## 1 Introduction
To further increase solar cells' efficiency and economic viability, the two optimisation techniques can be combined into an integrated system capable of focusing the light source onto a solar cell and orientating the panel towards the source of light. Recently, there are increasing interest of integrating the concentrating PV (CPV) technology into a building [11; 12; 13; 14]. A report published in 2021 by the Market Data Forecast indicated that the global concentrating PV (CPV) is now exceeding $790 million and will continue to achieve a compound annual growth rate of 14.5% until 2026 [15]. A joint report in 2017 by the Fraunhofer Institute for Solar Energy Systems (ISE) and the National Renewable Energy Laboratory (NREL) projected that the levelised cost of electricity of both the CPV and traditional PV system will achieve a competitive value of minimum $0.05/kWh by 2030 [16]. Researchers have developed various concentrator designs for building integration. The most prominent one is the design proposed by [PERSON] and [PERSON] [17] known as the compound parabolic concentrator (CPC). The CPC design itself has evolved over the years, i.e., 2D extrusion of a symmetrical reflective CPC [18], 2D extrusion of a symmetrical dielectric CPC [19], 3D rotationally symmetric dielectric CPC [20], reflective asymmetric CPC [21], dielectric asymmetric CPC [22] and crossed CPC [23]. Besides the CPC design, other concentrator designs explored previously include flat-plate static concentrator [24], extrusion of reflective parabolic concentrator [25], 3D refractive static concentrator [26], 3D dielectric totally internally reflecting concentrator [27], circular rotational square hyperboloid concentrator [28] and luminescent solar concentrator (LSC) [29]. All the CPV designs were tested experimentally under standard test conditions to identify their I-V and P-V characteristics. Researchers have attempted various ways to improve the CPV performance. [PERSON] et al. [30] proposed the use of hybrid perovskites to improve the CPV performance and their simulations indicated that these cells could work beyond the Shockley-Queisser limit with concentrators capable of concentrating 10-100 Suns (1 Sun = 1000 W/m\({}^{2}\)). [PERSON] et al. [31] developed a new metal halide perovskites to enhance the CPV performance and demonstrated that the cell accomplished the highest efficiency of 23.6% under 14 Suns. [PERSON] et al. [32] improved the quantum dots solar cells (QDSC) through the multi-photon absorption (MPA) to produce high densities of excitons, and achieved a 21.29% efficiency when tested with polymer lens CPVs that has a geometrical concentration gain of 4.08. [PERSON] et al. [33] increased the performance of an LSC by introducing a thick zinc chalcogenide and achieved an efficiency of 0.53%. [PERSON] et al. [34] on the other hand utilised indirect-bandgap semiconductor nanostructures to attain an LSC with an optical efficiency of 2.85%. As the PV systems have developed there has been an increasing demand to model their performance and predict the amount of energy that shall be generated under a set of given conditions. As a result of this, equivalent circuits of typical non-concentrating PV cells have been developed as well as other mathematical models to attempt to predict the performance characteristics and potential output power of a PV cell, i.e., to identify the current-voltage (I-V) and power-voltage (P-V) characteristics [35; 36; 37; 38; 39]. Note that these models differ between each other; each one of the model requires different parameters. To ensure the effectiveness of these models, often they are verified via experiments. These models also only demonstrated the simulation at normal incidence; no analysis were carried out to show the angular response of these typical non-concentrating PV cell. Although they are various PV models available, we found that there is limited literature on the modelling of concentrating PV (CPV) to characterise the output of the CPV design.