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A distributed robust optimization approach for the economic dispatch of flexible resources

机译:灵活资源经济派遣的分布式鲁棒优化方法

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摘要

Power systems are confronted with prodigious challenges of scheduling and operation incurred by the high penetration of distributed renewable energy with intermittency and uncertainty. Therefore, this paper proposes an improved distributed robust optimization approach with self-adaptive step-sizes based on the line search method and a polynomial filter, to minimize the overall costs of flexible resources including conventional generators, energy storage systems, renewable energy curtailments, deferrable loads and fie-line power exchanges, while considering various constraints, such as supply-demand power balance, line congestion constraints and power output limits. Numerical case studies conducted in a modified IEEE 14-bus system and a modified IEEE 118-bus system demonstrate the reliability, robustness and extensibility of the proposed approach. In addition, the effectiveness and accuracy of the proposed distributed robust optimization approach are validated through comparisons with the traditional centralized gradient method and the convergence performance is better in contrast to other distributed optimization algorithm.
机译:电力系统面临着随着分布式可再生能源与间歇性和不确定性的高渗透的调度和运行的促进挑战。因此,本文提出了一种基于线路搜索方法和多项式滤波器的自适应阶梯大小改进的分布式稳健优化方法,以最大限度地减少柔性资源的总成本,包括传统发电机,能量存储系统,可再生能量缩减,可推迟负载和FIE-LINE功率交换,同时考虑各种约束,例如供需功率平衡,线拥塞约束和功率输出限制。在修改的IEEE 14总线系统中进行的数值案例研究和改进的IEEE 118总线系统展示了所提出的方法的可靠性,鲁棒性和可扩展性。此外,通过与传统的集中梯度方法的比较验证了所提出的分布式鲁棒优化方法的有效性和准确性,与其他分布式优化算法相比,收敛性能更好。

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