Fault Analysis of a Small PV/Wind Farm Hybrid System Connected to the Grid

Abstract

The dynamic modeling, control, and simulation of renewable energy sources connected to the electrical grid are investigated in this study. Photovoltaic (PV) systems and wind systems connected to the power grid via the point of common connection (PCC) were the only two systems included in our study. Simulation and control methodologies are provided. For both PV arrays, the method of extracting maximum power point tracking (MPPT) is utilized to obtain the highest power under standard test conditions (STC: 1000 W/m², 25 °C). A power electronics converter that can transform DC voltage into three-phase AC voltage is required to connect a PV system to the grid. Insulated gate bipolar transistors (IGBTs) are utilized in a three-level voltage source converter (VSC). The distribution network is connected to this three-phase VSC by way of a step-up transformer and filter. During synchronous rotation in the $d-q$ reference frame, the suggested control for the three-level solar power system that is connected to the grid is constructed. To obtain a power factor as near to one as possible, the phase-locked loop (PLL) is employed to align the angle of the power grid voltage with the angle of the current coming from the inverter. Squirrel-cage induction generators (SCIGs), which are utilized as fixed speed generators and are linked directly to the power network, are the foundation of the wind system. Additionally, a pitch angle control approach is suggested to keep the wind turbine’s rotor speed stable. MATLAB/Simulink software is utilized to model and simulate the suggested hybrid system. Under fault scenarios such as the line to line to line to ground fault (LLLG fault), the suggested hybrid system’s dynamic performance is examined. The simulation results prove the ability to manage the small hybrid system that combines solar and wind power, as well as its dynamic performance.

1. Introduction

The most environmentally beneficial forms of energy to use are forms of alternative power such as solar and wind power generators. They have matured into a world-wide occurrence, the most rapidly expanding energy source in the world, and a clean, contemporary, effective technology that serves as a ray of vision of the future built on environmentally friendly, durable technology. Because of the worldwide increase in electricity demand, renewable energy sources adoption is more crucial than ever, such as solar photovoltaic (PV) and wind turbine producing systems.

In recent years, numerous investments and studies into PV/wind hybrid power systems have been conducted. An example of a hybrid generation system is provided in [1]. That is, a hybrid system is created by connecting a solar and wind system. A technique for managing energy in a hybrid generation system linked to the grid has been introduced, characterized by its capability for versatile energy transfer including standard operation without battery dependency, energy distribution, and energy balancing, making it suitable for both grid and user needs. The authors of [2] provided performance study of grid-connected hybrid power systems for wind and solar during fluctuation in load and climatic circumstances. The simulation findings in this reference demonstrated the resiliency of the MPPT control techniques in the face of daytime weather changes. Furthermore, the control of power flow technique efficiently meets the plant’s critical load demand. A grid-connected solar and wind hybrid energy system’s modeling, implementation and performance analysis were initially described in [3]. The effectiveness of MPPT techniques in obtaining the greatest power from hybrid power systems under a variety of environmental situations was demonstrated by the simulation results. Furthermore, because the hybrid power system’s injected reactive power is equal to zero, it successfully runs at unity power factor. In addition, the control technique effectively keeps the grid voltage constant despite changes in the outside environment and the power supplied from the hybrid power system. In reference [4], the topic of optimizing and assessing the functioning of a control system for a PV/wind power system connected to the grid is discussed. According to this source, the simulation results showed the proposed system can generate 8884 MWh annually, with a share of 89% wind generation and a 10% contribution from the PV system. The output of the hybrid system is highly reliant on changes in external factors such as the intensity of sunlight and velocity of wind. Because of this, it is imperative to use maximum power point tracking (MPPT) techniques to capture the most power possible under a variety of climatic situations. The MPPT control methods are covered in many kinds of literature [5,6,7]. For example, [6] looked into fuzzy logic control to obtain the most power out within a hybrid system of energy and the outcomes demonstrated the reliability of the control algorithms even in default situations and when connected to an electrical grid that is balanced. A total of 3.5 kW of power generated by the solar panel array is synchronized with the grid in a paper [8]. In this study, the inverter voltage and frequency are successfully synchronized with the grid voltage and frequency using a phase-locked loop (PLL).

