- Research
- Open access
- Published:
A vigorous simple most extreme force point tracker for pv battery charger
Environmental Systems Research volume 5, Article number: 25 (2016)
Abstract
Background
This paper proposes the dynamic way of utilizing the maximum power from solar for battery charger by means of maximum power point tracker with the new controlling parameter for improving the stability in power system network. The most efficient controller for PV related voltage converters is designed by the most efficient way of calculating the controlling parameter for MPPT of a PV battery charger which works in a full range condition with consistent changing environment. Other than this, another strong controller parameter is presented.
Results
Ideal MPPT calculations give PV current or voltage reference esteem as output controller parameter, in which frequent change in atmosphere may bring framework precariousness. Here, another variable is characterized to kill the issue and enhance the soundness of the framework. So as to contrast the introduced circuit and a traditional framework, Perturb and Observe (P&O) MPPT calculation which is surely understood in PV frameworks is actualized on the same framework.
Conclusions
Re-enactment results (Conventional P&O calculation and proposed structure) are displayed and thought about which show execution and adequacy of the proposed simple MPPT circuit.
Background
In view of renewable energy source the photovoltaic system is considered for power generation as it pertains to different points of interest like, cleanness, accessibility, less maintenance and no disorder. Hence it is known to be prominent amongst the most typical sorts of environmentally friendly power vitality possessions (Doris and Gelman 2011). In the use of rechargeable batteries, the Solar PV frameworks use PV battery charger (Fig. 1) is considered as the best decision among compact charging gadgets on account of straight forwardness and sunlight based vitality accessibility. The framework as a rule contains four primary parts, PV module as force source, Battery as energy stockpiling, DC/DC buck boost converter, streaming energy from source to battery, Control framework, for controlling the stream of energy to work proficiently.
As PV module contributes vast part of the framework cost (Enslin et al. 1997) ideal usage is attractive, subsequently discovering ideal working point which is the point, of maximum power separated from PVs is a customary objective in planning the control framework (Sundareswaran et al. 2014; Sera et al. 2013; Weidong et al. 2013). There are two significant methodologies for power extraction; sun following the maximum power point (MPP) (Ts et al. 2002). Solar amplifies the power, as illumination point influences the PV voltage–current (V–I) trademark significant to Kelly-cosine connection, yet it is not in the extent of this paper.
As showed in (Fig. 2) MPP is a novel point at any moment, that progressions with respect to irradiance conditions is presented to the panel, along these lines MPP tracker (MPPT), is an unavoidable part of the control framework.
A few calculations are produced for MPPT for entire system by considering the atmospheric conditions, mainly including power (Applebaum 1987; Braunstein and Zinger 1981), curve (Kislovski and Redl 1994; Wolf and Enslin 1993), slope Perturb & Observe (P&O) strategy. The impacts of supplying DC–DC converter from most maximum power source of PV array. Gow and Manning (2000) P &O MPPT procedure for accomplishing versatile following, no relentless state motions around the MPP and provides a nonspecific outline core (Abdelsalam et al. 2011) is integrated MPPT Converter as a part of the PV board. It is a practical and exceptionally proficient (Enslin et al. 1997) incremental conductance method PV Array, Power Conditioning, Control, DC Load, these four subsystem are tentatively conveys out (Nafeh et al. 1999).
MPT calculation in view of the way that the MPOP of a PV generator can be followed precisely by looking at the incremental and quick conductance of the PV cluster (Hussein et al. 1995), isolating rectangles calculation maximum power point following methodology for a photovoltaic framework utilizing the partitioning rectangles calculation, and it is equipped for hunting down worldwide greatest (Nguyen and Low 2010). A novel ES calculation uses (Petrone et al. 2011) the normal inverter swell was tried on a mimicked exhibit inverter framework (Brunton et al. 2010) extreme looking for (ES) control and swell connection control (RCC) is actualized. ES control, the examination exhibited there shows generally. RCC soundness and working properties are additionally tended to where the key distinction amongst RCC and prevalent ES control strategies is the bother source (Bazzi and Krein 2011) a food forward MP-point following plan is produced for the coupled-inductor interleaved-support converter-bolstered PV framework utilizing a fluffy controller (Veerachary et al. 2003). The new controller enhances the slope climbing look strategy by fuzzifying the tenets of such methods and wipes out their disadvantages (Alajmi et al. 2011). Comparative tests demonstrate that the proposed strategy can track the progression reaction rapidly and precisely; in the meantime show signs of improvement enhancement result. Zhou et al. (2011) neural system has a very straightforward structure and gives a profoundly precise recognizable proof of the ideal working point furthermore an exceedingly exact estimation of the most extreme force from the PV modules Hiyama et al. (1995) demonstrated that no less than 19 unmistakable techniques have been presented in the writing, with numerous minor departure from usage (Esram and Chapman 2007) assessments among the most normal MPPT systems, doing significant examinations concerning the measure of vitality removed from the photovoltaic board (PV) (tracking factor—TF) in connection to the accessible force, PV voltage swell, dynamic reaction and utilization of sensors (Berito et al. 2013).
