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Keywords

cost optimization; power scheduling; nonlinear programming

Abstract

In power systems with large amounts of renewable energy and high variability, conventional scheduling methods cannot adequately accommodate the effects of the above variability. A scheduling optimization method is proposed to evaluate the optimal unit participation factor by considering the variability of solar, wind, and load demand. Both sequential and dynamic models are used, and variability and uncertainty costs are considered in the optimization process. Since the participation factor fitting function is optimized only once at the beginning of the scheduling interval, the dimensions of the proposed scheduling optimization model are the same as those of the conventional method. The simulation analysis results show that compared with that of the traditional sequential method, the cost of the proposed dynamic method is reduced by 3.6%, which verifies the effectiveness of the proposed method.

DOI

10.19781/j.issn.1673-9140.2025.03.018

First Page

163

Last Page

173

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