Abstract
Summary. The dynamically rising demand for electricity must be satiated by both conventional and unconventional power sources. PV electricity generation is essential. The installed PV sources are not used to their full potential due to low irradiance and poor weather. The goal of many research publications was to maximize PV power using different MPPT approaches. In order to extract the most power under the aforementioned circumstances, this study introduces a novel notion of using a voltage boosting PV panels. Additional PV panels are used in the suggested way to provide enough voltage and current. Using a voltage-boosting PV panel, a 20 kW panel is examined for low irradiance and unfavorable weather conditions. In a proposed method, results are compared with the previous INC MPPT method using a 20-kW panel. Through the power analysis, the proposed method extracted 1277.5 kW of power per year that is more than the INC MPPT method, and Rs. 10,220 per year was benefited during low irradiation alone. The power extraction and cost benefits are similar in cloudy and misty conditions. With power, cost, and efficiency analyses, the new method is contrasted with the traditional incremental conductance method and perturb and observe methods. Simulations were run using the MATLAB/Simulink programme, and experimental results were assessed using the appropriate hardware setup.
1. Introduction
Due to the rising energy needs and the need to make power in a way that is good for the environment, the PV generator is the one that is used the most. Maximum power point tracking (MPPT) techniques are used in [1] to get the maximum power possible from the PV panel while accounting for variations in actual voltage and current. Current, voltage, curve-fitting, gradient descent, slide mode, incremental resistance MPPT, and AI-based methods such as fuzzy logic, neural networks, ANFIS, and hybrid methods were discussed, and the benefits and drawbacks of each were tallied based on different criteria [2].
The performance of PV panels is primarily influenced by irradiance, ambient PV cell temperature, and load impedance. In the study of [3], MPPT characteristics are compared. For a ramp change in radiance (600–1000–700 W/m2) and a step change in irradiance (300–600–300 W/m2), (400–1000–400 W/m2), and (500−1000 W/m2) [4, 5] and for fixed and variable increment techniques, the responses of several MPPT techniques are compared. For a small-scale PV power system, the effect of temperature is taken into account and an MPPT is constructed [6].
Most commonly, standalone mode operation of a single PV source is used to develop several MPPT approaches. To achieve the MPP with the reference of the output values of the systems, the method was implemented in the incremental conductance (INC), perturb and observe (P&O), and constant voltage controller (CVC) methods [7]. The modified IC method based on the new average global peak value was implemented in the existing INC method, and improved efficiencies are tabulated [8]. A direct control structure and buck-boost converter were implemented in both the P&O and INC methods. The results yield 98.3% efficiency in the P&O method and 98.5% in the INC method [9]. In these same methods, the field-programmable gate array (FPGA) was used in the high-speed test algorithm in the loop feature [10]. The soft MPPT technique is proposed in both P&O and INC methods to solve the issue of continuous steady state oscillations [11]. Problems with grid-integrated PV systems such as low active power, poor MPPT performance, and power loss[12]. Intelligent controllers with convertors are used with fundamental MPPT techniques like IC, P&O, and CVC to address this complexity [13]. The PV terminal voltage is periodically perturbed and compared to the prior value using the perturb and observe (P&O) approach. The P&O output is fluctuating slowly as the air conditions approach the maximum power operating point (MPOP). The MPOP deviated when the meteorological conditions changed quickly [14]. In the constant voltage (CV) approach, the PV voltage is matched to the reference voltage closer to the maximum power point. In contrast to other approaches in [15], the incremental conductance (IC) method draws maximum power at lower and rapidly varying irradiance conditions.