These strategies need computerized handling to apply, either in a microcontroller (MCU) or FPGA which expand framework many-sided quality and aggregate cost particularly undesirable in little scale frameworks. Keeping in mind the end goal to evade these, few simple circuits are proposed.
In Chen and Smedley (2004), a simple MPPT in light of one-cycle control (OCC) is proposed, it works well the length of the board temperature variety is little, as this paper concentrates on little compact frameworks used to charge rechargeable batteries, this constraint is basic. A few frameworks utilizing differentiators (Alonso et al. 2006 and Lee et al. 2008) are not appealing, on account of clamor affectability. In Bodur and Ermis (1994), MPPT is determined by clearing PV voltage from 0Â V to open circuit voltage (VOC) occasionally. The framework is not powerful in view of requirement for periodical scope.
Another framework utilizing a pilot PV system is proposed in Tariq and Asghar (2005). The pilot PV board, with attributes like that of fundamental PV system, is kept under no-heap condition. A small amount of the pilot PV VOC, which relates to MPP voltage (VMPP), is utilized as the reference voltage. This strategy is not productive particularly for little frameworks while initial PV ought to be kept open circuit. The other issue is that the qualities of stacked and emptied boards contrast amid lifetime.
Liang et al. (2010) and Hsieh et al. (2010) proposed a simple circuit to actualize P&O calculation, however it experiences many-sided quality and requiring a circuit to capacity PV voltage and force in any progression.
The simple MPPT displayed in (Ji et al. 2010), works by direct control of exchanging order. This prompts variable exchanging recurrence which is not alluring in light of EMC issues and yield current and voltage administrative issues (Villalva et al. 2010).
In this paper a basic simple circuit for MPPT execution of a close planetary system is proposed which is well-working in all meteorological conditions and has an altered recurrence. Another controlling parameter is likewise displayed which enhances the security of the framework.
This paper is sorted out as takes after. The proposed simple circuit and working guideline are portrayed in segment II. Segment III makes a survey on issue of routine controlling variables and presents the new one with a talk on outline criteria. The aftereffects of reproductions for the proposed framework and customary computerized P&O MPPT calculation and the examination are introduced in segment IV. The exploratory set-up and the outcomes are delineated in area V.
Limitations of the existing work
In the existing work for any variation in solar irradiance or any abrupt changes in atmospheric condition the output power on the grid side fluctuates due to solar output power fluctuations. The concept in the existing work is MPPT controller P&O algorithm. The MPPT charge controller ensures that the loads receive maximum current to be used (by quickly charging the battery) and the maximum power point could be understood as an ideal voltage at which the maximum power is delivered to the loads, with minimum losses. The existing MPPT controller with P&O algorithm has the following disadvantages. (i) Real peak solar PV curve cant be identified if there is any shadow on solar clustered array (ii) P&O algorithm is slow to find the maximum peak if the solar voltage is far from MPP.
Tracker implementation
The schematic graph of the PV battery charger control framework with the proposed MPPT circuit is represented in Fig. 3. The solar output power and current are given as input for MPPT algorithm so as to dispense with clamor and high recurrence parts of sign. The algorithm proposed in Fig. 3. Separates the sign by utilizing the comparator analogy. The comparator analogy in MPPT, P&O algorithm has two qualities, (i) zero, when the power is diminishing, (ii) high when the power is expanding. The output of MPPT, comparator analogy develops the reference signal which is required to frame the switching states that is required for triggering the converter state.
The reference signal developed at the output of the algorithm is unstable due to frequent change in atmospheric condition. Dur to this variation in the reference signal, the output power fluctuates very badly, causing instability in power system framework. To avoid the cause of instability problem, a new controlling factor ‘S’ is incorporated in the proposed scheme. The controlling factor has constant K0, K1, K2 constants for controlling the reference controlling parameter S for abrupt input change.
