Impact of Battery's Model Accuracy on Size Optimization Process of a Standalone Photovoltaic System
This paper presents a comparative study between two proposed size optimization methods based on two battery's models. Simple and complex battery models are utilized to optimally size a standalone photovoltaic system. Hourly meteorological data are used in this research for a specific site. Results show that by using the complex model of the battery, the cost of the system is reduced by 31%. In addition, by using the complex battery model, the sizes of the PV array and the battery are reduced by
... tery are reduced by 5.6% and 30%, respectively, as compared to the case which is based on the simple battery model. This shows the importance of utilizing accurate battery models in sizing standalone photovoltaic systems. The equation of the system's cost is partially derived and solved graphically. As a result, two curves are drawn which represent the different size combinations of the PV array and the storage battery for the desired LPSP. The tangent point of the presented curves indicates the optimum size of the PV/battery combination. This method has a limitation in which sizing curves have to be constructed for each particular load demand. Meanwhile, an analytical method was developed by Khatib et al.  for optimal sizing of a PV/battery configuration of a standalone PV system in Malaysia. The developed method was carried out by deriving size formulas for the size of PV array and battery which can be generalized for Malaysia and nearby zones. Firstly, the sizing methodology defines some constants, such as the specifications of the system and the load demand. Here, daily average meteorological and load demand data are used for this purpose. Then, the size of the PV array and the capacity of the storage battery are calculated based on a specific loss of load probability (LLP). The authors plot the LLP values versus the PV array size and PV array size versus the battery capacity. Then MATLAB fitting toolbox is used to estimate the coefficients of these formulas. This research work has some limitations in which a simple battery model is used, daily average meteorological data are utilized, and the method is not taking into consideration any economical parameters. In conclusion, these limitations may affect the accuracy of the sizing results. In 2016, Nordin and Rahman  proposed a novel optimization method for sizing a standalone PV system using numerical methods. The sizing methodology was done based on Malaysian's weather profile. Hourly meteorological and load demand data were utilized to verify the novelty of the proposed method. The authors assumed a design space that specifies the numbers of the PV modules and storage battery unites. Then, the LPSP is obtained for each combination in the design space. As a result, all the combinations that have the desired LPSP are selected for the second stage which is the calculation of the levelized cost of energy (LCE). Following that, the optimum PV/battery combination is chosen based on the minimum value of the LCE. Here, a simple linear PV array model and a dynamic battery model have been used to model the performance of the system. Therefore, the numerical method is the most frequently used method for optimally sizing a standalone PV system. Numerical method is mainly done in terms of a bi-objective techno-economic optimization function which is formulated based on the best trade-off between system's cost and availability  . Therefore, with the numerical method, four aspects must be considered to accurately size a standalone PV system, which are input data, system's models, simulation methods, and formulated objective function  . In previous works, simple battery models have been used to represent the charging and discharging process in sizing algorithms of standalone PV systems [9, 10] . Meanwhile, some more complex battery models are utilized [11, 12] . Simple battery models can be defined as a series of mathematical equations that express the status of the storage of a battery without reflecting the dynamic behavior of the charging and discharging processes. Simple battery models may affect the accuracy of the sizing results as the state of charge of the battery is not calculated accurately. In contrast, complex battery models consider the dynamic behavior of the battery during charging and discharging process. Thus, the accuracy of the sizing results is expected to be higher. Based on this, in this paper, a comparative study is done between two sizing algorithms that are based on simple and complex battery models. Experimental data of a 3 kWp PV system installed at the Universiti Kebangsaan Malaysia campus are used for this purpose. These data contain hourly solar radiation, ambient temperature, and actual system output.