The input voltage of battery charging system is always above the battery nominal voltage and it should be remained constant. But it depends on the type of input voltage sources. A battery charged directly by photovoltaic (PV) module as the input voltage source can cause the output voltage of PV module or the input voltage of battery charging system can fluctuate, because the output voltage of PV module depends on the solar irradiance. This problem can be solved by installing DC-DC boost converter between the PV module and battery. This paper presents a DC-DC boost converter based on PID controller for battery charging system. It is designed for the input voltage of 12V and output voltage of 14.7V system because it is applied to charge a 12 V, 7 Ah lead acid battery. Based on the simulation result of battery charging system shows that the output voltage of DC-DC boost converter can be remain around 14.7 V. It is due to the PID controller can damp the voltage oscillation and remain its steady state voltage. The time needed by the DC-DC boost converter to charge the battery in the fully charging condition is 1 hour: 3 minutes: 37seconds.

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This paper presents analysis of the solar radiation characteristics as energy source of photovoltaic (PV) powered uninterrupted power supply (PV-UPS) in Perlis, Northern Malaysia for the year of 2011 to 2013. The characteristics consist of daily, monthly and annual solar radiation. Peak sun hours (PSHs) of the solar radiation and PV power generation capacity are also analyzed. The potential of solar radiation as energy source of PV-UPS based on their values. They are low solar radiation (below 2.6 kWh/m 2), moderate solar radiation (between 2.6-3 kWh/m 2), high solar radiation (between 3-4 kWh/m 2) and very high solar radiation (above 4 kWh/m 2). The results show that the average monthly solar radiation for the past three years is 4.8 kWh/m 2. The annual total solar radiation in Perlis is 1761.1 kWh/m 2 which will generate a total electric energy of 228.9 kW/m 2 per year of PV module, if all the lands in Perlis are filled with horizontal PV panels, nearly 181.97 GWh of electricity could be produced per year. This shows the big potential of solar radiation for PV

The data of solar energy density in one area is very important when the area will constructed photovoltaic (PV) system. The data is as preliminary study to decide what the area is suitable or not to be constructed the PV application system. But, sometime the available data is missing because the limitation of weather equipment.  An alternative technique for the available data of solar energy density should be done for the continuity of PV application system decision. An estimation technique of solar energy density is one part of good alternative to solve this problem. This paper presents the estimation of solar energy density using Adaptive Neuron Fuzzy Inference System (ANFIS). The ANFIS system has two input data of the measured daily minimum, maximum temperature and difference between maximum and minimum temperature. The measured solar energy density is as target data of ANFIS system. The data is recorded from Medan meteorological station through the web site of world weather online for the year of 2018. The result shows that the average estimated solar energy density is classified in the very high solar energy density and based on the percentage error shows that the estimated solar energy density is acceptable.

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