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A distributed optimization method for wind-storage systems with superlinear convergence
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DOI：10.1016/j.est.2026.121035.png)
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Abstract
En 中文
• A bi-level distributed energy storage system optimization model is developed to coordinate global power dispatch with local objectives, including life-cycle cost and relative carbon payback period. • The relative carbon payback period is formulated via a high-order Taylor series expansion to capture the time-varying nature of carbon intensity. • An optimal control-based distributed optimization method is proposed to efficiently solve the high-order model with low communication cost. • Comparative results demonstrate higher solution accuracy, shorter computation time, and better adaptability to complex wind-storage systems.
Keywords:
distributed optimization
wind-storage systems
life-cycle cost
carbon payback period
high-order Taylor series
Journal
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9.8
Papers:
2.2W
Citations:
10.1W