In systems that convert wind energy, the squirrel-cage induction generator (SCIG) is most frequently used [9,10]. Numerous studies using SCIG and PV-based hybrid technology systems have been conducted [11,12]. The experimental examination, manipulating and managing the functioning of a hybrid energy system composed of both solar and wind power components was one of them, as provided by [11]. This source states that the maximum generated power for the SCIG wind turbine is 3 kW, while the highest generated power for the PV module is 44.71 W. The authors of [12] suggested power control for a combination wind–biogas–PV system. In this reference, the model maintains its stable behavior after disturbances in the active and reactive power of the load as well as the solar and wind energy input. More difficulties have recently arisen with a system that combines solar and wind power generation connected to the main power grid. Improved power quality injection, maximum power extraction, and issues with hybrid power systems’ connections to the electrical grid under all circumstances are some of these difficulties [13,14].

This work investigates the detail in creating a model that simulates the behavior and changes over time, design, and control of a hybrid power generation system that combines wind and solar power. Two PV arrays and two sets of 1.5 MW wind turbines are connected into the main AC bus of the proposed hybrid system to increase system efficiency. To maximize power under standard test conditions (STCs), the method of obtaining the highest level of power output is used for both PV arrays. SCIGs, which are utilized as constant speed generators and are connected directly to the grid, are the foundation of the wind system. A pitch angle control approach is suggested to keep the wind turbine’s rotor speed stable. The goal of this research is to is to evaluate and analyze the functioning of a combined solar and wind power system under fault scenarios such as the LLLG fault.

In brief, the current work delves into the intricacies of a hybrid PV/wind farm system connected to the electrical network:

• The paper presents a novel design for the PI regulator that takes into account the time constant of the pitch angle and the process of the quantity to be regulated;
• The proposed system is tested under high perturbation scenarios, such as the LLLG fault, and is found to have a robust controller that allows the system to quickly recover from faults;
• Furthermore, to enhance the robustness of the proposed method, the maximum peak value of power is taken into consideration.

The rest of this document is organized in the following manner: The proposed hybrid system architectural design is shown in Section 2. The Model of PV Array connected to the grid is covered in Section 3. The model of a SCIG connected to the grid was outlined in Section 4. The simulations conducted with MATLAB/Simulink to verify the effectiveness and performance of the suggested architecture are then described in Section 5. The study’s conclusions are presented in Section 6.

2. Proposed Hybrid System Architecture

A schematic with only one line of a small hybrid PV/wind farm system is shown in Figure 1. Two PV arrays that can produce a combined maximum of 145.2 kW at 1000 W/m² of solar irradiation make up the PV farm. Each section of the PV array is made up of 66 strings parallel, each of which is made up of five modules joined in series. A DC/DC converter is attached for every PV array. The results of the boost converters are linked to a 500 V common DC bus. Each MPPT controls its own boost. To achieve the highest power output from the PV array, the MPPTs employ the Perturb and Observe (P and O) technique in order to change the voltage between the terminals. A three-level VSC translates 500 V DC to 260 V AC while maintaining a power factor of one. The inverter is coupled to the grid by a three-level coupling transformer with a 400 kVA 260 V/25 kV rating. Power from the wind farm, which comprises four 1.5 MW wind turbines, is exported to a 120 kV grid via a 5 km 25 kV feeder and is coupled to a 25 kV system of distribution. A simulation of a wind farm with a capacity of 6 MW is created by utilizing two groups of wind turbines that each have a 1.5 MW output. Wind turbines employ SCIG. A wind turbine with variable pitch powers the rotor while a direct connection to the 60 Hz grid exists between the stator winding. When wind speeds surpass the standard velocity (9 m/s), the pitch angle is adjusted to maintain the generator’s output power at its standard level. The constant no-load requirement is met by the fixed bank of capacitors that are attached to the low voltage bus of each wind turbine (for every set of 1.5 MW turbines, 400 KVAR is required). The grid model is made up of conventional 120 kV equivalent transmission lines and 25 kV distribution feeders.

