Synthetic Time Series Generation Model for Analysis of Power System Operation and Expansion with High Renewable Energy Penetration

作     者：Rodrigo Palma-Behnke Jorge Vega-Herrera Felipe Valencia Oscar Nunez-Mata Rodrigo Palma-Behnke;Jorge Vega-Herrera;Felipe Valencia;Oscar Nú?ez-Mata

作者机构：Energy CenterDepartment of Electrical EngineeringFaculty of Mathematical and Physical SciencesUniversity of ChileSantiagoChile Department of Electrical EngineeringUniversity of AntofagastaAntofagastaChile School of Electrical EngineeringUniversity of Costa RicaSan PedroCosta Rica 

出 版 物：《Journal of Modern Power Systems and Clean Energy》 (现代电力系统与清洁能源学报（英文）)

年 卷 期：2021年第9卷第4期

页      面：849-858页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 0808[工学-电气工程] 080802[工学-电力系统及其自动化] 08[工学] 0807[工学-动力工程及工程热物理] 

基　　金：This work was supported by FONDAP/ANID Solar Energy Research Centre SERC-Chile(No.15110019),Fondecyt-ANID(No.1211968),Fondecyt(No.1181532) the National Master Thesis(No.CONICYT/21161139). 

主　　题：Time series analysis renewable energy source solar energy stochastic process statistical analysis wind energy 

摘      要：The increasing integration of renewable energy sources into current power systems has posed the challenge of adequately representing the statistical properties associated with their variable power generation. In this paper, a novel procedure is proposed to select a proper synthetic time series generation model for renewable energy sources to analyze power system problems. The procedure takes advantage of the objective of the specific analysis to be performed and the statistical characteristics of the available time series. The aim is to determine the suitable model to be used for generating synthetic time series of renewable energy sources. A set of indicators is proposed to verify that the statistical properties of synthetic time series fit the statistical properties of the original data. The proposal can be integrated into systematic tools available for data analysis without compromising the representation of the statistical properties of the original time series. The procedure is tested using real data from the New Zealand power system in a mid-term analysis on integrating wind power plants into the power system. The results show that the proposed procedure reduces the error obtained in analyzing power systems compared with reference models.