Power converters serve as MPP trackers by changing the power switches’ duty cycle [16]. Three dynamic test operation procedures, such as day-by-day operation, stepped operation, and EN50530 operation procedures, were introduced in P&O, VSSIC, and the hybrid step-size beta method [17]. Soft computing methods such as Kalman filter, fuzzy logic control (FLC), neural network, partial swarm optimisation (PSO), ant colony optimisation (ACO), artificial bee colony (ABC), bat algorithm, and hybrid PSO-FLC are introduced, and the results are computed [18]. In standalone or grid-connected PV systems, single or double power converters are used depending on the load requirements [19, 20]. The single stage inverter (SSI) is used in place of the double stage converter to reduce costs and the number of components [21]. The PV parameters are adjusted to keep the DC motor parameter constant at various levels of irradiation [22]. Using PWM pulses from MPPT, the conductance value of the power converter can be changed [23]. A solo PV system with a basic resistive load was simulated under varying weather conditions (−25 C to −50 C) [24, 25]. A variable step size incremental conductance is created to enhance the dynamic and steady state performance of the incremental conductance approach in load impedance change [26].
A battery energy storage system (BESS) is added to the PV system for residential applications in order to maintain the voltage level and prevent power supply interruptions [27]. To extract the most power possible, the PV is matched with the residential load line. For a single stage inverter PV system, constant and changing insolation (300 W/m2 to 700 W/m2) is taken into account, and the MPPT controller is built to run in standalone or grid linked mode depending on the PV output availability. By integrating one cycle control with MPPT, a single stage inverter with MPPT that increases power output by 3% and has an efficiency of more than 90% is increased to 95.67% [28].
The computational complexity of fuzzy logic controllers is lower than that of traditional controllers. Performance of a fixed step size (1000 W/m2 to 500 W/m) controller is evaluated with fuzzy logic with particle-swarm-optimization-based MPPT. Cell temperature will not have an impact on the power factor and the dc link voltage as they are independently managed [29] for the grid connected single stage inverter for step change in solar irradiation. The fuzzy controller’s membership function shape is changed to regulate the distance between its operational and maximum power points, and the increment in conductance is changed to be proportional to solar irradiation [30]. An adaptive fuzzy logic MPPT controller is proposed and tested for grid-connected PV systems [31] in order to enhance simple-fuzzy-logic-based MPPT. There is discussion of several single stage and multistage inverters. Grid-connected PV generators use unidirectional inverters to allow power to flow from the source to the grid. When using grid-connected PV with local loads or stand-alone PV with reactive loads, a bidirectional converter is used. The development of an adaptive neuro fuzzy inference system (ANFIS) PSO-based MPPT approach took into account ten different patterns of temperature and solar insolation [32]. To improve the short-term PV power forecasting, an ANFIS-based MPPT controller with a combination of GA-PSO is implemented.
The use of voltage/current-based ANN MPPT algorithms is encouraged because the difficulty of hardware implementation and the cost of sensors prevented consideration of irradiance and temperature fluctuation [33]. A long-term study is conducted to determine the accuracy. The ANN-based MPPT is constructed, and the effectiveness in locating the ideal operating point for stationary modules with a slope of 30 degrees is shown for various seasonal variations [34].
To address power quality improvement and safety concerns, various isolated microinverter topologies were considered for grid-connected systems [35]. The incremental conductance method is chosen from the literature review because it performs better than other MPPT techniques, particularly for changeable irradiance in grid-connected PV systems. The majority of studies used constant irradiance, while some of them also used irradiance changes of more than 400 W/m2. In order to obtain the greatest power for a sudden change in irradiance, a grid-connected PV system with a new MPPT technique is suggested in this research. The servo mechanism and new MPPT approach are proposed at lower irradiances (250 W/m2) to obtain the maximum power, and the uplift of power from source to grid is thoroughly studied [36]. The biased three-winding transformer performance was analyzed, and the result obtained through the biased MPPT technique in INC MPPT methods is taken into reference [37].
According to a literature review, no additional equipment has been employed to get the most power possible from the panel thus far. In this study, a novel method for obtaining MPPT is presented employing extra devices.
This section gives a quick overview of various PV systems and their MPPT methods that are described in the literature. Problems encountered when connecting the PV system to the grid and various approaches taken to achieve optimal efficiency are highlighted. The reference papers provide a brief description of the benefits and drawbacks. It introduces the idea of extract maximum power using additional devices.
