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    基于模糊优化的多场景风光火储优化调度

    Multi-scenario Wind-Solar-Thermal-Storage Optimal Scheduling Based on Fuzzy Optimization

    • 摘要: 为了减少风光出力不确定性给电力系统优化调度带来的影响,构建了风光火储调度模型,使用场景法分别生成丰能季与枯能季典型日作为调度数据基础,并结合模糊优化方法进行优化调度。对比了不同置信水平与模糊隶属度下模型成本与备用容量之间的关系。算例验证了模糊优化与多场景调度提升了系统的稳定性与新能源消纳率。结果表明:所提优化调度方法可使新能源消纳率提高4.6%,同时调度运行成本降低2.5万元,系统稳定性有所提升。

       

      Abstract: To mitigate the impact of the uncertainty in wind and solar power output on power system optimal scheduling, a scheduling model integrating wind, solar, thermal and storage resources was constructed. The scenario method was employed to generate typical days for both high-energy and low-energy seasons as the scheduling data basis, and fuzzy optimization method was applied for optimal scheduling. The relationship between model cost and reserve capacity under different confidence levels and fuzzy membership degrees was compared. Case studies demonstrated that fuzzy optimization and multi-scenario scheduling enhanced system stability and the accommodation rate of renewable energy. The results show that the proposed optimal scheduling method increases renewable energy accommodation rate by 4.6%, reduces scheduling and operational costs by 25 000 yuan, and improves system stability.

       

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