Three‐phase probabilistic load flow for power system with correlated wind, photovoltaic and load. Issue 12 (1st September 2016)

• Record Type: Journal Article
• Authors: Ran, Xiaohong; Miao, Shihong
• Is Part Of: IET generation, transmission & distribution. Volume 10:Issue 12(2016)
• Page Start: 3093
• Page End: 3101
• Publication Date: 2016-09-01
• Subjects: photovoltaic power systems -- wind power plants -- higher order statistics -- Monte Carlo methods -- load flow -- power distribution; power system performance -- wind power generation -- photovoltaic generation -- PV generation -- bus load -- adjacent wind farms -- PV resources -- three‐phase probabilistic load flow algorithm -- asymmetric line parameter -- unbalanced load -- input random variable -- joint correlation -- joint probabilistic model -- joint cumulant method -- Gram‐Charlier expansion -- cumulative distribution function -- Monte Carlo simulation -- renewable energy generation penetration -- 25‐bus distribution system; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2016.0424
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : In order to evaluate impact of different uncertainty, such as the intermittent behaviour of wind power and photovoltaic (PV) generation and bus load, and adjacent wind farms or PV resources on performance of power system, a new three‐phase probabilistic load flow (PLF) algorithm with asymmetric line parameter and unbalanced load of distribution system is proposed. Correlation among input random variables is considered, especially the joint correlation of wind power and PV generation and bus loads is considered, and then joint probabilistic model of wind power, PV generation and bus load is established. Then a joint cumulants method and Gram–Charlier expansion are applied to obtain the cumulative distribution function of desired random variables, and PLF results based on joint cumulants method are compared with the ones of Monte Carlo simulations. Proposed method allows evaluating potential impact of different correlation and renewable energy generation penetration on the PLF of power system. The effectiveness of proposed method is demonstrated with a typical structure of 25‐bus distribution system.