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Narrowing Frequency Probability Density Function for Achieving Minimized Uncertainties in Power Systems Operation – a Stochastic Distribution Control Perspective

机译:缩小频率概率密度函数,以实现电力系统操作中最小化的不确定性 - 随机分布控制视角

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In this paper, the summary of the stochastic swing equation will be firstly given taking into account of DERs. This will then be followed by the development of stochastic distribution control model that links the power sources and the loads with the PDF of the frequency using Fokker Planck Kolmogorov (FPK) equations. A generic constrained optimization problem will be formulated, where the cost function is composed of a kind of “functional distance” between the actual and the desired PDFs of the frequency. A feasible solution using B-spine Neural Networks based stochastic distribution control model will be described. Using the obtained stochastic distribution control model, a feedback type control algorithm will be described that uses controllable power sources and the loads to shape the PDF of the frequency or to minimize the randomness of the frequency via minimized entropy approach. Future directions will be briefly discussed in the later part of the paper.
机译:在本文中,首先考虑到DERS首先考虑到随机摆动方程的概述。然后将随后通过使用Fokker Planck Kolmogorov(FPK)方程,将电源和负载链接电源和负载的随机分布控制模型的开发。将制定通用约束优化问题,其中成本函数由频率的实际和所需PDF之间的“功能距离”组成。将描述使用基于B脊柱神经网络的随机分布控制模型的可行解决方案。使用所获得的随机分配控制模型,将描述使用可控电源和负载来形成频率的PDF的反馈类型控制算法,或者通过最小化熵方法最小化频率的随机性。将在纸张的后部将来讨论未来的方向。

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