IRJET- Implementation of Conventional Perturb with different Load for Maximum Power Point Trackin

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Implementation of conventional perturb with different load for maximum power point tracking algorithm for photovoltaic system using an embedded microcontroller Ramya l1 ,Satish B. A2 PG student, Electrical and Electronics Department, Dayananda Sagar College of Engineering, Bengaluru Assistant Professor Electrical and Electronics Department, Dayananda Sagar College of Engineering, Bengaluru ---------------------------------------------------------------------***--------------------------------------------------------------------1

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Abstract - The traditional calculation of perturb and observe (P&O) is broadly connected because of its straightforwardness, ease and easy execution. Notwithstanding, it experiences hazards amid fast changes of climate as well as swaying around maximum control point (MPP) at enduring state.

Insecurities happen because of the wrong choice taken by the customary P&O calculation at the initial step change in obligation cycle amid the fast change in radiation. The purpose behind the unfaltering state wavering is the persistent annoyance and exchange off between step sizes and the joining time. This examination exhibits an altered P&O calculation to conquer such downsides. It utilizes a steady load system to help the regular P&O calculation for perceiving the reason for control change and to empower it in taking the correct choice at initial step change in obligation cycle amid quick difference in climate. The proposed calculation is reenacted utilizing a solitary sun based photovoltaic module of 80 W and a DC/DC help converter. It is approved tentatively and actualized inside an installed microcontroller. The exploratory setup exhibits a proposed demonstrates based plan procedure that utilizes estimations' information for MPP following frameworks' plan.

It joins equipment on the up and up recreation and model testing utilizing real climate estimations. Reproduction and trials demonstrate phenomenal outcomes.

Key Words: Maximum Control Point (MPP), Perturb & Observe (P&O).

1. INTRODUCTION The change of energy by methods for photovoltaic boards has continuously stimulated incredible enthusiasm because of the enduring increment in oil costs, the ecological contamination caused by hydrocarbons, also, a steady lessening in the costs of photovoltaic (PV) boards. By the by, the low energy effectiveness because of the transformation of sun based energy into electric energy is one of the fundamental snags to the far reaching increment of this kind of energy source. Consequently, the extraction of the most extreme conceivable energy of each board is the primary innovative test these days. A few calculations have been proposed in the writing on the greatest power point following (MPPT) issue, which have enlivened various methodologies to boost photovoltaic frameworks effectiveness under different irradiance conditions. For example, [1] demonstrates five diverse ways to deal with explain the MPPT: (I) following methods with steady © 2018, IRJET

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parameters, that is, calculations that consider, amid the most extreme power point (MPP) forecast, parameters, for example, constants, e.g., voltage of greatest control point autonomous of temperature and irradiance, straight reliance the PV current in MPP and the short out current [2], straight connection between voltage in MPP and open-circuit voltage [3], and so forth; (ii) following strategies with estimation and examination, to be specific, the look-into table strategy [4] and direct present control strategy [5]; (iii) following systems with experimentation, in particular, the annoy and watch (P&O) calculation [6] and its alterations [7,8]; (iv) following procedures with scientific estimation, in particular, incremental conductance (INC) [9,10]; lastly (v) following methods with insightful forecast (delicate figuring), which will be clarified in detail beneath. Delicate figuring based systems have uncovered an intense instrument to manage MPPT streamlining. Besides, the accessibility of superior and moderate micro controllers makes the usage of these calculations conceivable in down to earth circumstances.

These actualities have supported the look into on delicate processing based ways to deal with handle the MPPT issue.

Hence, in [11], an Artificial Neural Network (ANN) MPPT controller, in view of settled and variable advance size, is proposed. In this work the information required to produce the ANN demonstrate are created utilizing P&O. The controller is created in two stages: (I) a disconnected advance required to characterize the neural systems and went for finding the ideal structure (the quantity of layers and neurons, initiation capacities, parameters, and preparing calculation) of the MPPT controller; and (ii) an online advance where the ideal neural system MPPT controller found in the past advance is utilized as a part of the PV framework. Different works toward this path can be found in [12– 16]. In addition, other delicate registering procedures, for example, Fuzzy rationale control (FLC) [17– 21] what's more, Particle swarm enhancement (PSO) [22], can likewise be utilized for MPPT improvement. An intriguing paper where a wide range of strategies for MPPT are talked about is exhibited in [23].