3. PV Array with Grid Connection Model

The three-phase grid-connected PV system is made up of a PV array, a boost converter, a DC link, a controlled inverter, a filter, a step-up transformer, and a grid. The boost converter control and the inverter control are the system’s two controllers. We must sense the PV array current and voltage before sending them to the MPPT to produce reference voltage in order to execute the boost converter control. The created reference voltage is compared with the PV real voltage to produce an error, which is sent to the PI controller in order to produce the reference signal. To create the control signal for a boost converter, a PWM generator receives the created reference signal. We must perceive both the three-phase inverter current and the three-phase grid voltage in order to control the inverter. The outer voltage loop and the inner current loop are the two control loops for this inverter. The DC reference voltage is compared with the DC voltage in the voltage loop to produce an error, which is then sent to the PI controller to produce the reference currents $I_d^{*}$ and $I_q^{*}$ set to zero. When the generated reference current $I_d^{*}$ and $I_q^{*}$ in the current loop are compared with the inverter’s real current, an error is created. The error is then sent to the PI controller, which uses it to obtain the reference voltage $V_d^{*}$ and $V_q^{*}$. The three-phase inverter’s control signal is generated by the PWM generator using the reference voltages $V_d^{*}$ and $V_q^{*}$, which are converted to the $abc$ reference voltage. Four phases are used to design the three-phase grid-connected PV solar. The PV solar array is designed first (the number of series and parallel modules we need to reach the required output power and voltage). The boost converter’s second stage of design. The inverter’s third stage of design is based on an $RL$ filter concept. Lastly, the controller (MPPT and PI controller) is created. Figure 2 displays the main schematic model of the PV system that is linked to the utility grid [15,16].

3.1. PV Array Model

A similar circuit for a PV array with $N_{Shu}$ shunt and $N_{Ser}$ series cell arrangements is illustrated in Figure 3 [15,16,17].

The following equation provides the fundamental equation that characterizes the I–V properties of the solar model [15,16,17,18]:

$$I_{Array}=N_{Shu}{I}_{PH}-N_{Shu}{I}_{Sat} \left(\exp \left[\frac{\left(V_{Array}+R_{Ser}{I}_{Array}\left(\frac{N_{Ser}}{N_{Shu}}\right)\right)}{V_T{N}_{Ser}}\right]-1\right)-\frac{V_{Array}+R_{Ser}{I}_{Array}\left(\frac{N_{Ser}}{N_{Shu}}\right)}{R_{Shu}\left(\frac{N_{Ser}}{N_{Shu}}\right)}$$

(1)

where:

$$I_d=I_{Sat}\left[\exp \left(V_d/V_T\right)-1\right]$$

(2)

$$V_T=\frac{N_{Cell}KT{Q}_D}{q}$$

(3)

where $N_{Cell}$ represents the quantity of series-connected cells in a module, $T$ is the cell temperature (K), $q$ is the electron charge (C), $K$ is the Boltzmann constant (J/K), $Q_d$ is the diode quality factor, $I_{PH}$ is the photocurrent, $I_{Sat}$ is the diode saturation current, $V_T$ is the terminal voltage, and $V_d$ is the diode voltage.

The I–V and P–V properties of the PV array are illustrated in Figure 4:

3.2. DC/DC Converter Model

One of the simplest switch-mode converter types is a DC/DC boost converter, which raises the input voltage in response to a certain situation. Figure 5 depicts the schematic for the boost-type converter we employed in this study [19,20].

