# Multi-input rectifier stage for a system of hybrid PV/wind driven PMSG

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## Abstract

This article depicts a novel configuration of the multi-input rectifier stage for a system of hybrid PV/wind driven permanent magnet synchronous generator (PMSG). Maximum power point tracking (MPPT) techniques are applied to extract maximum power from the wind turbine and the solar module when it is obtainable to increase the PV efficiency and wind driven PMSG. Using dc/dc converter topology individually with control of MPPT to produce power. Perturb and Observe (P&O) MPPT algorithm is applied for PV device that the dc voltage is utilized as perturbation variable whereas, in wind system, the perturbation variable is utilized in modified P&O MPPT algorithm. In this work, the main contribution is the implementation of a PV/wind driven PMSG hybrid model in the form of Matlab Simulink based on multi-input rectifier stage. In this study, a multi-input rectifier topology for grid-inserted PV/Wind driven PMSG model has been applied. MPPT based control of PV supply is carrying out on cuk converter topology. The multi-input rectifier stage has the ability to eradicate current harmonics. Therefore, no extra input filters are required. Matlab/Simulink program is applied in the present study to implement the modeling and analysis of grid-inserted PV/wind driven PMSG based on multi-input rectifier topology.

## Keywords

Hybrid renewable energy system (HRES) Wind driven PMSG system PV system MPPT control techniques Multi-input rectifier topology## 1 Introduction

The expression hybrid renewable energy is applied to depict any energy system with more than one form of generator ordinarily a traditional generator powered by diesel and renewable energy sources like photovoltaic, wind energy and hybrid system [1, 2]. Hybrid energy system is to give an economical and sustainable energy for the rustic electrification which uses a collection of non-renewable energy resources such as fossil fuel, nuclear power or a collection of renewable energy resources such as PV and wind [3]. This is clean energy and obtainable in nature. The merits above non-renewable fossil fuel based on power generation, like low contamination and high efficiency [4]. Solar system is one of the ersatz clean energy resources that are paid close interest by humans because, it is very significant to have an effective and suitable MPPT technique for the PV device [5]. There are several types of converter topology, between them we have chosen the most appropriate type which is boost-converter topology for our design, because it is widespread no isolated converter, its ability of increasing the voltage where it is also popular to have low speed wind and the impedance connected to the generator in our case need to be reduced to have it equal to the internal impedance in the generator. Occasionally this type is known the step-up converter [6]. The wind power at most depends upon geographical features and climate conditions and change occasionally. Thence, it is needful to build a system that can produce maximum power for all working conditions. Lately, PMSG is applied for wind generating system because of its merits like best reliability, low maintenance and more efficient etc. For maximum power transfer in each wind speeds, the converter should be able to decrease PMSG terminal voltage in low speeds and raises it in high wind speeds. Numerous hybrid PV/Wind power systems with control of MPPT technique have been suggested previously [7, 8]. In the present article, a multi-input rectifier stage for grid inserted hybrid PV/Wind driven PMSG system has been applied. Control of MPPT for the PV source is carrying out on cuk converter. The multi-input rectifier converters have the ability to cancel the high current harmonics. Therefore, no extra input filters are required. Fusion of multi-input rectifier topology works completely for individual and simultaneous operation. MPPT can be addressed by several ways, for example: P&O, constant voltage (CV) and incremental conductance (INC) etc. It is widely applied, mostly for low-cost applications [9]. These days, utilization of solar energy includes use of PV cells, solar thermal power and solar water heating. In general, the PV device consists of PV generator which is a collection of series-shunt electrically attached solar panels. There are two techniques of our study, with and without tracking systems. The present article aims to investigate the performance of PV-wind driven PMSG hybrid energy system under various weather conditions based on multi-input rectifier topology.

The rest of the present article is arranged as follows after introduction: In Sect. 2, modeling analysis of PV system configuration is discussed. In Sect. 3, modeling analysis of wind energy conversion system (WECS) and its control strategy are presented. The proposed PV-Wind driven PMSG hybrid energy system and its components are illustrated in Sect. 4. The simulation results about the performance of hybrid model are included in Sect. 5. In Sect. 6, summary of findings is addressed.