1.1 Concept of conventional P&O algorithm Customary P&O calculation is the least difficult, least expensive and most prominently utilized as a part of training [16]. Be that as it may, it isn't strong in following the privilege MPP at fast changes of climate or load [7, 13, 24]. The flowchart of the essential P&O MPPT calculation is

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introduced in Fig. 1a. The fundamental P&O examines the P−V bend of PV module in scan for the MPP by changing the working point which is known as bother step, and afterward estimating the adjustment in P (ΔP),known as perception step. In the event that ΔP is more prominent than zero, at that point another perturbation is introduced in the same direction. If ΔP is lower than zero, the direction of the perturbation is changed. The P&O keeps searching for the MPP until it has found an operating point such that ΔP is closely to zero in any direction; this condition is called steady state. At steady state, the operating point oscillates around the MPP giving rise to the wastage of some amount of accessible vitality. These motions can be limited by diminishing the settled advance size, yet it sets aside generally greater opportunity to achieve MPP. The P&O continues annoying the framework keeping in mind the end goal to identify a change in the MPP (caused by an adjustment in the ecological conditions), which triggers another sweep [7, 8].

radiation bend amid a similar irritation K which brings about positive change in both power (ΔP) and voltage (ΔV) [13].

1.2 Performance of conventional P&O algorithm during rapid change of radiation.

Begin P&O algorithm

Measure Vpv(k) , Ipv(k)

Fig. 2 MPPT system and load change. a .Schematic diagram of MPPT system.

Calculate the power P(k) = Vpv(k) * Ipv(k) δVpv = Vpv(k) –Vpv(k-1) δP = P(k)-P(k-1)

b. Change of operating point with respect to load resistance.

The data of positive change in control what's more, voltage amid annoyance K + 1 will make calculation to increment voltage irritation as opposed to diminishing.

Subsequently, the working point moves from direct 2 toward point 3 as appeared in Fig. 1b.This wrong choice of traditional P&O calculation causing the working purpose of PV framework is strayed far from MPP because of progressive difference in climate as appeared in Fig. 1b.

Additionally, the progressive quick diminishing of radiation will go astray the working purpose of PV framework far from MPP as talked about in [2].

δP>0

δVpv >0

Decrease the module voltage

δVpv >0

Increase the module voltage

Decrease module

voltage

Increase module voltage

1.3 Behavior of conventional P&O algorithm during steady change of radiation.

Update History of voltage Vpv(k-1) = Vpv(k),P(k-1) = P(K)

Fig 1: Conventional P&O algorithm The progressive quick expanding of radiation causes float or unsteadiness issue because of regular P&O calculation.

Assume there is an increment in radiation level from 600 to 1000 W/m2 and the PV framework works at point MPP1 at bother K as appeared in Fig. 1b. At that point, the working point will be moved to another point 2 in comparing © 2018, IRJET

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The enduring difference in climate will cause wrong choice of P&O calculation at first irritation as talked about in quick difference in climate, yet the following annoyance will revise this wrong activity [8]. Assume there is an expansion in radiation level from 400 to 600 W/m2 also, the PV framework works at the relentless difference in climate will cause wrong choice of P&O calculation at first bother as examined in quick difference in climate, however the following bother will amend this wrong activity [8].Assume there is an expansion in radiation level from 400 to 600 W/m2 what's more, the PV framework works at MPP1 as ISO 9001:2008 Certified Journal

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appeared in Fig. 1c. At that point expanding of PV power and voltage will build voltage irritation and the working point from MPP2 will occupy at point 2 as appeared in Fig. 1c. The following irritation on the same P– V bend – without climate change – will be negative change in PV control (ΔP < 0) and the positive change in PV voltage (ΔV > 0) causing diminish in the voltage irritation towards MPP2 with consequent next annoyances as appeared in Fig. 1c.

Normally, the PV system operates close to MPP at steady weather and without change in load as shown in Fig. 2b. The load change causes the operating point of the PV system to move away – either right or left side – from MPP at point a of Fig. 2b. The increasing in load resistance from RL1 to RL2 will move the operating point to the right side of MPP at point b that is causing decrease in power and increase in voltage.

