Daily clearness index profiles and weather conditions studies for photovoltaic systems. (December 2017)

• Record Type: Journal Article
• Authors: Lai, Chun Sing; Li, Xuecong; Lai, Loi Lei; McCulloch, Malcolm D.
• Is Part Of: Energy procedia. Volume 142(2017)
• Page Start: 77
• Page End: 82
• Publication Date: 2017-12
• Subjects: photovoltaic system -- clustering -- clearness index; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2017.12.013
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: The increasing number of distributed photovoltaic (PV) systems connected to the power grid has made system planning and performance evaluation a challenging task. This is mainly due to the computational complexity, such as load flow analysis with large irradiance datasets collected from various locations of the installed PV farms. Solar irradiance data are known to possess the characteristic of high uncertainty, due to the random nature of cloud cover and atmospheric conditions. This paper presents the studies on the relationships of clustered clearness index profiles and the weather conditions obtained from the weather forecasting stations. Four years of solar irradiance and weather conditions data from two locations (Johannesburg and Kenya) were obtained and are used for the analysis. The preliminary study shows that the weather condition is related to the daily clearness index profiles. This work will form the basis for estimating the daily clearness index profile with weather conditions.