Deriving energy conversion
Approximating charger loss (Ploss) to zero, and assuming battery voltage (VBat.) constant (valued while voltage changes dynamically very slow) and considering power balance for charger input and output power,
where, Iout is the charger output current. demonstrates that I out is a well representative for P in , which can be used as input of MPPT algorithm. Therefore multiplying V PV and I PV is omitted from circuit in.
Novel supervisory variable
Predictably controller affords Vor I ref as the output and uses PV sway as th ref e contribution parameter for implementation of MPPT algorithm. In the proposed systems, rapid weather change, or a to a degree of sudden shadow on PV module which cause a sudden change in V–I characteristic of PV module may result in system instability while following the set value, and thus the PI controller saturates and hence any further step change in the reference value of Vref/Iref causes the output to be ineffective, therefore PV output power remains constant and the defined MPPT algorithm fails to find MPP, when V ref /I ref remnants superior than new short circuit PV current (I sc ) or newfangled open circuit PV voltage (V oc ). Alternatively unsteadiness occurs when V ref /I ref falls out of range of variations V PV /I PV . This instability is a major problem in PV modules with piercing V–I physical characteristics.
To avoid the instability problem the new controlling variable S is defined as below.
where I PV , and V PV are instantaneous PV current and voltage respectively, and k 0 , k 1 , k 2 are constants. Selecting appropriate value of k 0 , k 1 , k 2 cause S ref to endure in variety of operation either for abrupt input change, and hence it improve the stability of the system. With reference to the V–I characteristic, of PV module for different irradiance factor the voltage and current varies in opposite direction, and hence least possible and maximum value of S are calculated as
Figure 4 shows the solar V–S characteristics for different value of irradiance. Dash lines denote for MPP.
In order to guarantee MPPT working for different conditions, it is necessary to calculate the controlling factor S ref . This relies between the minimum and maximum instantaneous values of S according to the worst condition.
The controlling reference value is incorporated in the proposed algorithm, by considering the entire atmospheric circumstances. With reference to Eq. (3). the maximum worst condition is determined when Voc is minimum. The extreme worst condition (K0 − K2Voc) is obtained with minimum insolation and maximum PV temperature. (K0 + K1Isc) is the minimum condition obtained with Isc = 0. Based on the above Implementation the Eq. (4) is obtained.
Figure 5 depicts the reference controlling factor for increase in K2 and decrease in the factor K1 with decreasing illumination. When the illumination decreases, the output power is decreased in which the Voc is minimum with Isc maintained constant. Therefore Sref which is the main factor in controlling the instability is primarily zero and then increases to Sref (MPP). Therefore for fleeting stability the assortment of difference for S should satisfies the following conditions.
S MPP should be larger than zero to be able to be shadow by PI controller which means the extreme on S–P curve should be greater than zero. This criterion is used to determine k 1 .
A remarkable firm positive site of utilizing the new controlling variable S cause the system to maintain its stability in abrupt atmospheric change. The circuit contains only a voltage subtractor, promotion two voltage dividers. Using node equation for circuit in is derived.
From (3) the constants k 1 , k 2 , and k 3 are obtained.
Circuit design and stability analysis
In order to analyze the stability of the system, small signal model of the charger using a buck–boost converter as dc/dc converter is derived.
Small signal model while using S as control parameter
The small signal model of the buck–boost converter using voltage and current control are designed by utilizing the model Voltage and current to duty cycle transfer functions of the entire system and are given by (11) and (12).
where, Req is the input resistance of the converter.
The small signal variables used in (11) and (12), are defined in the following.
Using (2), (11) and (12) G sd (s) can be calculated,
Simulation and experimental results
Dualistic virtual reality is performed using conventional digital Perturb &Observe algorithms. The V–I curve of PV panel is shown in Figs. 6, 7, 8. A buck converter model is used as charger with 100 kHz switching occurrence and the nominal voltage of the battery is anticipated to be 12 V. The operating Clock frequency for implemented MPPT algorithm and step frequency for P&O algorithm are same as 100 Hz. The platform for computing and making decision for any change in the duty cycle is done at specific time intervals in case of conventional P&O algorithm. The step frequency represent the time interval for deciding the time interval. For example if change in duty cycle is done every 1 ms. then the step frequency is 100 Hz.
S is used as controlling variable to implement both the algorithms. The scenario of simulating illumination is described in the following.
90% illumination at first 0.1 s time interval then gradually increase to 100% illumination for 0.1 s time interval, and remaining constant till t = 0.3 s. Finally sudden change to 80% illumination at t = 0.3 s.
