Quantifying the energy imbalance in hydrogen energy storage-assisted power systems under heat waves

• Modeling the impacts of heatwaves on renewable generation, temperature-sensitive load, and line thermal ratings. • Incorporating the decision-dependent uncertainty in demand response into energy balance quantification. • A quantification model for the heatwave-induced energy imbalance based on two-stage stochastic framework. • A quantification model for determining the Hydrogen amount to the proactively pre-stored before the heatwaves. • An efficient solution method based on Benders decomposition to solve the problem. The increasing occurrence frequency of extreme temperature events, e.g., heat and cold waves, causes prolonged periods of low renewable production and increased load demand, threatening the power system energy balance. In this context, this paper proposes to quantify the energy imbalance in long-duration Hydrogen energy storage (HES)-assisted power systems under heat waves (HWs). First, we comprehensively model how HWs impact the operating characteristics of multiple grid components, including renewable generation, load, and dynamic thermal rating of transmission lines. Both exogenous prediction information and decision-dependent uncertainties (DDU) in demand response (DR) are properly modeled and taken into account. On this basis, we establish a quantification model for evaluating future energy imbalance in the presence of upcoming HWs in a two-stage stochastic framework, where the first stage determines the Hydrogen amount to be pre-stored before the heatwave, and the second stage comprises scenario-wise operation during the heatwave considering impacts of heatwaves on multiple components, DR, and available energy storage from HES. A Benders decomposition-based solution method is presented for the established two-stage stochastic model with DDU and mixed-binary recourse. Case studies on modified IEEE-6 bus and 118-bus systems verify the proposed model and solution method. Case study results show that the energy imbalance and operation costs due to HWs can be effectively decreased by pre-storing Hydrogen, implementing DDU-featured DR, and preserving more generator reserve capacity.

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Publication Details

Journal
International Journal of Electrical Power & Energy Systems
Published
2024-12-26
DOI
https://doi.org/10.1016/j.ijepes.2024.110434
Citations
2
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.42
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article

Quantifying the energy imbalance in hydrogen energy storage-assisted power systems under heat waves

Wenqian Yin, Jilei Ye, Peng Kong, Pengcheng Fan et al.
2 citations
International Journal of Electrical Power & Energy Systems
Integrated Energy Systems Optimization
0.42
article

Quantifying the energy imbalance in hydrogen energy storage-assisted power systems under heat waves

Wenqian Yin, Jilei Ye, Peng Kong, Pengcheng Fan, Xun Dou, Yuping Wu, Kun Zhuang
article en
2 citations

Abstract

• Modeling the impacts of heatwaves on renewable generation, temperature-sensitive load, and line thermal ratings. • Incorporating the decision-dependent uncertainty in demand response into energy balance quantification. • A quantification model for the heatwave-induced energy imbalance based on two-stage stochastic framework. • A quantification model for determining the Hydrogen amount to the proactively pre-stored before the heatwaves. • An efficient solution method based on Benders decomposition to solve the problem. The increasing occurrence frequency of extreme temperature events, e.g., heat and cold waves, causes prolonged periods of low renewable production and increased load demand, threatening the power system energy balance. In this context, this paper proposes to quantify the energy imbalance in long-duration Hydrogen energy storage (HES)-assisted power systems under heat waves (HWs). First, we comprehensively model how HWs impact the operating characteristics of multiple grid components, including renewable generation, load, and dynamic thermal rating of transmission lines. Both exogenous prediction information and decision-dependent uncertainties (DDU) in demand response (DR) are properly modeled and taken into account. On this basis, we establish a quantification model for evaluating future energy imbalance in the presence of upcoming HWs in a two-stage stochastic framework, where the first stage determines the Hydrogen amount to be pre-stored before the heatwave, and the second stage comprises scenario-wise operation during the heatwave considering impacts of heatwaves on multiple components, DR, and available energy storage from HES. A Benders decomposition-based solution method is presented for the established two-stage stochastic model with DDU and mixed-binary recourse. Case studies on modified IEEE-6 bus and 118-bus systems verify the proposed model and solution method. Case study results show that the energy imbalance and operation costs due to HWs can be effectively decreased by pre-storing Hydrogen, implementing DDU-featured DR, and preserving more generator reserve capacity.

International Journal of Electrical Power & Energy SystemsVol. 164
Nanjing Tech University (CN)
Affordable and clean energy
Openalex Percentile: Top 36%
Integrated Energy Systems Optimization
0.42
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