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Requirement design for a reliable and efficient ramp capability product

机译:可靠,高效的斜坡能力产品的需求设计

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With increasing intermittent renewable penetration, net load variations and uncertainties increase. When there is a sudden change in wind, real-time dispatches can be short of ramp capabilities from online generators, and offline generators may not respond fast enough. To manage the challenge of maintaining power balance, a ramp capability product is being developed by many ISOs with requirements set based on the Gaussian sigma rule, e.g., 2.5 sigma for the 99% confidence level. However, a simple Monte-Carlo simulation test shows that the realized confidence levels for different numbers of sigma's are generally different from what were prescribed. More importantly, there are significant rooms for cost savings while maintaining the required confidence. How do we design the ramp requirements so that the realized level truly satisfies the required confidence and the cost is optimized in a systematic way? Our idea is to use Monte-Carlo simulation to evaluate realized confidence levels and expected costs by mimicking real-time dispatches. Simulation-based optimization is then used to efficiently minimize the expected cost while maintaining the required confidence. Numerical results show that the designed ramp requirements can effectively manage net load variations and uncertainties at the specified confidence with significant cost savings.
机译:随着间歇性可再生能源渗透的增加,净负荷变化和不确定性增加。当风量突然变化时,实时调度可能会缺少在线发电机的斜坡能力,并且离线发电机的响应速度可能不够快。为了应对保持功率平衡的挑战,许多ISO正在开发一种具有斜坡能力的产品,其要求基于高斯Sigma规则设置,例如对于99%置信度设置为2.5 Sigma。但是,简单的蒙特卡洛模拟测试表明,不同数量的sigma的已实现置信度通常不同于规定的置信度。更重要的是,在保持所需信心的同时,还有大量节省成本的空间。我们如何设计斜坡要求,以使实现的水平真正满足要求的置信度并以系统的方式优化成本?我们的想法是通过模拟实时调度,使用蒙特卡洛模拟来评估已实现的置信度和预期成本。然后,基于仿真的优化可用于有效地最小化预期成本,同时保持所需的置信度。数值结果表明,设计的斜坡要求可以在指定的置信度下有效管理净负载变化和不确定性,同时可以节省大量成本。

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