## 2 Modeling analysis of (PV) system configuration

_{sh}) is very high, series resistance (R

_{s}) is very low and enough to neglect the two terms to simplify the characteristic equation of the solar cell model to become:

_{L}: Light-generated current under a given insolation, I

_{0}: Diode saturation current and I

_{sh}: Shunt current, V

_{D}: Voltage across the diode, q: Electron Charge (1.60217 × 10

^{−19}C) and k: Boltzmann Constant (1.3807 × 10

^{−23}J/K), m: Dimensionless ideality factor of the diode, STC: Standard test condition, T: Cell temperature (K), R

_{s}: Series resistance of the cell (Ω) and R

_{sh}: Shunt resistance of the cell (Ω).

_{oc}) and (I

_{sh}) are the two main parameters applied which depicts the electrical performance of the cell.

### 2.1 Analysis of solar PV cell performance with changing irradiance and temperature

The expression irradiance is known as the measure of power density of sunlight given at a site on the earth in (w/m^{2}), while the measure of energy density of sunlight known as irradiation. The two terms are associated to solar elements. With the increasing solar irradiance both (V_{oc}) and (I_{sh}) rises and therefore, the MPP changes.

Temperature plays other main factor in determine solar cell efficiency. As the temperature rises the average of photon generation rises therefore, the reverse saturation current rises fastly and this decreases the band gap.

^{2}with constant temperature at 25 °C. We can observe that, the module current is proportionate to the radiation, whereas the V

_{oc}changes a bit with irradiation. Table 1 shows the values of various MPP through changing of irradiation, the MPP increases from 42.85 at 250 to 150 at 1000 W/m

^{2}. Therefore, the rise of irradiation permits the increase of maximum power point.

Values of various MPP through changing of irradiation

Irradiation in (W/m | 250 | 500 | 750 | 1000 |

Power (W) | 42.85 | 75 | 118.53 | 150 |

Also, temperature is an important element in the behaviour of PV module. Figure 5a, b depicts, the increase in temperature leads to a clear decrease in the V_{oc}.

Values of various MPP through changing of temperature

Temperature in (°C) | 25 | 50 | 75 |

Power (W) | 108 | 135.45 | 150 |

### 2.2 MPPT control techniques for PV system

MPPT technique is applied to ameliorate the efficiency of solar panel, WT and they regulated to work at their point of maximum power. The MPPT algorithm relies on an initial reference of rotor speed for the WT and voltage for the PV array. The conformable power outputs for the two devices are measured. The delivered power by a PV device of one or more PV cells is depend on the three factors which are irradiance, temperature and current drawn from the cells. There are numerous techniques to maximizing the power from a PV device, several commonly traditional techniques for MPPT available in the literature [13, 14, 15, 16], in general, the most widely-used are presented below:

#### 2.2.1 Constant voltage (CV) technique

_{ref}. The magnitude of V

_{ref}is regulating equal to the V

_{MPP}of the PV module or to other calculated better constant voltage. So, measurement of the V

_{PV}is needful to set up the duty-cycle of the dc/dc Sepic by PI organizer. It is important to notice that if the PV panel is in low insulation status, the CV algorithm is more effectual than the P&O or the INC methods. Constant voltage (CV) is sometime integrated jointly with other MPPT methods. The constant voltage (CV) is implemented using the instruction flowchart as indicated in Fig. 6.

#### 2.2.2 Short-current (SC) technique

_{op}to a current power converter controlled. Actually, the working current I

_{op}for maximum power output is commensurate to the short circuit current I

_{SC}at different status of irradiance level (S) as in Eq. (4):

_{op}can be defined instantly by detecting I

_{SC}. So, this control technique needs measurements of I

_{SC}. So, it is needful to insert a static switch in shunt with PV array, to make the short-circuit status. It is remarkable to reminder that, through the short-circuit V

_{PV}= 0 thus, no power is provided by the PV device and no energy is produced. As in the earlier method, mensuration of the PV array voltage is desired for the PI regulator to get the V

_{ref}magnitude able to produce the current I

_{op}. The features of this technique it is simple, low cost to carry out and does not require an input. The demerits: irradiation is always properly at the MPP owing to differences on the array which are not appraised, data changes at different climate conditions and sites and also it has lower efficiency. The instruction flowchart of the SC method is illustrated in Fig. 7.

