Prediction of renewable energy hosting capacity using multiple linear regression in KEPCO system

被引:6
作者
Lee, Kyungsang [1 ,2 ]
Im, Seunghyuk [1 ]
Lee, Byongjun [1 ]
机构
[1] Korea Univ, Dept Elect Engn, Seoul 02841, South Korea
[2] Korea Elect Power Corp, KEPCO Acad, Seoul 01793, South Korea
基金
新加坡国家研究基金会;
关键词
Renewable energy; Hosting capacity; Power system; Multiple linear regression;
D O I
10.1016/j.egyr.2023.09.121
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In order to prepare measures for the stable operation of the power system to expand renewable energy, the renewable energy hosting capacity (HC) in the system shall be identified in advance. This paper proposes a methodology for predicting monthly HC based on factors affecting HC. It was found out that these factors are: Total generation, ratio of nuclear, coal, liquefied natural gas (LNG), and other power generations. A prediction model was developed using multiple linear regression by integrating and separating data of elements from weekend data. A comparison of the determination coefficients showed that the models incorporating weekend data exhibited the best accuracy. In conclusion, the proposed model has the characteristics of predicting various HCs simply and quickly with five factors.
引用
收藏
页码:343 / 347
页数:5
相关论文
共 19 条
[1]  
AEMO, 2018, Inertia requirements methodology.
[2]  
[Anonymous], 2022, 2022Korea Power Exchange Daily dispatch report
[3]  
[Anonymous], 2020, 2020Korea Power ExchangeA basic study on the low inertia power system assessment and operation measures by expansion of renewable energy resources Naju
[4]  
안준영, 2017, [Journal of Korean Institute of Information Technology, 한국정보기술학회논문지], V15, P1, DOI 10.14801/jkiit.2017.15.9.1
[5]  
ERCOT, 2018, Inertia: Basic Concepts and Impacts on the ERCOT Grid
[6]  
Gonzalez-Longatt F, 2013, 2013 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT), P826, DOI 10.1109/ICIT.2013.6505779
[7]  
International Energy Agency (IEA), 2022, GLOB EN REV 2021
[8]  
Kim Do Hyun, 2019, 전기학회논문지, V68, P1094
[9]  
Korea Electric Power Corporation, 2016, A study on the power system impact assessment of variable energy resources and countermeasures Naju
[10]  
Korea Electric Power Corporation, 2016, A study on the evaluation and countermeasures of the system impact of volatility power source Naju