The following equations control this converter:

$$V_0=\frac{V}{1-\alpha }$$

(4)

$$I_0=I\left(1-\alpha \right)$$

(5)

where$\alpha$, $V_0$, and $I_0$ stand for the boost converter’s duty cycle, output voltage, and output current, respectively. $\alpha$ is obtained as the output of the MPPT control system.

3.3. MPPT Control Based on P and O Technique

This technique uses a little disturbance to change the power output of the PV array. the amount of energy produced of the PV is monitored and contrasted with the previous power. The same process is resumed if the output power rises; otherwise, the perturbation is turned around. The voltage of the PV array is perturbed by this technique. In order to determine if the power has grown or decreased, the PV array voltage is changed. By using this method, voltage incrementing causes the power to change depending on where the action takes place within the MPP: when it occurs on the left side, the power increases, and when it occurs on the right, the power decreases. The P–V curve’s slope, as determined by [21,22]:

$$\left\{\begin{array}{cc}d{P}_{PV Array}/d{V}_{PV Array}=0,& at MMP\\ d{P}_{PV Array}/d{V}_{PV Array}>0,& left of MMP\\ d{P}_{PV Array}/d{V}_{PV Array}<0,& right of MPP\end{array}\right.$$

(6)

The flowchart in Figure 6 paints a clear picture of the adopted P and O algorithm’s inner workings.

3.4. Control of VSC

The VSC needs to maintain power factor at one and helps to regulate the DC bus voltage. As depicted in the image of Figure 2, two control loops are used by the control system: $I_d$ and $I_q$ network currents (active and reactive current components) are controlled by an internal control loop, while DC link voltage is controlled by an external control loop. The output of the external DC voltage controller is the $I_d$ current reference. As a way to preserve a power factor of one, zero is entered as the $I_q$ current reference. The voltage outputs $V_d$ and $V_q$ of the current controller are transformed into the three signals with modulation $U_{ref-abc}$ that the PWM three level pulse generator uses. The PI controller is utilized to create both the internal and external control loops [15,16,17,18,19,20,21,22,23]. The PLL is used to obtain the phase angle necessary for the $abc$to $dq$ transformation module.

Inside a forward-thinking loop, the grid voltage vector is employed to account for the grid harmonics [24]. Below is a representation of the inverter’s voltage and power equations in $d-q$ synchronous reference frame:

$$\left\{\begin{array}{c}{V}_d^{*}=R{I}_d+V_d-\omega L_f{I}_q+L_f\frac{d{I}_d}{dt}\\ V_q^{*}=R{I}_q+V_q-\omega L_f{I}_d+L_f\frac{d{I}_q}{dt}\end{array}\right.$$

(7)

$$\left\{\begin{array}{c}P=V_d{I}_d+V_q{I}_q \\ Q=-V_d{I}_q+V_q{I}_d \end{array}\right.$$

(8)

In the $d-q$ reference, the voltages shown by Equation (7) are connected. The method for compensating for the coupling of the axes $d$ and $q$ is shown in Figure 7.

The following decoupled voltages equation is obtained from the inverter’s voltage equation in a $d-q$ synchronous reference frame [25]:

$$\left\{\begin{array}{c}{V}_d^{*}=R{I}_d+V_d-\omega L_f{I}_q+K_p\left(I_d^{*}-I_d\right)+K_i\int \left(I_d^{*}-I_d\right)dt\\ V_q^{*}=R{I}_q+V_q-\omega L_f{I}_q+K_p\left(I_q^{*}-I_q\right)+K_i\int \left(I_q^{*}-I_q\right)dt\end{array}\right.$$

(9)

where $K_p$ and $K_i$ refer to the regulator’s proportional and integral gains, respectively. Figure 8 shows the Simulink model for the various VSC building blocks:

3.5. Phase-Locked Loop

PLL block must be added to the system since the conversion from the $abc$-frame to the $dq$-frame necessitates synchronization between the $abc$ values and the $dq$ values. It primarily comprises of a voltage-controlled oscillator, an output signal limiter, and a compensator [15,16,17,18,19,20,21,22,23,24,25,26]. The visual in Figure 9 brings to light the inner workings of a three-phase PLL using the Simulink model.