2. Overture of the Proposed System’s Methodology
2.1. Functional Block Diagram of the Proposed System
In the proposed method, the PV generator is connected to the microgrid through a couple of inverter and transformer. During low irradiance, the auxiliary transformer output voltage is added to boost the PV voltage and produce the power with the help of feedback power from the grid through the impulse integrated inverter MPPT method.
The proposed impulse integrated inverter MPPT approach for grid-tied PV generators is shown functionally in Figure 1. Through a couple of inverters, filter circuits, and transformers, the PV module is connected to the single phase grid. An inverter and a filter circuit are used at the front stage of both the transformer to convert the DC voltage of PV to AC voltage. The main inverter is rated highly, while the auxiliary inverter is rated lower. Both main transformer and auxiliary transformer secondary windings are linked together in series. The secondary windings of both transformers are connected to the grid. The secondary voltage of the auxiliary transformer is added to increase the PV voltage to match the grid voltage level. The MPPT controller receives Ipv and Vpv from the PV array output terminals along with the Irr reference. The MPPT controller’s pulses cause the inverter circuit’s input conductance to change accordingly. Inverter switches enable the PV to produce the most power possible. The correct sensors are positioned in the correct locations in order to obtain the reference values of voltage and current.
In this proposed model, the PV panel is divided in to two parts. They are as follows:(1)Main panel(2)Auxiliary panel
During normal irradiation, switches S1 and S2 are in the closed state, and both panels are connected to primary winding 1.
When there is not enough sunlight, the voltage that is present across the primary winding of the transformer is not high enough to allow the power that is available from the photovoltaic panel to be transferred to the secondary side of the transformer, which is connected with the load. After this point, the switch S1 and the switch S2 will be turned to the OFF position. Because of this switching operation, the auxiliary photovoltaic panel is now connected to the second primary winding of the transformer, and there is now an adequate voltage produced across the primary side of the transformer.
2.1.1. Proposed System Modeling
The equivalent circuit for solar cell shown in Figure 2 is represented as a current source influenced by the photons is connected in parallel with diode which represents barrier in the PV cell and with the series connected resistor RS and the parallel connected resistor RP. Kirchhoff’s law is applied in equation (1) to get the current obtained from the PV. PV current variation is proportional to the change in the environmental changes like irradiance and temperature changes which leads to the nonlinearity behavior. Hence, the maximum power from the PV is not easily taken and the curve changes with respect to the atmospheric conditions. To overcome this struggle, some (maximum power point tracking) MPPT algorithms are developed to track the curve and extract the available maximum power from the PV. Conductance of the PV is matched with that of the load. Relationship between the impedance values is given in equation (2). Along with the conventional power equation, the conditions for power transfer from source to grid are depicted in equations (3) and (4).where is output current in the PV panel, is current in the PV panel, is current through the parallel resistor, and is current through the parallel resistance.where is total impedance, is impedance in the main inverter circuit, is impedance in the auxiliary inverter circuit, is impedance in the main filter circuit, is impedance in the auxiliary filter circuit, is impedance in the main primary side of the transformer, and is impedance in the auxiliary primary side of the transformer. To transmit power from source to grid,andHere, is output voltage of the PV, is grid voltage, and is grid current.
The PV system properly works at higher irradiance value is shown in Figure 3. But for lower irradiance value, it affects the power transfer from source to grid, as it cannot satisfy the condition. The obtained value of PV voltage and grid voltage relation is given in (5) which is not as in (3) and (4). The voltage and current equations for the PV system during lower irradiance are given in equations (6) to (11).
At lower irradiance,where, is output voltage of the main PV and is output voltage of the auxiliary PV.where is voltage across inductor in the main circuit, is voltage across capacitor in main circuit, is main circuit primary voltage, is voltage across inductor in auxiliary circuit, is voltage across capacitor in auxiliary circuit, and is auxiliary circuit primary voltage.
At higher irradiance,
To satisfy the condition for power transfer from source to grid, an auxiliary transformer is brought into the system. The required modification needed is obtained in equations (13) and (14).
At lower irradiance,
New conditions for power transfer from source to grid are obtained from (15) and (16). The turns ratio of the auxiliary transformer is given in equations (17) and (18).