#### 2.2.3 Open voltage (OV) technique

_{MPP}is constantly near a constant percentage of the V

_{OV}. The k value is generally among 0.7–0.8. It is needful to upgrade V

_{OC}sometimes to compensate any temperature change. This technique necessitates measurements of the V

_{OV}if the circuit is opened. Once more it is needful to insert a static switch to the PV device; for this method the switch should be inserted in series to open the circuit. If I

_{PV}= 0 no power is provided by the PV device and therefore no energy is produced. In this algorithm also measurement of the V

_{PV}is desired by the regulator. Figure 8 shows the instruction flowchart for this method. The merits of this technique are comparatively low cost, very simple to perform. The demerits are slower response, not precise and may not work punctually at maximum power point.

#### 2.2.4 Incremental conductance (INC) technique

_{pv}/V

_{pv}to the incremental conductance dI

_{pv}/dV

_{pv}. The INC offers perfect performance at quickly changing atmospheric status where I

_{pv}and V

_{pv}are the PV array current and voltage, respectively. The instruction flowchart depicted in Fig. 10 illustrates the working of this technique. It begins with sensing the values of voltage and current PV module. Then, it computes the changes, \(\Delta {\text{I}}\) and \(\Delta {\text{V}}\) using the current and previous values. The merits of this method it can define the MPP without oscillating about this value. The demerits are: increase the computational time owing to slow of the sampling frequency follow from the high complexity of the technique compared to the P&O. Also the INC can perform unpredictably at rapidly changing atmospheric status.

#### 2.2.5 Perturb and observe (P&O) technique

### 2.3 Boost converter topologies

_{in}= typical input voltage, V

_{out}= desired output voltage, η = converter efficiency. The (η) is added to the equation, because the converter has to transfer the energy dissipated. This computation gives a more factual duty cycle than quite the equation without (η). The following step to calculate the switch current in order to determine the inductor ripple current.

_{s}= converter switching frequency, L = chosen inductor value. This equation is a good assessment for the suitable inductor:

## 3 Modeling analysis of (WECS) configuration

In this scenario, a resistor is applied as the load and the MPP will be indicated into maximum voltage through it. The diode bridge rectifier is utilized instead of a 3-phase controlled PWM in order to its low cost and high reliability. This section presents the WT converts the wind power into mechanical power in the rotor shaft. Thereafter, converted into electricity by using a PMSG. The voltage created by the PM machine is rectified by using a 3-phase passive rectifier that converts the AC voltage produced by the PMSG to a DC voltage.

_{P}depend mainly on λ when β equal zero degree. Figure 15 depicts the power coefficient (C

_{p}) of the wind turbine versus tip speed ratio (λ). Observed that, the C

_{P}optimum value is approximately 0.48 for λ equal to 8.1, the performance coefficient of a WT is affected by the ratio of tip-speed to wind-speed, as follows:

^{3},

*A*: Area of the circle swept by the rotor (m

^{2}).z, λ: Tip speed ratio of the wind system, λ

_{opt}: optimal tip speed ratio,

*β*: Pitch angle (degree), J: Moment of inertia, kg m

^{2}, W: Turbine rotor speed in (rad/s).

_{p}optimum value (C

_{p-opt}). Therefore, it is requisite to set the rotor speed at optimum rate of the tip speed ratio (λ

_{opt}).

### 3.1 Control of MPPT techniques for WECS

#### 3.1.1 Tip speed ratio (TSR)

In this type, it is desired to retain up the tip speed ratio (TSR) to an optimum value that extracted power is maximized by adjusting the rotational speed of the generator. In this case, optimal point can be known theoretically or experimentally and save as a reference. Although however, this type is fast response. However, the requisite of an accurate anemometer for measuring the speed of the wind causes the system more costly, especially for small scale of a WECS. Figure 18a depicts block diagram of a WECS with TSR algorithm.

#### 3.1.2 Power signal feedback (PSF)

The PSF requires the familiarity of WT maximum power curve that is tracked by its control mechanisms. The maximum power curves can be given through simulation or experimental tests on individual WTs. Figure 18b illustrates block diagram of a WECS with PSF algorithm. In this case, \({\text{P}}_{\text{m-opt}}\) is created by using a pre get power-speed curve. Wherever wind speed or the turbine speed is applied as the input. The controller decreases the error among optimum power and actual power.

#### 3.1.3 Hill-climb search (HCS)

The HCS is a mathematical optimization strategy applied to search for the local optimum point of a specific function. It is broadly applied in WECS by searching the optimal working point to extract maximum power. This control depends on perturbing a control variable in small step-size as depicted in Fig. 18c. The HCS control does not need prior knowledge of the WTs characteristic curve; it is simple and flexible. So, it fails to reach the points of maximum power at fast wind variations when applied for medium and large inertia WTs.

