Power system probabilistic production simulation containing large-scale wind power and photovoltaic power

“…Therefore, an extra uncertainty scaling factor for loads and PVs is introduced which is eventually multiplied with the corresponding value from the daily loading or PV curve, respectively. The normal distribution for the system loading uncertainty has mean value 1 pu and standard deviation 3.33% and the beta distribution a and b parameters are 13.7 and 1.3 respectively [39]. For wind generation, the mean value of the wind speed within one day is considered constant [40], and the uncertainty of the wind speed is modelled using a Weibull distribution [41].…”

Section: B Modelling Of Uncertaintiesmentioning

confidence: 99%

Probabilistic Framework for Online Identification of Dynamic Behavior of Power Systems With Renewable Generation

Papadopoulos

Guo

Milanović

2018

IEEE Trans. Power Syst.

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The paper introduces a probabilistic framework for online identification of post fault dynamic behavior of power systems with renewable generation. The framework is based on decision trees and hierarchical clustering and incorporates uncertainties associated with network operating conditions, topology changes, faults and renewable generation. In addition to identifying unstable generator groups, the developed clustering methodology also facilitates identification of the sequence in which the groups lose synchronism. The framework is illustrated on a modified version of the IEEE 68 bus test network incorporating significant portion of renewable generation.

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“…A current controller, real (active)-reactive power PQ controller and over frequency power reduction control of the converter are included in the model. Further details about the system and references to the sources of data used in simulations can be found in [41][42][43][44][45][46] and appropriate system settings and computational tools downloaded from https://data.mendeley.com/.…”

Section: Examples Of Probabilistic Power System Stability Studies (A)mentioning

confidence: 99%

Probabilistic stability analysis: the way forward for stability analysis of sustainable power systems

Milanović

2017

Phil. Trans. R. Soc. A.

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Future power systems will be significantly different compared with their present states. They will be characterized by an unprecedented mix of a wide range of electricity generation and transmission technologies, as well as responsive and highly flexible demand and storage devices with significant temporal and spatial uncertainty. The importance of probabilistic approaches towards power system stability analysis, as a subsection of power system studies routinely carried out by power system operators, has been highlighted in previous research. However, it may not be feasible (or even possible) to accurately model all of the uncertainties that exist within a power system. This paper describes for the first time an integral approach to probabilistic stability analysis of power systems, including small and large angular stability and frequency stability. It provides guidance for handling uncertainties in power system stability studies and some illustrative examples of the most recent results of probabilistic stability analysis of uncertain power systems.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'.

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Power system probabilistic production simulation containing large-scale wind power and photovoltaic power

Cited by 21 publications

References 7 publications

Probabilistic Framework for Transient Stability Assessment of Power Systems With High Penetration of Renewable Generation

Probabilistic Framework for Transient Stability Assessment of Power Systems With High Penetration of Renewable Generation

Probabilistic Framework for Online Identification of Dynamic Behavior of Power Systems With Renewable Generation

Probabilistic stability analysis: the way forward for stability analysis of sustainable power systems

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