Condition for power transfer from PV source to grid,
The overall simplified diagram is given in figure 3
Equation (19) shows the computation of load angle from the q component of the auxiliary capacitor voltage and the auxiliary capacitor voltage .
Equation (20) gives the relationship between the voltage components and .
The difference between the actual value and measured value gives the . Equations (21) and (22) give the value of and .
Let us consider , the required modification in the impedance of the PV’s output side is getting as follows:
The load angle δ1 is obtained from the output power of the main inverter and the maximum PV power.
Current mode of a grid connected PV converter is considered in Figure 4
The relationship between the input vector and output vector of the PV inverter can be represented as follows:
The converter output impedance matrix is constructed as follows:
To analyze the converter system, the following model is constructed:
Input admittance of the converter derived from the PV impedance is as follows:
The cross coupling coefficients are constructed as follows:
From the analysis of equation (29), the required values of and are calculated with the help of δ1 and δ2 which values are generated with the help of phase locked loop.
An MPPT controller shown in Figure 5, controls the voltages that come out of the main PV panel and the other auxiliary panel. In this controller, the tabulated available input voltage is taken as a reference and compared with the output voltage; from this difference, the MPPT controller computes the value of the power angle for inverter 2, which is connected between the auxiliary PV panel and primary winding 2. Also, the Vpv and Ipv values are calculated through the suitable sensors, and the current IRR value is taken as a reference value, then the MPP value is computed. The driver circuit sends the PWM signal to both inverters and obtains the maximum power from the PV panel.
In Figure 6, the computed PLL value of the main PV panel inverter δ1 and auxiliary panel inverter δ2 is generated through the PLL circuit.
2.2. Working Methodology of the Proposed System
2.2.1. Flowchart
The execution steps for the proposed scheme are pictorially depicted in Figure 7.
(1) Algorithm. The algorithm of working methodology is given as follows:(1)Start the programme(2)Measure the voltage values of PV and grid and secondary of the transformer(3)Find the voltage and current values according to the irradiance level and set it as maximum value and fix the new value of secondary voltage(4)Find the value in the voltage and current parameters(5)If ∆V, ∆I, ∆VSy = 0, then ensure the PV current and voltage equals the maximum value(6)If ∆V does not equal to zero, check the ratio of ∆ values of I and V equals to the negative value of the ratio of I and V(7)If that ratios will not equal then, compare the ∆ ratio with actual parameter ratio(8)If ∆ ratio is greater than the negative value of actual parameters ratios or the ∆ value of current is greater than zero, then increase the voltage value of PV(9)If ∆ ratio is lesser than the negative value of actual parameters ratios or the ∆ value of current is lesser than zero, then decrease the voltage value of PV(10)If the ∆ value of VSy is not equal to zero, then add the ∆VSy to the secondary voltage value of transformer by adding the auxiliary circuit to get the new value
The amount of additional PV panel current () is injected from the additional PV panel with the help of the controllers. Due to , the required voltage across the primary winding is successfully created and it will drive the available power from the main PV panel to grid. The proposed simulation setup includes 20 kW panel.
3. Simulation and Analysis of the Proposed Method
Table 1 provides a list of the simulated system parameters for the proposed technique.
3.1. Simulink Block Diagram and Resultant Waveforms
Three elements make up the suggested system simulation base model for proposed MPPT. As shown in Figure 8, they are the PV array block, control circuit, and power circuit.
3.1.1. Implementations of the Simulink Block Diagram
Figure 9 depicts the simulation of the suggested system. It is split up into three main sections. The first installation has two 20 kW PV arrays. Grid-integrated circuits and a transformer with two primary and one secondary winding make up the power circuit. All control components and units are present in the control circuit.
Table (2) describes the varying radiation from the sun between 7.00 am and 5.30 pm.
3.2. Power Circuit
On the PI INC transformer, the power circuit is made up of two primary windings and one output winding. One input winding is linked to the inverter from the PV panel 1, and another input winding is connected to the inverter from the PV panel 2 and is controlled by the appropriate controller. The setup is called as PI INC block. The current generated by the second winding is used to raise the transformer’s output voltage. The voltage is smoothed using an LC filter. Figure 10 depicts the previously mentioned configuration.