3.6. RL Filter

An inductance was added to the inverter to improve the load current (injection current) and decrease switching losses in the power components. Designing the inductance value takes current ripple into account. The ripple current can often be set between 15% and 25% of the rated current. The following are possible outcomes for the maximum current ripple [27]:

$$\Delta i_{Lmax}=\frac{1}{8}·\frac{V_{dc}}{L_f{f}_{sw}}$$

(10)

The intended value of the inductance $L_f$ in this system can be 20% of the rated current.

4. Model of SCIG Connected to the Grid

A direct connection exists between the SCIG wind turbine and the grid. A gearbox was utilized to boost the lower rotational speed of the wind turbine to the high rotational speed of the generator because the speed of the SCIG is fixed [28]. SCIG boasts several key benefits such as that it is more durable, dependable, well-tested, and reasonably priced than a doubly fed induction generator (DFIG) and permanent magnet synchronous generator (PMSG) [29]. However, because the generator is overloaded, SCIG utilizes reactive power to bring about excitation and can only harvest a little amount of electricity from the wind. With a constant speed-based SCIG connected to the utility network, the usual design of a wind turbine is shown in Figure 10 [30].

4.1. Turbine Model

The following equation provides the turbine’s mechanical output power [31,32].

$$P_m=C_{power}\left(\mathsf{\gamma }, \delta \right)\frac{\rho A}{2}{V}_{\omega }^3$$

(11)

where $P_m$stands for the driving force of movement that the turbine captures and transmits to the rotor (W), $C_p$ for the turbine’s power coefficient, and $\rho$ for the mass per unit volume of air (kg/m³), $A$ stands for the area covered by the turbine (m²), $V_{\omega }$ for the wind’s swiftness (m/s), $\mathsf{\gamma }$ for the proportion of velocities, and $\delta$ for the slant of the blade (°).

According to (11), the expression $C_{power}$ for a wind turbine that extracts 1.5 MW of power from the wind is expressed as follows:

$$C_{power}\left(\mathsf{\gamma }, \delta \right)=0.5176\left(\frac{116}{{\gamma }_i}-0.4\delta -5\right)e^{-21/{\gamma }_i}+0.0068 \gamma$$

(12)

where

$$\frac{1}{{\gamma }_i}=\frac{1}{\gamma +0.08\delta }-\frac{0.035}{{\delta }^3+1}$$

(13)

Figure 11 shows the $C_{power}-\gamma$ properties for various pitch angle values.

4.2. Pitch Angle Controller

The blade pitch angle is regulated by a proportional-integral (PI) controller to maintain the electric power output at the nominal mechanical power. Once the detected electric power output is fewer than the nominal value, the pitch angle is maintained at zero degrees. The PI controller modifies the pitch angle to bring the evaluated power back to its standard value when it exceeds it [30,31,32,33]. Figure 12 shows the novel control system:

4.3. SCIG Model

The algebraic expressions that detail the voltage of the SCIG’s stator and rotor in the rotating $d-q$ reference frame are as follows [30,31,32,33,34,35]:

$$\left\{\begin{array}{c}{\upsilon }_{sd}=R_s{I}_{sd}+\frac{d{\varphi }_{sd}}{dt}-{\omega }_{sy}{\varphi }_{sq} \\ {\upsilon }_{sq}=R_s{I}_{sq}+\frac{d{\varphi }_{sq}}{dt}+{\omega }_{sy}{\varphi }_{sd} \\ 0=R_r{I}_{rd}+\frac{d{\varphi }_{rd}}{dt}-\left({\omega }_{sy}-{\omega }_r\right){\varphi }_{rq}\\ 0=R_r{I}_{rq}+\frac{d{\varphi }_{rq}}{dt}+\left({\omega }_{sy}-{\omega }_r\right){\varphi }_{rq}\end{array}\right.$$