#### 3.1.4 Optimal torque (OT)

In OT the generator torque is controlled to get optimum reference torque curve according to P_{max} of the WT at a specific wind speed. Figure 18d depicts block diagram of a WECS with OT algorithm. Therewith, this control is widely applied in WECS. Furthermore, the OT curve that obtained mainly via experimental tests will change if the system ages and affect the efficiency of MPPT.

_{opt}: Constant determined by the WT and P

_{m-opt}: Optimal power curve,

*C*

_{p}: Non-dimensional power coefficient of the WT.

_{d}and I

_{d}is given by:

## 4 Maximum power control of hybrid generation system

### 4.1 Multi-input rectifier topology

_{1}, D

_{2}) from every converter topology. This configuration permits each topology to work normally singly within the case which one source is unavailable [23, 24].

_{1}turn-off and D

_{2}will always be on, the suggested circuit diagram be a Sepic-converter, the relation among the input to output voltage is expressed by Eq. (18).

_{2}turn-off and D

_{1}turns on and the suggested circuit diagram are a Cuk-converter as depicted in Fig. 21b. The relation between input to output voltage is expressed by Eq. (19). In two cases, each converter has step-up or step-down which provides more design flexibility within the system when duty ratio control is employed to implement MPPT management.

### 4.2 Modes of operation

_{1}is longer than M

_{2}, the switching will be state I, II, IV. Likewise, the switching will be state I, III, IV when the switch conduction intervals are conversely. For best explanation, the inductor current waveforms of every switching state are set as follows supposing that d

_{2}> d

_{1}, therefore only states I, III, IV are illustrated in this example. In this case, I

_{i,PV}is the average current from PV supply, I

_{i,W}is the RMS current after the rectifier (wind state) and I

_{dc}is the average output current. The key waveforms which present the switching states are illustrated in Fig. 23.

The mathematical model which relates the output voltage and the input sources (V_{W} and V_{PV}) will be given as follows:

*State I (M1 on, M2 on):*

*State III (M1 off, M2 on):*

*State IV (M1 off, M2 off):*

## 5 Simulation analysis and results

- 1.Parameters of PV Array
Module: CA Solar MS-150 M, Maximum Power (P

_{max}): 150 WOpen circuit voltage (V

_{oc}): 43.2 V, Short-circuit current (I_{sc}): 4.87 AVoltage at MPP (V

_{mp}): 34.4 V, Current at MPP (I_{mp}): 4.36 ACells per module (N

_{cell}): 72, Standard Operating Temperature: 25 °CMaximum irradiance level: 1000 W/m

^{2}

- 2.Parameters of Wind System
Type of generator: PMSG, Rated output power: 3000 W

Stator winding: Star connection, Number of pole pairs: Four

Frequency: 50 Hz, Stator resistance: 0.43 Ω/phase and Armature inductance: 8.35 mH

Inertia constant: 0.01197 kg m

^{2}, Fraction factor: 0.0012 N m s

Case Study (1): simulation results for PV system

Case Study (2): simulation results for wind turbine system

Case Study (3): simulation result of hybrid system using multi-input rectifier topology

## 6 Conclusion

This paper presents a detailed simulation of the PV/wind hybrid power system model. It is carried out under MATLAB/Simulink software. In this article, renewable energy resources are introduced like wind energy and solar system, the discussion presents a hybrid solar/wind systems to suppress the problems associated with both systems and using advantages aforementioned. The hybrid (PV-wind) is investigated and implemented by using MATLAB program. The P&O MPPT used for MPP tracking and illustrates the compassion between the generated power with and without the tracker. The numerical simulation results have proven the robustness of the proposed hybrid PV and wind energy in response to rapid changes in solar radiation and wind speed conditions.

## Notes

### Compliance with ethical standards

### Conflict of interest

Author wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome.