3.3. Control Circuit
The filter circuit is employed in the simulated power circuit depicted in Figure 11 to cancel out the undesirable signal. For MPPT, a mathematical algorithm is created to determine the value of the needed second PV panel voltage with the help of the computation block. The error values are calculated and provided to the PID controller in this stage. The PWM generator sends output from the PID controller to the VSI. Finally, the secondary winding from the second PV panel receives the computed voltage.
The PV panel’s terminal voltage and current are measured, and ripples are eliminated using an appropriate filter. The PV terminal voltage and current are used to instantly calculate the change in conductance values. Figure 11 illustrates the difference between the actual and reference voltages, which is used to compute the required second PV panel voltage. Due of the proposed system’s grid connectivity, synchronization is crucial to grid integration. To track the values of δ1 and δ2 in this method, a single-phase PLL is employed. In the suggested inverter system, this value is used as a reference to generate the modulating signal.
The simulation control circuit depicted in Figure 11 is essential to the system methodology that is suggested. Through the specific computational block, it regulates the system’s output.
3.4. Proposed System Simulated Output
3.4.1. Solar IV Curve and Solar PV Curve Characteristics
The PV and IV properties of the PV module and the array of PV modules used in the suggested simulation system are shown in Figures 12.
3.4.2. Case 1: Low Irradiation (7.00 am to 9.00 am and 4.00 pm to 5.30 pm–250 W/m2 to 350 W/m2)
PV terminal current and voltage values are given in Figure 13. Initially during the low irradiation 7.00 am to 9.00 am (0 sec to 1 sec) and 4.00 pm to 5.30 pm (2 sec to 3 sec) with no load condition, the current and voltage values of the PV panel is very low. But in the normal irradiation, both values got improved.
The electricity drawn from PV is depicted in Figure 14. The proposed method extracts more power than the traditional method when the irradiance is low.
The load power that is maintained at both low and high levels of irradiation is shown in Figure 15.
Figure 16 shows the grid power for irradiance level. The grid provides the necessary extra power to the load when the PV power is insufficient to meet the load’s needs. If there is more PV power available than what is needed to meet the load, the extra PV electricity is injected into the grid. The grid power is positive and lower than the traditional incremental MPPT during the 0 sec to 1 sec when power flows from the grid to the load. The extra PV power is delivered into the grid between 1 and 2 seconds, making the grid power negative. The grid power is negative in the proposed method whereas it is positive in the conventional way during the time interval of 2 to 3.5 s when the available PV power is marginally larger than the load requirement.
The auxiliary inverter’s power angle variation is seen in Figure 17. During the low irradiation period, the auxiliary unit is connected with the auxiliary inverter. The auxiliary inverter power angle is generated through the PI INC MPPT controller and this power angle δ is used to improve the transformer primary side voltage.
The main and auxiliary inverters' peak to peak and rms voltages are displayed in Figure 18 correspondingly. While the auxiliary inverter voltage level is dependent on the PV voltage, the main inverter maintains its voltage level. The auxiliary inverter output voltage is 0 since it is not necessary when the PV voltage is adequate to power both the load and the grid.
The auxiliary inverter current is shown in Figure 19. No current is drawn from the inverter when the radiation level is high. The inverter current is almost 1 A between 0 and 1. Due to biasing, the inverter current is high between 2 second and 3.5 second.
4. Power and Cost Analysis for the Proposed System
The power extracted from the 20 kW PV panel is examined and contrasted with the existing incremental conductance MPPT method. The following two categories are used to underpin investigations:(1)Low irradiation. Table 3 compares the cost of the proposed system to the present system during the low-irradiation period as well as power extraction per hour(2)Irradiation due to cloudy and misty condition. Table 4 compares the existing system’s cost analysis and electricity extraction per hour during the overcast and misty period with the proposed system
4.1. Low Irradiation
Comparison of the cost of the proposed system to the present system during the low-irradiation period as well as power extraction per hour is given in Table 3.
