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Energy and Reserve Scheduling Under Wind Power Uncertainty: An Adjustable Interval Approach

机译：风电不确定性下的能源和储备调度：可调区间法

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摘要

This paper presents an adjustable interval optimization model for the energy and reserve clearance while treating the wind power variation and uncertainty. Instead of conventional predicted intervals (PIs), adjustable intervals (AIs) as subsets of PIs are proposed as more judicious choices for economically covering wind uncertainties. Ramp-capability reserve is modeled to ensure the existence of sufficient ramp capability needed to follow up wind power variation within AIs. However, realization of wind power beyond AIs, which is no longer compensable by ramp-capability reserve, would necessarily lead to either load shedding or wind spillage. In order to optimally determine AIs, apart from the energy and reserve procurement costs, the costs associated with load shedding and wind spillage are incorporated in the objective function. The confidence level theory is employed as well for tuning the robustness and conservatism of the final solution. Performance of the proposed method is examined on several case studies on an 8-bus and modified IEEE 118-bus test systems. Sensitivity analyses are conducted to specify the impacts of important parameters on the obtained solution. The results confirm the applicability and effectiveness of the proposed methodology.
机译：本文提出了一种可调节的区间优化模型，用于处理风能变化和不确定性时的能量和储备净空。代替常规的预测间隔（PI），建议将可调节间隔（AI）作为PI的子集，作为更明智的选择，以经济地涵盖风的不确定性。建模坡道能力储备以确保存在足够的坡道能力，以跟踪AI内部的风力变化。但是，实现超出AI的风力发电已不再可能由斜道能力储备补偿，因此必然导致甩负荷或风力溢出。为了最佳地确定AI，除了能源和储备采购成本外，与减载和风泄漏相关的成本也包含在目标函数中。置信水平理论也用于调整最终解决方案的鲁棒性和保守性。在8总线和改进的IEEE 118总线测试系统的几个案例研究中，检验了所提出方法的性能。进行灵敏度分析以指定重要参数对所获得解决方案的影响。结果证实了所提出方法的适用性和有效性。

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