
record_format Article
series Sensors
spelling doaj-art-10c15c186f9a4b8bbc83f1f11bcc6d762025-08-20T01:54:08ZengMDPI AGSensors1424-82202024-11-012422733510.3390/s24227335Demand Response Strategy Considering Industrial Loads and Energy Storage with High Proportion of Wind-Power IntegrationChongyi Tian0Julin Li1Chunyu Wang2Longlong Lin3Yi Yan4Shandong Key Laboratory of Smart Buildings and Energy Efficiency, School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, ChinaShandong Key Laboratory of Smart Buildings and Energy Efficiency, School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, ChinaShandong Key Laboratory of Smart Buildings and Energy Efficiency, School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, ChinaShandong Key Laboratory of Smart Buildings and Energy Efficiency, School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, ChinaShandong Key Laboratory of Smart Buildings and Energy Efficiency, School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, ChinaTo address the challenges of reduced grid stability and wind curtailment caused by high penetration of wind energy, this paper proposes a demand response strategy that considers industrial loads and energy storage under high wind-power integration. Firstly, the adjustable characteristics of controllable resources in the power system are analyzed, and a demand response scheduling framework based on energy storage systems and industrial loads is established. Building on this foundation, a multi-scenario stochastic programming approach is employed to develop a day-ahead and intra-day multi-time-scale optimization scheduling model, aimed at maximizing economic benefits. In response to the challenges of wind-power fluctuations with high temporal resolution, a strategy for smoothing intra-day wind-power variability is further proposed. Finally, simulations are conducted to derive optimal demand response strategies for different stages. As verified by the comparison of different scheduling strategies, the demand response strategy proposed in this paper can reduce wind curtailment when there is sufficient wind power and reduce load shedding when there is insufficient wind power, which effectively reduces the system operation cost.https://www.mdpi.com/1424-8220/24/22/7335wind-power consumptionindustrial loadshybrid energy storagemultiple time scalesenergy management
spellingShingle Chongyi Tian
Julin Li
Chunyu Wang
Longlong Lin
Yi Yan
Demand Response Strategy Considering Industrial Loads and Energy Storage with High Proportion of Wind-Power Integration
Sensors
wind-power consumption
industrial loads
hybrid energy storage
multiple time scales
energy management
title Demand Response Strategy Considering Industrial Loads and Energy Storage with High Proportion of Wind-Power Integration
title_full Demand Response Strategy Considering Industrial Loads and Energy Storage with High Proportion of Wind-Power Integration
title_fullStr Demand Response Strategy Considering Industrial Loads and Energy Storage with High Proportion of Wind-Power Integration
title_full_unstemmed Demand Response Strategy Considering Industrial Loads and Energy Storage with High Proportion of Wind-Power Integration
title_short Demand Response Strategy Considering Industrial Loads and Energy Storage with High Proportion of Wind-Power Integration
title_sort demand response strategy considering industrial loads and energy storage with high proportion of wind power integration
topic wind-power consumption
industrial loads
hybrid energy storage
multiple time scales
energy management
url https://www.mdpi.com/1424-8220/24/22/7335
work_keys_str_mv AT chongyitian demandresponsestrategyconsideringindustrialloadsandenergystoragewithhighproportionofwindpowerintegration
AT julinli demandresponsestrategyconsideringindustrialloadsandenergystoragewithhighproportionofwindpowerintegration
AT chunyuwang demandresponsestrategyconsideringindustrialloadsandenergystoragewithhighproportionofwindpowerintegration
AT longlonglin demandresponsestrategyconsideringindustrialloadsandenergystoragewithhighproportionofwindpowerintegration
AT yiyan demandresponsestrategyconsideringindustrialloadsandenergystoragewithhighproportionofwindpowerintegration