Economic Dispatch Strategy for Wind‐Storage Power Plants Considering Multiple Working Conditions under Spot Electricity Prices

To enhance the profitability of wind storage power stations under spot electricity pricing, an initial step involves establishing a foundational optimal scheduling model specific to these conditions. Subsequently, this model is refined to incorporate the operational states commonly encountered, such as power restrictions, load protocol power supply, and power assessments at the grid connection point. Each scenario's optimal scheduling model is meticulously developed to address these variables. Utilizing data from a wind power storage station located in northwest China, the commercial solvers are employed to derive the optimal scheduling solutions and evaluate the financial performance under various scenarios. The findings reveal that, compared to the scenario without energy storage as a benchmark, model optimization yields a revenue increase of 9.54% under spot pricing. Moreover, when accounting for the centralized energy storage grid connected end power restriction, distributed energy storage grid connected end power restriction, load protocol power supply, and power assessments, the revenue enhancements are 6.11%, 6.74%, 7.31%, and 10.56%, respectively. This study demonstrates that by mitigating the adverse impacts of these diverse operational conditions, a substantial improvement in the overall financial returns of wind storage power stations can be achieved. © 2026 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

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Publication Details

Journal
IEEJ Transactions on Electrical and Electronic Engineering
Published
2026-01-15
DOI
https://doi.org/10.1002/tee.70238
Primary Topic
Electric Power System Optimization
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article
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article

Economic Dispatch Strategy for Wind‐Storage Power Plants Considering Multiple Working Conditions under Spot Electricity Prices

Naying Wei, Xu Chen, Jia Cao, Yongcan Zhu et al.
IEEJ Transactions on Electrical and Electronic Engineering
Electric Power System Optimization
article

Economic Dispatch Strategy for Wind‐Storage Power Plants Considering Multiple Working Conditions under Spot Electricity Prices

Naying Wei, Xu Chen, Jia Cao, Yongcan Zhu, Jingyu Mu, Xinru Dang
article en

Abstract

To enhance the profitability of wind storage power stations under spot electricity pricing, an initial step involves establishing a foundational optimal scheduling model specific to these conditions. Subsequently, this model is refined to incorporate the operational states commonly encountered, such as power restrictions, load protocol power supply, and power assessments at the grid connection point. Each scenario's optimal scheduling model is meticulously developed to address these variables. Utilizing data from a wind power storage station located in northwest China, the commercial solvers are employed to derive the optimal scheduling solutions and evaluate the financial performance under various scenarios. The findings reveal that, compared to the scenario without energy storage as a benchmark, model optimization yields a revenue increase of 9.54% under spot pricing. Moreover, when accounting for the centralized energy storage grid connected end power restriction, distributed energy storage grid connected end power restriction, load protocol power supply, and power assessments, the revenue enhancements are 6.11%, 6.74%, 7.31%, and 10.56%, respectively. This study demonstrates that by mitigating the adverse impacts of these diverse operational conditions, a substantial improvement in the overall financial returns of wind storage power stations can be achieved. © 2026 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

IEEJ Transactions on Electrical and Electronic Engineering
Xi'an Polytechnic University (CN), Inner Mongolia Electric Power (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 87%
Electric Power System Optimization
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Economic Dispatch Strategy for Wind‐Storage Power Plants Considering Multiple Working Conditions under Spot Electricity Prices — Naying Wei, Xu Chen, et al. · IEEJ Transactions on Electrical and Electronic Engineering (2026) | TGRS Research Map | TGRS