A Two-stage Stochastic Programming Model for Optimal Reactive Power Dispatch with High Penetration Level of Wind Generation
A Two-stage Stochastic Programming Model for Optimal Reactive Power Dispatch with High Penetration Level of Wind Generation
复制标题
风力发电高渗透率无功优化调度的两阶段随机规划模型
DOI：
10.5370/jeet.2017.12.1.053
复制
发表时间：
2017
影响因子：
1.9
通讯作者：
Wang Cong
中科院分区：
文献类型：
--
作者：
Cui Wei;Yan Wei;Lee Wei Jen;Zhao Xia;Ren Zhouyang;Wang Cong
风电接入水平的提高对传统的确定性优化问题无功优化调度提出了挑战。本文提出了一个两阶段随机规划模型，考虑风速和负荷的不确定性，在指定的时间间隔的ORPD。为了避免过度运作，将在第一阶段确定赔偿人的时间表，同时考虑到调整赔偿人的费用。在不确定性的影响下，有载分接开关（OLTC）和发电机在第二阶段将补偿由第一阶段的决定所造成的不匹配。所提出的模型的目标是最小化的CAC和预期的能量损失的总和。利用三点估计法（TPEM）将随机规划问题转化为等价的确定性问题。采用遗传算法和内点法相结合的方法求解这一大规模混合整数非线性随机问题。IEEE 14节点和IEEE 118节点系统的算例验证了该方法的有效性。
The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.
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影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
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DOI：
10.1016/j.ijepes.2014.09.008
发表时间：
2015
影响因子：
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DOI：
10.1049/ip-c.1993.0063
发表时间：
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期刊：
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影响因子：
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