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

Hong Wang, Z. Qu
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引用次数: 1

Abstract

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.
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实现电力系统运行不确定性最小化的窄频概率密度函数——一个随机分布控制的视角
本文首先对考虑DERs的随机摆动方程进行总结。随后将采用Fokker - Planck Kolmogorov (FPK)方程建立随机分布控制模型,该模型将电源和负载与频率的PDF联系起来。一个通用的约束优化问题将被制定,其中成本函数是由频率的实际和期望的pdf之间的一种“功能距离”组成。本文将描述一种基于B-spine神经网络的随机分布控制模型的可行解决方案。利用得到的随机分布控制模型,描述了一种反馈型控制算法,该算法使用可控电源和负载来塑造频率的PDF或通过最小化熵方法最小化频率的随机性。未来的方向将在本文的后半部分简要讨论。
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