A prototype model is designed (Fig. 9) to accept the capacity of the solar framework in which the qualities are described. Three solar panel are paralleled so as to support the power output from solar and utilized as the power source in converter. The power output supported by the entire system (solar PV converter) is around 1.5 Kw for the designed prototype model (Fig. 10).
PV yield voltage for ordinary operation of the charger is appeared in Fig. 11 the working point is the MPP (≈17 V). So as to demonstrate the issue of utilizing current (or voltage) as charger control parameter, two tests has been performed while IPV was the charger control parameter (first test), and quick environmental change was mimicked by in part shading the board range. The outcome (PV yield voltage) appeared. The same condition is considered for the charger with S and without S as charger control parameter. Figures 12 and 13 shows the current variation for change in irradiance (new control variable not considered) with respect to time. On observing the output (Fig. 13) it is noticed switching time of the converter varies as the insolation varies at different instant, which in turn the current fluctuates causing instability in the entire network. This is eliminated in Fig. 10 by implementing MPPT calculation with new control variable ‘S’ to maintain the stability of the entire system and also the proposed framework in the same condition has a well execution to track the MPP.
Conclusion
In the proposed manuscript dynamic control scheme is presented to analyze the performance of a three-phase grid-connected PV system and to enhance the dynamic stability limit with the change in atmospheric conditions by utilizing the new control factor. The projected controller setup cancels all possible nonlinearities by converting the entire PV system into two decoupled linear subsystems with stable internal dynamics by incorporating the control variable ‘S’. The DC link voltage and current from solar PV system controlled by MPPT P&O algorithm with controlling script is injected into grid are controlled to ensure the operation of the PV system at unity power factor and in Stable condition. From the simulation results, it is clear that the controller performs better under varying atmospheric conditions. Future work will deal with the expansion of the projected method by considering the mismatches within the solar PV model and to implement it on a large interrelated structure.
References
Abdelsalam A, Massoud A, Ahmed S, Enjeti P (2011) High-performance adaptive perturb and observe MPPT technique for photovoltaic-based microgrids. IEEE Trans Power Electron 26:1010–1021
Alajmi B, Ahmed K, Finney S, Williams B (2011) Fuzzy-logic-control approach of a modified hill-climbing method for maximum power point in microgrid standalone photovoltaic system. IEEE Trans Power Electron 26:1022–1030
Alonso R, Queinnec I, Pastor A, Lagrange D, Salamero L (2006) MPPT of photovoltaic systems using extremum-seeking control. IEEE Trans Aerosp Electron Syst 42:249–258
Applebaum J (1987) The quality of load matching in a direct-coupling photovoltaic system. IEEE Trans Energy Convers 2:534–541
Bazzi A, Krein P (2011) Concerning maximum power point tracking for photovoltaic optimization using ripple-based extremum seeking control. IEEE Trans Power Electron 26:1611–1612
Berito M, Galotto L, Sampaio L, Azevedo M, Canesin C (2013) Evaluation of the main MPPT techniques for photovoltaic applications. IEEE Trans Ind Electron 60:1156–1167
Bodur M, Ermis M. Maximum power point tracking for low power photovoltaic solar panels. In: IEEE 1994 mediterranean electrotechnical conference; 12–14 April 1994; Antalya, Turkey. pp. 758–761
Braunstein A, Zinger Z (1981) On the dynamic optimal coupling of a solar cell array to a load and storage batteries. IEEE Trans Power Apparat Syst 100:1183–1188
Brunton S, Rowley C, Kulkarni S, Clarkson C (2010) Maximum power point tracking for photovoltaic optimization using ripple-based extremum seeking control. IEEE Trans Power Electron 25:2531–2540
Chen Y, Smedley K (2004) A cost-effective single-stage inverter with maximum power point tracking. IEEE Trans Power Electron 19:1289–1294
Doris E, Gelman R. The Role of Policy in Clean Energy Market Transformation, US Department of Energy, Technical Report, 2011; NREL/TP-6A20-49193
Enslin J, Wolf M, Snyman D, Swiegers W (1997) Integrated photovoltaic maximum power point tracking converter. IEEE Trans Ind Electron 44:769–773
