Evaluating Solar–Wind Complementarity Metrics for Enhanced Load Matching in Day-Ahead Scheduling

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Authors: Shutao Zhou, Yufeng Guo, Dazhi Yang, Junci Tang, Yihang Ouyang, Wei Xu, Dipti Srinivasan
Cited by: 1

Abstract

Leveraging the complementarity of solar and wind power is key for firming up renewable output. However, traditional metrics designed to smooth generation-side fluctuations fail to reflect the full value of complementarity from a system scheduling perspective. This work proposes a novel complementarity metric to evaluate how well blended wind and solar generation matches load demand. Furthermore, to support practical scheduling optimization, a typical-day selection method is developed based on the meteorology–generation–load interactive features, ensuring the diversity and coverage of the constructed scenarios. Experiments show that the proposed metric accurately quantifies the complementarity between wind and solar generation and load demand, effectively capturing the temporal patterns of the net load fluctuations. Incorporating the optimized complementarity metric into day-ahead scheduling enables the system to achieve better load matching, reduced regulation pressure on conventional units, and higher overall system flexibility.

Fields of Study & Subjects

Integrated Energy Systems Optimization Electric Power System Optimization Smart Grid Energy Management

Publication details

Journal / source
IEEE Transactions on Sustainable Energy
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
17
Issue
3
Pages
2420–2432
Publication date
12 January 2026