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probabilistic load flow Calculation of Power System Integrated with Wind Farm Based on Kriging Model

Energy Engineering 2021年第3期118卷 565-580页

作者： Lu Li Yuzhen Fan Xinglang Su Gefei Qiu Faculty of Land Resource Engineering Kunming University of Science and TechnologyKunming650500China School of Control and Computer Engineering North China Electric Power UniversityBeijing102206China

Because of the randomness and uncertainty,integration of large-scale wind farms in a power system will exert significant influences on the distribution of power *** paper uses polynomial normal transformation method to deal with non-normal random variable correlation,and solves probabilistic load flow based on Kriging *** method is a kind of smallest unbiased variance estimation method which estimates unknown information via employing a point within the confidence scope of weighted linear *** with traditional approaches which need a greater number of calculation times,long simulation time,and large memory space,Kriging method can rapidly estimate node state variables and branch current power distribution *** one of the generator nodes in the western Yunnan power grid,a certain wind farm is chosen for empirical *** are used to compare with those by Monte Carlo-based accurate solution,which proves the validity and veracity of the model in wind farm power modeling as output of the actual turbine through PSD-BPA.

关键词： probabilistic load flow Kriging model wind turbine clusters polynomial normal transformation correlation

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Combined Cumulant and Gaussian Mixture Approximation for Correlated probabilistic load flow Studies:A New Approach

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CSEE Journal of Power and Energy Systems 2016年第2期2卷 71-78页

作者： B Rajanarayan Prusty Debashisha Jena Department of Electrical and Electronics Engineering National Institute of Technology KarnatakaSurathkalIndia 575025

In this paper,a probabilistic load flow analysis technique that combines the cumulant method and Gaussian mixture approximation method is *** technique overcomes the incapability of the existing series expansion methods to approximate multimodal probability distributions.A mix of Gaussian,non-Gaussian,and discrete type probability distributions for input bus powers is *** distributions of multimodal bus voltages and line power flows pertaining to these inputs are precisely obtained without using any series expansion *** the same time,multiple input correlations are *** of the proposed method is demonstrated in IEEE 14 and 57 bus test *** are compared with cumulant and Gram Charlier expansion,cumulant and Cornish Fisher expansion,dependent discrete convolution,and Monte Carlo *** of different correlation cases on distribution of bus voltages and line power flows are also studied.

关键词： Correlation cumulant Gaussian mixture approximation photovoltaic generation probabilistic load flow

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Optimal Transmission Switching Based on probabilistic load flow for Power System with Large Scale Renewable Energy Integration

Optimal Transmission Switching Based on Probabilistic Load F...

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作者： Rizwan Ahmed 山东大学

学位级别：硕士

High scale integration of renewable energies has led power system towards a new set of challenges that have increased the complexity of cost optimization ***,forecast errors in the prediction of wind,PV and load greatly affect the accuracy of *** studies have been focused by using optimal transmission switching（OTS）to solve different power system *** renewable sources integration in the power system imposes the uncertainties which change the system state dynamically,and to apply OTS under such conditions is a big *** cater with the above mentioned problem we used probabilistic load flow（PLF）with Gram-Charlier expansion method,to calculate the uncertain condition of the power system and the state of the power ***,Gram-Charlier method has been proposed for solving PLF based OTS for large-scale integration of renewable *** Gram-Charlier Expansion method has been used for forecast error evaluation in order to improve the accuracy of the proposed ***,proposed method use in this work has the fast convergence *** this work,uncertainies of a wind farm along with PV and load are considered as in realistic *** this thesis,the simultaneous optimization of generation dispatch and network topology for PLF based OTS has been *** results evaluations are based on the 24 hours with varying topology structure and cost *** the different time scales,different level of penetration of RES is considered to verify the model effectiveness and system *** justification and benchmarking of the proposed model modified IEEE-118 bus system is *** proposed formulation,uncertainties of the renewable sources can be taken into account to deal with the dynamic behavior of the *** results depict that the proposed approach is quite useful for large-scale power *** introduction of new technologies to create a more controllable and flexible grid is a part

关键词： Renewable Energy Sources Wind Power Generation Optimal Transmission Switching probabilistic load flow Gram-Charlier Expansion

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Cumulant-based correlated probabilistic load flowconsidering photovoltaic generation and electric vehiclecharging demand

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Frontiers in Energy 2017年第2期11卷 184-196页

作者： Nitesh Ganesh BHAT B. Rajanarayan PRUSTY Debashisha JENA Department of Electrical and Electronics Engineering National Instituteof Technology Karnataka Surathkal Mangalore 575025 India

This paper applies a cumulant-based analytical method for probabilistic load flow (PLF) assessment in transmission and distribution systems. The uncertainties pertaining to photovoltaic generations and aggregate bus load powers are probabilistically modeled in the case of transmission systems. In the case of distribution systems, the uncertainties pertaining to plug-in hybrid electric vehicle and battery electric vehicle charging demands in residential community as well as charging stations are probabilistically modeled. The probability distributions of the result variables (bus voltages and branch power flows) pertaining to these inputs are accurately established. The multiple input correlation cases are incorporated. Simultaneously, the performance of the proposed method is demonstrated on a modified Ward-Hale 6-bus system and an IEEE 14-bus transmission system as well as on a modified IEEE 69-bus radial and an IEEE 33-bus mesh distribution system. The results of the proposed method are compared with that of Monte-Carlo simulation.

关键词： battery electric vehicle extended cumulant method photovoltaic generation plug-in hybrid electric vehicle probabilistic load flow

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