## 5 Standalone PV System Optimization Technique
### Intuitive Methods  
The intuitive method is simple, easy to be implemented, and can be used to give rough suggestion for preliminary design. The sizing rules are base on designer's experience, using lowest performance either in a time period data or by directly using average value (daily, monthly, or annual) of solar irradiance. Hence, this method allocates the system to generate more power than required by a safety margins. The quantitative relationship between subsystem, such as generated power subsystem, battery's state of charge subsystem, or reliability subsystem, is not considered. Besides, this technique also does not consider random nature of solar radiation and meteorological condition. This method is not very popular because it is limited for rough estimation and preliminary design only. Besides, this method tends to give oversized design and has low reliability [12; 34; 79]. There are some studies for optimal sizing of a SAPV system using the intuitive method. Based on the records, the first application of intuitive technique was done in 1997 [93], where optimization of a SAPV system and tilt angle modules was done at five sites in Iran with different longitudes, latitudes and altitudes. First, the authors start optimizing the system by determining the optimum tilt angle between 0\({}^{\circ}\) to 90\({}^{\circ}\) for each sites, to maximize PV power generation. Then, PV array was chosen using the least PV size required to fulfil demand requirements, in order to minimize the cost. After that, by using statistical approach, number of successive cloudy days was decided. Based on that, battery size was determined, with expectation to fulfil demands during low intensity of solar radiation in cloudy days. However, this study only explains the PV and battery system sizing roughly without explanation of the modelling methods. Besides, the smallest PV array size was selected, and thus, it is very possible that the power generated by the system will be enough to supply the load, or unable to charge battery until having is enough charge to supply the load during cloudy days. Afterwards in 2003, more detailed study was done using intuitive approach based on estimated monthly average of solar irradiation data in Dhaka, Bangladesh [94]. The researchers calculate array size by choosing a month with minimum solar radiation. Three designs of sizing methods to fulfil same daily load demands were developed and compared. In array sizing for first design, the authors first compared and choose a month with the worst peak sun hour (PSH) at tilt angle of site latitude, and tilt angle of \(\pm 15^{\circ}\) to site latitude in summer and winter season. On the other hand, the second design's array sizing was done by manually chose worse radiation between 40\({}^{\circ}\) and 10\({}^{\circ}\) tilt angle with azimuth of 0\({}^{\circ}\), and for third design, same method was applied for 40\({}^{\circ}\) and 10\({}^{\circ}\) tilt angle with azimuth of \(\pm 45^{\circ}\). Then, the battery capacity chosen is assumed be able to supply 2 to 3 autonomy days. Lastly, the design with minimum array and battery size was selected as best design. Since the comparison has too many variables, an exclusive comparison between designs is defeasible. Later, a more neat sizing was done in 2009 [95]. Solar irradiation data in Egypt for south facing PV array tilted by site latitude was used and considered as optimum tilt angle in that particular region. To fulfil an average daily demand for a household in remote area, PV array was sized with