## References

- 1.Kumar PV, Suresh A, Rashmi MR (2016) Optimal design of fused chopper based standalone hybrid wind solar system. Indian J Sci Technol 9(21):1–6CrossRefGoogle Scholar
- 2.Abdullah MA, Yatim AHM, Tan CW, Saidur R (2012) A review of maximum power point tracking algorithms for wind energy systems. J Renew Sustain Energy Rev 16(2012):3220–3227CrossRefGoogle Scholar
- 3.Rezvani A et al (2015) Enhancement of hybrid dynamic performance using ANFIS for fast varying solar radiation and fuzzy logic controller in high speeds wind. JES 11(1):11–26Google Scholar
- 4.Singaravel MR, Daniel SA (2015) MPPT with single DC-DC converter and inverter for grid connected hybrid wind-driven PMSG-PV system. IEEE Trans Ind Electron 62(8):1–8CrossRefGoogle Scholar
- 5.Mohamed SA, El Sattar MA (2019) A comparative study of P&O and INC maximum power point tracking techniques for grid-connected PV systems. SN Appl Sci J 1(174):1–13Google Scholar
- 6.Pillai V, Antony N (2015) Integrated multi input CUK converter used standalone system for WECS and PV. Int J Res Adv Technol 3(9):75–85Google Scholar
- 7.Saravanan K, Kumar AS, Nandini N (2016) Design and simulation of hybrid renewable energy system (HRES) to supply three phase induction motor using fuzzy logic controller. JCPS 9(4):1922–1929Google Scholar
- 8.Mohamed SA (2018) Design, control and performance analysis of a grid-connected hybrid system. Egypt Int J Eng Sci Technol 24:18–26Google Scholar
- 9.Verma D, Nema S, Shandilya AM, Dash SK (2015) Comprehensive analysis of maximum power point tracking techniques in solar photovoltaic systems under uniform insolation and partial shaded condition. J Renew Sustain Energy Rev 7:1–27Google Scholar
- 10.Bhasme S, Revankar AP (2012) Modeling and analysis of single phase grid connected photovoltaic system. Int J Power Syst Oper Energy Manag 1(4):52–58Google Scholar
- 11.Habbati B, Ramdani Y, Moulay F (2014) A detailed modeling of photovoltaic module using Matlab. NRIAG J Astron Geophys 3(1):53–61CrossRefGoogle Scholar
- 12.Abdulateef J (2014) Simulation of solar off- grid photovoltaic system for residential unit. Int J Sustain Green Energy 4(3–1):29–33Google Scholar
- 13.Sera D, Mathe L, Kerekes T (2013) On the perturb-and-observe and incremental conductance MPPT methods for PV systems. IEEE J Photovolt 3(3):1070–1078CrossRefGoogle Scholar
- 14.Nemsi S, Barazane L, Diaf S, Malek A (2013) Comparative study between two maximum power point tracking (MPPT) techniques for photovoltaic system. Revue des Energies Renouvelables 16(4):773–782Google Scholar
- 15.Roberto F, Sonia L (2008) Energy comparison of MPPT techniques for PV Systems. WSEAS Trans Power Syst 3(6):446–455Google Scholar
- 16.Saleh EB, Matthew A, Volker P (2014) Overview of maximum power point tracking control methods for PV systems. J Power Energy Eng 2:59–72CrossRefGoogle Scholar
- 17.Carrillo C, Diaz-Dorado E, Silva-Ucha M, Perez-Sabín F (2010) Effects of WECS settings and PMSG parameters in the performance of a small wind energy generator. In: IEEE international symposium on power electronics, electrical drives, automation and motion, pp 766–771Google Scholar
- 18.Babu NR, Arulmozhivarman P (2013) Wind energy conversion systems—a technical review. J Eng Sci Technol 8(4):493–507Google Scholar
- 19.Smida MB, Sakly A (2015) Pitch angle control for variable speed wind turbines. RESD 1:81–88Google Scholar
- 20.Lalouni S, Rekioua D, Idjdarene K, Tounzi AM (2014) An improved MPPT algorithm for wind energy conversion system. JES 10(4):484–494Google Scholar
- 21.Sachan A, Gupta AK, Samuel P (2017) A review of MPPT algorithms employed in wind energy conversion systems. J Green Eng 6(4):385–402CrossRefGoogle Scholar
- 22.Hussain J, Mishra MK (2016) Adaptive maximum power point tracking control algorithm for wind energy conversion systems. IEEE Trans Energy Convers 31(2):1–9CrossRefGoogle Scholar
- 23.Kavitha N, Durgalakshmi K, Kishore B (2015) Modified converter topology for hybrid wind and PV systems. Int J Adv Res Electr Electron Instrum Eng 4(7):6702–6709Google Scholar
- 24.Sudharshan A, Yohan M, Shrujan RVK, Gayathri Y (2013) A hybrid wind-solar energy system using cuk–sepic fused converter. Int J Eng Res Appl 3(6):287–293Google Scholar