(14)

where on the $d$ and $q$ axes, the stator voltages are ${\upsilon }_{sd}$ and ${\upsilon }_{sq}$, respectively; the currents flowing through the stator are $I_{sd}$ and $I_{sq}$, respectively; the currents flowing through the rotor are $I_{rd}$ and $I_{rq}$, respectively; the flux elements present in the stator are ${\varphi }_{sd}$ and ${\varphi }_{sq}$, respectively; and the flux elements present in the rotor are ${\varphi }_{rd}$ and ${\varphi }_{rq}$, respectively. In addition, $R_s$ and $R_r$ stand for the stator and rotor resistances, respectively, while ${\omega }_{sy}$ represents the synchronous speed and ${\omega }_r$ represents the rotor’s spin velocity.

Flux and current relationships are expressed by the equations below:

$$\left\{\begin{array}{c}{\varphi }_{sd}=l_s{I}_{sd}+l_m{I}_{rd}\\ {\varphi }_{sq}=l_s{I}_{sq}+l_m{I}_{rq}\\ {\varphi }_{rd}=l_r{I}_{rd}+l_m{I}_{sd}\\ {\varphi }_{rq}=l_r{I}_{rq}+l_m{I}_{sq}\end{array}\right.$$

(15)

where $l_s$, $l_r$, and $l_m$ stand for the inductances of the stator, rotor, and magnet respectively.

The SCIG’s electromagnetic torque equation is as follows:

$$T_{em}=\frac{3}{2}p\left({\varphi }_{sd}{I}_{sq}-{\varphi }_{sq}{I}_{sd}\right)$$

(16)

where $p$ stands for how many machine pole pairs there are.

Additionally, the subsequent formula employed to calculate the active and reactive power emitted by the stator:

$$\left\{\begin{array}{c}{P}_s=\frac{3}{2}\left({\upsilon }_{sd}{I}_{sd}+{\upsilon }_{sq}{I}_{sq}\right)\\ Q_s=\frac{3}{2}\left({\upsilon }_{sd}{I}_{sq}-{\upsilon }_{sq}{I}_{sd}\right)\end{array}\right.$$

(17)

5. Results and Simulation

MATLAB/Simulink is employed to carry out the simulation model of the suggested hybrid system setup. Appendix A contains specific details about the small hybrid PV/wind farm system shown in Figure 1. The photovoltaic array produces a maximum output of 72 kW at STC. The wind turbine produces 3 MW at a nominal wind speed of 9 m/s. There are two parts to this section: (1) Without fault, and (2) with fault.

5.1. Without Fault

Initial grid analysis of all parameters is conducted without a distribution network fault. Figure 13 shows that the PV array produces voltage, current, and power of approximately 250 V, 287 A, and 71.9 KW, respectively, at STC. Figure 14 displays the DC voltage that the boost converter delivers. The boost converter elevates the natural PV voltage around 250 V to 500 V DC voltage at STC. Figure 15 displays the output voltage of the inverter. It is clear that the three-phase VSC preserves power factor constant at 1 and transforms 500 V DC to 260 V AC. Figure 16 displays the inverter’s filtered output voltage. To reduce the harmonics that the voltage source inverter produces, an $L$ filter is used here. According to Figure 17, the PV farm’s active power injection was about 141 KW, and since the reactive power was zero, the power factor was one. As seen in Figure 18, the SCIG consumed 2.85 MVAR of reactive power, whereas the active power harnessed by the wind farm was about 6 MW. Figure 19 displays a PCC bus with constant voltage and a peak voltage per phase of 20 kV (25 kV L-L). Regardless of changes in power from the combination system that was injected, the PCC-bus voltage remains constant. The three-phase injected the current of the PCC bus as mentioned in Figure 20. As is evident, the DC/AC converter controller controls current amplitude in relation to injected power. The power balance of a hybrid power system is visualized in Figure 21. It should be mentioned that the combined amount of power using the PV and wind farms is injected from the combination system to the PCC bus.