4.2. Cloudy and Misty Conditions
Comparison of the existing system’s cost analysis and electricity extraction per hour during the overcast and misty period with the proposed system is given in Table 4.
4.3. Extracted Power Analysis
Annual power extraction analysis of proposed and existing MPPT methods energy value are given in (Table 5).
4.4. Cost Analysis
Annual cost analysis of proposed and existing MPPT methods energy value is given in Table 6.
Figures 20 and 21 contrast the proposed PI INC approach with the current INC method by providing a visual depiction of energy extraction and cost analysis.
The suggested methodology is explained in this section. The choice is made between the transformer and the additional panel. The transformer was chosen to preserve the voltage profile by adding the necessary voltage. Present is the implementation plan for the increased voltage approach. There is provided a functional block diagram of the suggested system. The PI INC MPPT method’s dynamic equation is derived. In addition, provided are the model’s algorithm and flowchart. In terms of power and cost analysis, a comparison is made between the present and proposed approaches.
4.5. Comparative Analysis of Power Extraction during Varied Irradiation
Table 7 describes the improvement of power developed using the proposed methodology (20 kW Panel).
In Section 3, where simulation parameters and their corresponding values are presented, the suggested method is simulated in full. The method’s simulation block module, control scheme, and power circuit are described. The PV array’s V-I and P-V characteristics are displayed. It is possible to obtain simulation results for the PI INC MPPT method and compare them to INC MPPT. The outcomes demonstrated the advantages of the PIO INC MPPT. The proposed system’s daily extracted power from the PV was substantially improved according to the simulated output waveforms and data values.
5. Experimental Evaluation of the Proposed System
5.1. System Setup
A simplified simulation model was used to create the tangible prototype for the Focused Method. Table 8 gives the component ratings for the trial system. Two single-phase inverters constructed using an IGBT power module from SEMIKRON and one auxiliary unit make up this circuit. A secondary winding and a primary winding with two inputs each make up the proposed three-winding transformer. One voltage smoothing capacitor and the secondary winding are linked in parallel to the grid. Through the inverter circuit, one primary winding is linked to the PV source, while a second winding is linked to the auxiliary PV source. The required supply is acquired from the auxiliary PV source through the Inverter and it derived with SEMIKRON’s-based voltage control circuit. PV source 1 and the auxiliary the corresponding sensor ratings listed in Table 8. Auxiliary PV source’s (PV source 2) voltage and current values are measured by suitable sensors and the corresponding sensor ratings listed in Table 8. The suggested control strategy was created in MATLAB/Simulink using the Simulink coder shown in figure 22, and it was then implemented in the TI Launchpad f28379 d. The power control circuit in Figure 23 was isolated using the TLP250, which also served as the power module’s driver. Figure 24 depicts the deployment of the whole experimental evaluation system.
5.2. Experimental Evaluation Setup of Hardware Photo
The hardware input supply for the proposed system comes from a 1 kW PV panel is shown in Figure 24. While drawing power from the PV, three-winding transformers are needed (two primary windings and one secondary winding). Between the primary winding of the transformer (0–15) V and (0–15) V/230V and the PV panel, there are two inverters connected. The following components: a rectifier, voltage controller, and a TI launch pad f28379 d Texas board controller are used for the control unit, as illustrated in Figure 22.
5.3. Control Circuit Implementation Using SIM Coder
The terminal voltage and current of the PV panel are measured, and then any ripples in the signal are removed by a filter that is appropriate for the situation. The voltage and current readings at the PV terminals are immediately put to use in order to calculate the values for the change in conductance.
The auxiliary voltage provided by the PV system is determined by the immediate power availability. The control circuit is responsible for determining the required auxiliary voltage, with the difference between the actual voltage and the reference voltage being depicted in Figure 22. Since the proposed system will be connected to the grid, synchronization will play an important part in the process of grid integration. For the purpose of achieving frequency tracking of the value of, this method makes use of a single-phase phase-locked loop (PLL). Within the framework of the proposed inverter system, this value of will serve as a reference for the generation of the modulating signal.
