Earticle

초록

영어

Due to the oil crisis and the insecurity of nuclear energy, the exploitation of renewable energy has attracted researchers’ attentions recently. In particular, to charge electric power in smart grid cities, it is important to integrate multiple renewable energy sources efficiently. Unlike the existing energy sources, the renewable energy sources such as wind and solar have low availability because they are uncontrollable. Thus, in order to make stable and predictable electric power generation, many forecasting models have been proposed. This paper examines whether there is any spatio-temporal correlation between wind speed and sunlight, which is not considered by the existing forecasting models for predicting power generation. To achieve this research objective, we categorize and analyze Jeju weather data by regions and seasons. Through the analysis, we show how wind and solar can complement each other. We expect that our analysis scheme can be used as a basis for predicting power generation in smart grid cities where multiple renewable energy sources are combined together.

목차

Abstract
 1. Introduction
 2. Background and Related Works
 3. Correlation Analysis and ANOVA by Seasons and Regions
 4. Correlation Analysis among Wind Speed, Sunlight and Rainfall
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Chan Jung Park [ Department of Computer Education, Jeju National University, Jeju-do, Republic of Korea ]
• Junghoon Lee [ Department of Computer Science and Statistics, Jeju National University, Jeju-do, Republic of Korea ]
• Seong Baeg Kim [ Department of Computer Education, Jeju National University, Jeju-do, Republic of Korea ]
• Jung Suk Hyun [ Department of Management Information Systems, Jeju National University, Jeju-do, Republic of Korea ]
• Gyung Leen Park [ Department of Computer Science and Statistics, Jeju National University, Jeju-do, Republic of Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605