1.5 Description of conventional P&O algorithm problem The ordinary P&O calculation has poor following of MPP for climate change and great following for stack change at steady climate. This poor following of MPP is expected to the calculation can't recognize the reason for control change either is originating from climate variety or irritation venture because of load change. The MPPT moves from the genuine MPP because of the speedy change in the climate condition. Also, relentless state motions are because of exchange offs between step size and following pace of MPP.

2. MATLAB Simulation Fig 3: PV power and voltage due to weather variations 1.4 Conventional P&O algorithm and load change.

The PV load (RL) is connected across PV terminal via DC/DC boost converter as shown in Fig. 2a. The DC/DC boost converter matched the load impedance with source impedance of the PV system to satisfy maximum power transfer. In addition, P&O MPP trackers enable PV systems to operate at MPP. The relations between input and output variables of DC/DC boost converter.

Vout = d * Vpv Iout = Ipv/d

Fig 4:Simulink Model of P&O MPPT using different load

d = 1/(1-D)

3. SIMULATION RESULT

SL = Ipv/Vpv = d2 Iout / Vout= d2/RL RL= d2 Vpv/Ipv . where Vout and Iout are output voltage and current of boost converter, d is a linear control variable between Vout and VPV, D is the duty cycle, SL is the slope of load line and RL is the output load resistance of DC/DC boost converter. The operating point of the PV system is determined by the slope of load line as shown in Fig. 2b. This slope will change the operating point on I–V characteristic curve of the PV system by changing the linear variable ‘d’ or load resistance. The algorithm will take this variable as controlled variable for voltage change and the computes the duty cycle from (3) as follow D = (d − 1)/d

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Fig 5: Output of MPP using P&O algorithm for different load MPPT algorithms at initial solar radiation level of 0.4 KW/m2 which corresponds to power variance from 0 to 29.5W at the load 94 ohm and then it is increase to 39.5W at

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the load 150 ohm in Y -axis at time from 0 to 0.1 s for first load and 2 to 2.2 s for second load in X –axis

photovoltaic system’, Int. J. Eng. Innov. Technol. (IJEIT), 2013, 3, (2), pp. 333–337

4. CONCLUSION

[12] Solodovnik, E., Shengyi, L., Dougal, R.: ‘Power controller design for maximum power tracking in solar installations’, IEEE Trans. Power Electron., 2004, 19, pp.

1295–1304

The P&O algorithm using different load is simulated by using a 80 W PV module. and it is implemented using an embedded microcontroller Simulation results show the ability of P&O algorithm using different load to extract an accurate maximum power due to rapid changes of radiation with quick and high response.

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[13] Femia, N., Petrone, G., Spagnuolo, G., et al.: ‘Optimization of perturb and observe maximum power point tracking method’, IEEE Trans. Power Electron., 2005, 20, (4), pp. 963–973 [14] Liu, F., Duan, S., Liu, B., et al.: ‘A variable step size INC MPPT method for PV systems’, IEEE Trans. Ind. Electron., 2008, 55, (7), pp. 2622–2628 [15] Tey, K., Mekhilef, S.: ‘Modified incremental conductance algorithm for photovoltaic system under partial shading conditions and load variation’, IEEE Trans. Ind. Electron., 2014, 61, (10), pp. 5384–5392 [16] Rawat, R., Chandel, S.: ‘Hill climbing techniques for tracking maximum power point in solar photovoltaic systems-a review’, Int. J. Sustain. Dev. Green Econ. (IJSDGE), 2013, 2, pp. 90–95 [17] Esram, T., Chapman, P.: ‘Comparison of photovoltaic array maximum power point tracking techniques’, IEEE Trans. Energy Convers., 2007, 22, (2), pp. 439–449 [18] Liu, F., Kang, Y., Duan, S., et al.: ‘Comparison of P&O and hill climbing MPPT methods for grid-connected PV converter’. 3rd IEEE Conf. on Industrial Electronics and Applications, ICIEA 2008, 3–5 June 2008

[6] Faranda, R., Leva, S.: ‘Energy comparison of MPPT techniques for PV systems’, WSEAS Trans. Power Syst., 2008, 3, (6), p [7] Nasr Allah, A., Saied, M., Mustafa, M., et al.: ‘A survey of maximum PPT techniques of PV systems’. Browse Conf.

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678–687 [11] Swathy, A., Archana, R.: ‘Maximum power point tracking using modified incremental conductance for solar © 2018, IRJET

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