5.2. With Fault

Three lines to ground fault is a condition that occurs frequently in industrial settings and is actually quite harmful for converters built using power electronics. The voltage dip and excess current flow must be managed to prevent any device damage due to the semiconductor devices’ quick response times [36]. On the transmission line, an LLLG fault with a 0.1 s fault duration occurred at time t = 6 s. The LLLG fault’s impact on the parameters of a PV panel is shown in Figure 22. It is obvious that during the fault, the PV array’s voltage, current, and maximum output power are reduced; nevertheless, after 6.1 s, these parameters returned to normal value. Figure 23 depicts how the DC voltage the DC converter delivers is disturbed from 6 to 6.1 s into the LLLG fault. The controller has the capacity to manage the disturbance, causing the voltage to stabilize at 500 V in just 6.1 s. The DC voltage abruptly increases at 6 s from 500 V to 1545 V before dropping to 490 V before the fault is cleared. Without a pitch angle controller, the rotor speed climbs to high values during grid disturbances, as seen in Figure 24. At this point, the rotor speed can be stabilized with the use of the pitch angle controller. It is evident that following the occurrence of the fault, the rotor speed stabilizes. Consequently, the pitch angle controller contributes to the stability of rotor speed. The behavior of the PCC bus’s three-phase voltage throughout an LLLG fault is shown in Figure 25. The voltage is kept at 20 kV prior to the start of the incident (max). The voltage at the grid is 0 for 6 to 6.1 s during the LLLG fault. The voltage returned to normal after 6.1 s. The outcome reveals that the inverter was shut down between the seconds of 6 and 6.1. Figure 26 depicts the three-phase current behavior of the PCC bus during the LLLG fault. It shows that the current was settled at 224 A before to the fault’s beginning and increased to 1000 A with the injection of the fault at 6 s. After the faulty period, the current finally restores to its regular value of 224 A. The outcome demonstrates that current increases abruptly to 1000 A during the faulty period and then decreases to the steady state at a time instant of roughly 7 s. Figure 27 displays the PCC bus’s receipt of active and reactive power during the faulted duration. It has been demonstrated through modeling and actual experiences that the real and reactive power supplied into the PCC bus are also disrupted during the LLLG fault between the seconds of 6 and 6.1. The active power delivered into the PCC bus is zero during the faulty period. Additionally, it can be seen that there is a power surge right after the fault is cleared, which causes the converter to transport more power and strains the devices. Reactive power is one of the parameters that is least altered after an LLLG malfunction. A spike is noticed immediately once the fault was fixed, and within 7 s it returned to normal value.

6. Conclusions

This work effectively investigates the modeling, control, and simulation of a small hybrid PV/wind farm system that is coupled to the electrical network. Two PV arrays and two sets of 1.5 MW wind turbines are integrated into the proposed hybrid system at the PCC. For both PV arrays, the incremental conductance MPPT approach is used to maximize power under STC. At various time intervals, the variation in the three-phase voltage, current, active power, and reactive power injected to the electrical network is investigated. The $d-q$ reference frame serves as the foundation for the converter’s mathematical model. In the synchronously rotating frame, a three-phase VSC is regulated to transmit the highest amount of actual power into the power grid. The PLL enables network phase angle extraction with preview. The rotational velocity of the wind turbine’s blades is stabilized by using a pitch angle controller as well. Under failure scenarios such as the LLLG fault, the suggested hybrid system’s dynamic performance is evaluated. Because of the controller’s robustness, the system parameters quickly return to their original levels following a fault. Since the generated actual and reactive powers match the reference values provided by the MPPT control of the solar system and pitch angle control of the wind turbine, the simulation outputs proved the success of the control schemes used.