Analysis of the System Costs of Wind Variability Through Monte Carlo Simulation

J. Cardell, C. Lindsay Anderson
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引用次数: 16

Abstract

Wind power forecast uncertainty raises concerns of the impact of wind power on power system and electricity market operations. The analysis presented in this paper uses an optimal power flow (OPF) model in a Monte Carlo Simulation (MCS) framework to estimate the cost impacts from the uncertainty in windfarm output. Using various regional load levels, and assumptions on the costs for providing balancing energy, the results from the OPF and MCS show that wind power forecast uncertainty for the test system can increase production cost up to 350 times, though for most cases the forecast uncertainty does not introduce significant changes from the base cases. The real and reactive power losses are shown to be higher for scenarios with low wind-high load and high wind-low load as compared to the moderate wind-load cases.
通过蒙特卡罗模拟分析风变率的系统成本
风电预测的不确定性引发了人们对风电对电力系统和电力市场运行影响的担忧。本文的分析使用蒙特卡罗仿真(MCS)框架中的最优潮流(OPF)模型来估计风电场输出的不确定性对成本的影响。使用不同的区域负荷水平,并假设提供平衡能源的成本,OPF和MCS的结果表明,测试系统的风电预测的不确定性可以增加生产成本高达350倍,尽管在大多数情况下,预测的不确定性不会带来基本情况的显着变化。低风高负荷和高风低负荷情况下的实际和无功功率损耗均高于中等风负荷情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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