可再生能源发电量和负荷分布不均的区域电力系统统一多目标优化

IF 1.8 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Long Zhao, Xiangfei Meng, Lichao Yang, Jia Wei
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引用次数: 1

摘要

可再生能源分布不均的大型电力系统的优化是参与子网协同运行的一项重要而紧迫的任务。本文提出了一种利用统一多目标优化(MOO)将不同策略集成到综合问题中的新方法。为此,首先建立了描述每个子电网需求的个体最优模型。总体目标在经济成本方面是统一的。这种统一在不损失通用性的情况下集成评估不同的优化结果。全局目标是个体目标与经验系数的加权和。因此,可以同时解决子网格之间的内部耦合限制和影响。最后,通过根据偏好需求调整相应的权重,优化的解决方案可以有效地在所有子电网中分配可再生能源。因此,可以最大限度地满足个人和全球需求。所提出的统一MOO在基于多个修改的PJM 9总线网格的配置系统上进行了测试。满足多区域联合系统的全局最优,系统总成本增加15.1%,工业区成本增加21.4%,居民甩负荷损失成本增加27.3%。尽管每个区域都必须牺牲其部分利益,但折衷的运营行为确保了总成本最优。数值结果验证了实现有希望的全局最优解的有效性,以及满足不同子网格要求的灵活性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Unified multi-objective optimization for regional power systems with unequal distribution of renewable energy generation and load

Unified multi-objective optimization for regional power systems with unequal distribution of renewable energy generation and load

The optimization for large-scale power systems with unequal renewable energy distribution is an important and urgent task to collaborate operations of the participated sub-grids. This article proposes a novel method by utilizing the unified multi-objective optimization (MOO) to integrate diverse strategies to a comprehensive problem. For this aim, individual optimal model is first established to describe the demands of each sub-grid. The overall objectives are unified in terms of economy costs. This unification integrates evaluate different optimized results without loss of generality. The global objective is the weighted sum of the individual objectives with empirical coefficient. Thus, the internal coupled restrictions and influences among sub-grids can be solved simultaneously. Finally, by adjusting the corresponding weights according to the preferred requirement, the optimized solution can effectively allocate renewable energy throughout all sub-grids. Consequently, both individual and global requirements can be met at utmost. The proposed unified MOO is tested on the configured systems based on multiple modified PJM 9-bus grids. Satisfying the global optimum of the multi-region joint system, the total system cost increases by 15.1%, the industrial zone cost increases by 21.4%, and the residential load shedding loss cost increases by 27.3%. Although each region has to sacrifice some of its benefits, the compromise operational behavior ensures that the total cost is optimal. Numerical results verify the effectiveness in achieving the promising global optimal solution, and the flexibility in meeting the requirements of different sub-grids.

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CiteScore
5.10
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