Esram T, Chapman P (2007) Comparison of photovoltaic array maximum power point tracking techniques. IEEE Trans Energy Convers 22:439–449
Gow J, Manning C (2000) Controller arrangement for boost converter systems sourced from solar photovoltaic arrays or other maximum power sources. IEEE Electric Power Appl 147:15–20
Hiyama T, Kuouzuma S, Imakubo T (1995) Identification of optimal operating point of PV modules using neural network for real time maximum power tracking control. IEEE Trans Energy Convers 10:360–367
Hsieh C, Yang C, Feng F, Chen K. A photovoltaic system with an analog maximum power point tracking technique for 97.3% high effectiveness. In: IEEE 2010 European solid state circuits conference; 14–16 September 2010; Sevilla, Spain. pp. 230–23
Hussein K, Muta I, Hoshino T, Osakada M (1995) Maximum photovoltaic power tracking: an algorithm for rapidly changing atmosphere conditions. IEEE Gener Transm Distrib 142:59–64
Ji S, Jang D, Han S, Roh C, Hong S. Analog control algorithm for maximum power tracker employed in photovoltaic applications. In: IEEE 2010 international power electronics conference; 27–29 Oct. 2010; Singapore. pp. 99-103
Kislovski A, Redl R. Maximum-power-tracking using positive feedback. In: IEEE 1994 power electronics specialists conference; 20–25 June 1994; Taipei, Taiwan. pp. 1065–1068
Lee K, Niu J, Lin G. A simplified analog control circuit of a maximum power point tracker. In: IEEE 2008 photovoltaic specialists conference; 11–16 May 2008; San Diego, California, USA. pp. 1–3
Liang Z, Guo R, Huang A. A new cost-effective analog maximum power point tracker for PV systems. In: IEEE 2010 energy conversion congress and exposition; 12–16 September 2010; Atlanta, GA, USA. pp. 624–631
Nafeh A, Fahmy F, Mahgoub O, El-Zahab E (1999) Microprocessor control system for maximum power operation of PV arrays. Int J Numer Model 12:187–195
Nguyen T, Low K (2010) A global maximum power point tracking scheme employing direct search algorithm for photovoltaic systems. IEEE Trans Ind Electron 57:3456–3467
Petrone G, Spagnuolo G, Vitelli M (2011) A multivariable perturb-and-observe maximum power point tracking technique applied to a single-stage photovoltaic inverter. IEEE Trans Ind Electron 58:76–84
Sera D, Mathe L, Kerekes T, Spataru S, Teodorescu R (2013) On the perturb-and-observe and incremental conductance MPPT methods for PV systems. IEEE J Photovolt 3:1070–1078
Sundareswaran K, Peddapati S, Palani S (2014) MPPT of PV systems under partial shaded conditions through a colony of flashing fireflies. IEEE Trans Energy Convers 29:463–472
Tariq A, Asghar M. Development of an Analog Maximum Power Point Tracker for Photovoltaic Panel. In: IEEE 2005 international power electronics and drives systems; 28 November 2005–1 December 2005; Malaysia. pp. 251–255
Ts K, Ho M, Chung H, Hui S (2002) A novel maximum power point tracker for PV panels using switching frequency modulation. IEEE Trans Power Electron 17:980–989
Veerachary M, Senjyu T, Uezato K (2003) Neural-network-based maximum-power-point tracking of coupled-inductor interleaved-boost-converter-supplied PV system using fuzzy controller. IEEE Trans Ind Electron 50:749–758
Villalva MG, Siqueira TG, Ruppert E (2010) Voltage regulation of photovoltaic arrays: small-signal analysis and control design. IET Power Electron 3:869–880
Weidong X, Zeineldim H, Zhang P (2013) Statistic and parallel testing procedure for evaluating maximum power point tracking algorithms of photovoltaic power systems. IEEE J Photovoltaics 3:1062–1069
Wolf S, Enslin J. Economical PV maximum power point tracking regulator with simplistic controller. In: IEEE 1993 power electronics specialists conference; 20–24 June 1993; Seattle, Washington. USA. pp. 581–587
Zhou L, Chen Y, Guo K, Jia F (2011) New approach for MPPT control of photovoltaic system with mutative-scale dual-carrier chaotic search. IEEE Trans Power Electron 26:1038–1048
Authors’ contributions
TY implemented the MPPT tracer. RK formed the experimental scheme. Both authors read and approved the final manuscript.
Acknowledgements
We acknowledge Sri Sai Ram College of Engineering Research and Development Section.
Competing interests
The authors declare that they have no competing interests.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
About this article
Cite this article
Teekaraman, Y., Ramya, K. A vigorous simple most extreme force point tracker for pv battery charger. Environ Syst Res 5, 25 (2016). https://doi.org/10.1186/s40068-016-0075-0
Received:
Accepted:
Published:
DOI: https://doi.org/10.1186/s40068-016-0075-0