## 2 PV Power Systems
### Grid-Connected PV Systems  
The output of grid-connected PV systems is connected to the AC grid through a DC-AC inverter, as shown in Figure 3. The system can be subdivided into two types: central and decentralized grid-connected PV systems [31]. Compared to the decentralized grid-connected PV systems, the central grid-connected PV systems have a wide power range that can feed directly into medium- and high-voltage grids [32; 33]. For power systems with a high share of PV generation, frequency fluctuation is a frequently encountered issue, which can negatively impact the power system, because PV power is highly affected by weather conditions and the incidence angle of light and shading [34]. Introducing power curtailment and providing energy storage systems are the most common solutions for frequency stability problems [35]. Figure 1: Stand-alone PV power conversion system. Figure 2: Hybrid PV power conversion system. * _PV power curtailment methods_  
Figure 4 illustrates an alternative grid-connected PV system with a power curtailment control algorithm. The advantages of this method are a more straightforward implementation and a lower initial investment. When the PV power curtailment method is implemented, the power generated by the PV panels is lower than the maximum PV power, meaning that the operating point is at a suboptimal power level [36]. Therefore, the current-voltage (I-V) curve and the actual MPP need to be estimated to determine the available power. There are several existing and proposed methods for estimating the maximum available power point while operating suboptimally, which can be categorized into two types: measurement-based and curve-fitting-based methods [37; 38]. In measurement-based methods, additional sensors, such as temperature and irradiance sensors, are required for measuring the real-time operating point [39]. With these additional sensors, the measurements are more accurate. Thus, the implementation of the control strategy is effective. However, due to the employment of additional sensors in the PV system, its cost and complexity may increase. For curve-fitting-based methods, curve fitting with a number of PV voltage and current samples is used for the estimation of the entire I-V curve. The Newton quadratic interpolation (NQI) or nonlinear least squares is commonly used to solve curve-fitting problems. The accuracy of NQI, influenced by the selection of three sample points, has been discussed in [40]. The results of the nonlinear least-squares curve-fitting technique are highly affected by the initial values and noise, which have been analyzed in detail in [41]. In reference [40], two current-voltage points were used to estimate the open-circuit current, allowing the MPP to be calculated using an empirical expression for power curtailment. While this method is simpler to implement, it is highly sensitive to noise. In work [41], nonlinear least-squares curve-fitting was used to estimate the actual I-V curve, the power-voltage (P-V) characteristic, and the MPP. The operating point can be operated on both sides of the P-V curve. A control strategy based on the PV voltage was proposed to regulate pulse-width modulation (PWM) for adjusting the output power of the boost converter to fulfil the grid power requirements. Additionally, an effective approach  
Figure 4: Alternative grid-connected PV system control with power curtailment control algorithm. Figure 3: Grid-connected PV power conversion system. was proposed to address instability issues arising from sudden changes in irradiance and temperature. In [42], the P-V characteristic and the MPP were estimated by curve fitting. A PV power curtailment method with the ripple control algorithm was proposed for the adjustment of a two-stage inverter. The system is operated on the right side of the MPP, resulting in instability of the system when step changes occur in the irradiance, but higher efficiency is achieved.