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Incorporating Massive Scenarios in Transmission Expansion Planning with High Renewable Energy Penetration
IEEE Transactions on Power Systems ( IF 6.5 ) Pub Date : 2020-03-01 , DOI: 10.1109/tpwrs.2019.2938618
Zhenyu Zhuo , Ershun Du , Ning Zhang , Chongqing Kang , Qing Xia , Zhidong Wang

High renewable energy penetration profoundly increases the diversity of operating statuses for the power system. Therefore, massive operating scenarios need to be considered in transmission expansion planning (TEP) to fully reflect the impact of renewable energy on power system operation. Usually, representative scenarios need to be selected to reduce the computational burden of TEP. However, the impact of abandoning many scenarios is unclear because investment decisions are highly non-linear with respect to the input scenarios. In this paper, we propose a TEP model to effectively consider massive scenarios without reduction. We use Benders decomposition to divide the TEP problem into an investment master problem and many operation subproblems. Multiple parametric linear programming (MPLP) is applied to cluster the operation subproblems in each iteration. Here, only one operation subproblem needs to be solved in each cluster, and the results of other subproblems in the same cluster can be analytically obtained. The clustering process is objective-based and self-updated dynamically during each iteration so that the effects of all the scenarios on investment decisions are considered. The efficiency improvement and effectiveness of the proposed method are illustrated through case studies on the modified Garver's 6-bus, IEEE RTS-79, IEEE RTS-96, and realistic-sized test system.

中文翻译:

将海量场景纳入可再生能源高渗透率的输电扩建规划

可再生能源的高渗透率极大地增加了电力系统运行状态的多样性。因此,输电扩容规划(TEP)需要考虑海量运行场景,充分体现可再生能源对电力系统运行的影响。通常,需要选择具有代表性的场景来减少 TEP 的计算负担。然而,放弃许多情景的影响尚不清楚,因为投资决策相对于输入情景是高度非线性的。在本文中,我们提出了一个 TEP 模型来有效地考虑海量场景而不会减少。我们使用 Benders 分解将 TEP 问题划分为一个投资主问题和许多操作子问题。应用多参数线性规划 (MPLP) 对每次迭代中的操作子问题进行聚类。这里,每个簇中只需要求解一个运算子问题,可以解析得到同一簇中其他子问题的结果。聚类过程是基于目标的,并在每次迭代期间动态自我更新,以便考虑所有场景对投资决策的影响。通过对改进的 Garver 6 总线、IEEE RTS-79、IEEE RTS-96 和实际大小的测试系统的案例研究,说明了所提出方法的效率改进和有效性。聚类过程是基于目标的,并在每次迭代期间动态自我更新,以便考虑所有场景对投资决策的影响。通过对改进的 Garver 6 总线、IEEE RTS-79、IEEE RTS-96 和实际大小的测试系统的案例研究,说明了所提出方法的效率改进和有效性。聚类过程是基于目标的,并在每次迭代期间动态自我更新,以便考虑所有场景对投资决策的影响。通过对改进的 Garver 6 总线、IEEE RTS-79、IEEE RTS-96 和实际大小的测试系统的案例研究,说明了所提出方法的效率改进和有效性。
更新日期:2020-03-01
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