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 2years 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 20years. So, the derived system may have statistical confidence for at least 20years 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.