基于可再生能源集成和系统柔性研究的随机生产仿真模型

Shucheng Liu, Wenxiong Huang, Yi Zhang
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引用次数: 0

摘要

为了整合大量可再生能源发电以满足加州可再生能源投资组合标准(RPS)目标,建立了一个随机生产模拟模型来评估加州独立系统运营商(CAISO)系统的容量和灵活性。该模型模拟了CAISO系统的运行,使用四个随机变量,发电资源强制中断,负荷,太阳能和风力发电,以捕获广泛的可能的系统条件。提出了一种新的模式保持方法来创建随机负荷、太阳能和风力发电变量的样本。该模型用于研究加利福尼亚州整合33%可再生能源发电的系统容量和灵活性需求。这项研究的结果已在长期采购计划(LTPP)程序中提交给加州公用事业委员会(CPUC)。
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A stochastic production simulation model for renewable integration and system flexibility studies
A stochastic production simulation model was developed to evaluate the California Independent System Operator (CAISO) system capacity and flexibility sufficiency in order to integrate high volume of renewable generation to meet the California state renewables portfolio standard (RPS) goals. The model, which simulates the operation of the CAISO system, uses four stochastic variables, generation resource forced outages, load, solar and wind generation, to capture a wide range of possible system conditions. A novel pattern preserving methodology was developed to create samples of stochastic load, solar and wind generation variables. The model was used to study the system capacity and flexibility needs to integrate 33% renewable generation in California. The results of this study were filed to the California Public Utilities Commission (CPUC) in the Long Term Procurement Plan (LTPP) proceeding.
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