An optocoupler TLP250 and a bridge rectifier are used in the driver circuit depicted in Figure 25 to primarily control the voltage.
5.4. Hardware Result
The auxiliary PV panel voltage is shown in Figure 25. During normal irradiation the auxiliary voltage is connected to the main panel. During low irradiation, the voltage value is reduced in 1 to 2 seconds, and then the auxiliary PV panel is connected to the second winding of the primary winding in 2 to 3 seconds.
In Figure 26, the voltage peaks during the initial period. When the auxiliary unit is connected to the main panel, there is no voltage to flow to the second winding through the auxiliary inverter on the primary side of the transformer. When the switches S1 and S2 open, the auxiliary unit is connected to the transformer primary winding 2.
The RMS value PV panel 2 is shown in Figure 27. When PV panels 1 and 2 are connected to the primary winding, during this period, the RMS value of the auxiliary unit is near zero. The RMS value is increased after PV panel 2 is connected to the auxiliary unit.
Initially, PV panel 1 and PV panel 2 are connected together, and the combined PV output is connected to the load through the transformer. At no load, the combined PV output is high. During low irradiation with load, the output value of PV 1 is reduced, as shown in Figure 28.
Figure 29 shows how the power is boosted due to the improved voltage from the auxiliary unit. After the switches are opened, the auxiliary panel is connected to the auxiliary unit.
Figures 30(a) and 30(b) depict the proposed PV system’s entire impact. The integrated PV system produces its most electricity under typical irradiation. In 0-1 seconds, it is explicitly mentioned. If there is no power transmission from the period of 1 sec to the period of 2 sec, the radiation period is low. The PV panel then supplies the load with the available power following the separation of the auxiliary panel, which takes place in 2 to 3 seconds.
(a)
(b)
The PLL value of power and its angle are shown in Figures 31(a) and 31(b). When compared to the loading condition, the power angle is superior when it is obtained at low irradiation after one second.
(a)
(b)
Hardware of the proposed system is developed. Voltage and current of the proposed PI INC MPPT technique were obtained. Extraction of continuous power irrespective of the change in irradiation was presented. Hardware results justify the implementation of proposed MPPT technique as it ensures maximum power extraction under varied environmental conditions.
6. Conclusion
The proposed system, PI INC MPPT, was successful in drawing energy from the solar PV panel during periods of low irradiance. Through research, simulation modelling and effective hardware outcomes, this technique was verified. This unique proposed MPPT approach using an auxiliary unit extracts an additional 3 MW of electricity per year when compared to the current method. The planned three-winding transformer was built with an auxiliary unit that produces the right output, achieving the ultimate objective. The Texas board controller proved successful in controlling the voltage needed for the primary winding. Further research is possible using the proposed MPPT with auxiliary unit model because there is a lot of room for interpretation in terms of the field’s potential. The current economy and the electricity demand are thought to be better suited for this methodology.
Abbreviations
| MPPT: | Maximum power point tracking |
| PV: | Photovoltaic |
| PWM: | Pulse width modulation |
| THD: | Total harmonic distortion |
| PLL: | Phase locked loop |
| CV: | Constant voltage |
| INC: | Incremental conductance |
| VSSIC: | Variable step size incremental conductance |
| P&O: | Perturb and observe |
| ADC: | Analog to digital |
| : | First primary winding voltage |
| : | Second primary winding voltage |
| : | Photovoltaic terminal voltage |
| : | Photovoltaic terminal current |
| : | Power from the PV panel |
| : | Auxiliary PV current |
| : | Auxiliary PV voltage |
| : | Maximum PV voltage |
| : | Maximum PV current |
| : | Maximum PV power |
| : | Additional impedance. |
Data Availability
The author gathered the information for their manuscript from the following text books. Data on the world’s use of renewable energy is taken from “Raturi, A. K. (2019). Renewables 2019 global status report.” The information on the radiation comes from “D. Rekioua, Ernest Matagne, Modelization, Simulation, and Control. Science & Business Springer.”
Conflicts of Interest
The authors affirm that they have no conflict of interests with regard to this study.