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Requirement design for a reliable and efficient ramp capability product

机译:要求设计可靠,高效的斜坡能力产品

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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:随着间歇性再生渗透,净负荷变化和不确定性增加。当风突然发生变化时,实时调度可以短缺在线生成器的斜坡能力,并且离线发生器可能无法快速响应。为了管理维持权力平衡的挑战,许多ISO具有基于高斯Sigma规则的需求,例如,在高斯Sigma规则,例如99%的置信水平的2.5 sigma的需求开发了斜坡能力产品。然而,一个简单的Monte-Carlo仿真试验表明,不同数量的Sigma的实现置信水平通常与所规定的不同。更重要的是,有很大的房间可以节省成本,同时保持所需的信心。我们如何设计斜坡要求,以便实现的水平真正满足所需的信心,并以系统的方式优化成本?我们的想法是利用Monte-Carlo模拟来评估实现的置信度和预期成本,通过模仿实时调度。然后,基于仿真的优化用于有效地减少预期成本,同时保持所需的置信度。数值结果表明,设计的斜坡需求可以有效地管理规定的信心以显着的成本节省的净负载变化和不确定性。

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