An efficient sizing method for a stand-alone PV system in terms of the observed block extremes

• Published in: Applied energy Vol. 91; no. 1; pp. 375 - 384
• Main Author: Chen, Shin-Guang
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2012
• Subjects: approaches; Arrays; batteries; Climate; Climate cycle; Computer simulation; Confidence intervals; Economics; energy balance; Extreme value theory; global warming; Loss of power probability; Mathematical models; Photovoltaic system; probability; Sizing; Solar irradiation; solar radiation; Weather conditions; Solar irradiation; Climate cycle; Extreme value theory; Sizing; Loss of power probability; Photovoltaic system
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2011.09.043

► A fast optimal sizing method under climate change. ► It provides the method of creating climate cycles for PV system applications. ► It proposes a new reliability indicator to denote the upper bound probability of a PV application. ► It presents a premiere economic optimization for such approach. ► It gives examples to illustrate the proposed approach. This paper proposes a novel and fast sizing method under the constant daily load profile for sizing a stand-alone PV system. The term “efficient sizing” means that the approach did not use simulation but could get the result as good as those employing simulation. So, the sizing method is more efficient than the others. Traditionally, a typical day or a typical year’s solar irradiation profile is employed for the sizing task. However, facing the global warming crisis as well as the fact that no 2 years would have the same weather condition for a single site, this approach statistically models the trend of climate change year by year and put it into the sizing formula, so that the results are optimal for the current weather condition and for the future as well. Hence, the suitable size for the PV array and the number of batteries are obtained by purely computation. This is different from the traditional sizing curve method. Although the traditional sizing curve method were satisfactory in the normal cases, they might fail in the extreme climate condition. This paper concludes the behavior of the extreme climate for at least 20 years. So, the derived system may have statistical confidence for at least 20 years of operation. A new reliability index (Loss of Power Probability) in terms of Extreme Value Theory is introduced. LPP provides upper bound reliability for application and rich information for many extreme events. A technological and economical comparison among the traditional daily energy balance method, sizing curve method and this approach is conducted and shows the usefulness of this approach.