ISSN Vol.07,Issue.01, January-2015, Pages:

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1 ISSN Vol.07,Issue.01, January-2015, Pages: A Novel Improved Variable Step Size of Digital MPPT Controller For A Single Sensor in Photo Voltaic System K.MURALIDHAR REDDY 1, K.MEENENDRANATH REDDY 2, G.VENKATA SURESH BABU 3 1 PG Scholar, Dept of EEE (EPS), SITS, Kadapa, Andhrapradesh, India. 2 Assistant Professor, Dept of EEE, SITS, Kadapa, Andhrapradesh, India. 3 Associate Professor & HOD, Dept of EEE, SITS, Kadapa, Andhrapradesh, India. Abstract: Recent researches focus mainly on the solar energy that almost all the part of this world receives abundantly with variation in its potential. Many studies have made it possible to convert these energies in to more efficient electrical energy. The interference of power electronics in almost of all the fields have made more sophistication in industries with loads that require the most efficient and accurate amount of supply. In this paper a new Digital Control Technique Based MPPT is proposed to Track and Maximum Power. MPPT is a method to obtain the maximum power from a module in any weather condition. As solar energy is varying in nature, the MPPT is the main focus of energy conservation. By the V - I characteristics of solar energy, there is only one point in its curve where the maximum power is achieved. The Digital Controllers used in this paper are an adaptive step- size and adaptive-perturbation-frequency algorithm, by utilizing a variable step-size algorithm, the speed, accuracy, and efficiency of the PV system MPPT are improved when compared to the fixed step-size load-current-based algorithm. Tracking that particular point with accuracy has developed many algorithms in this field. Furthermore, the proposed adaptive algorithm utilizes a novel variable perturbation frequency scheme which further improves the controller speed. Matlab Simulink Software is used to solve the Project and both the Controller are Compared. Keywords: Adaptive-Perturbation-Frequency Perturb And Observe (P&O) Algorithm, Adaptive Step Size, Dc Dc Converters, Maximum Power Point Tracking (MPPT), Photovoltaic (PV), Solar Energy. I. INTRODUCTION Photovoltaic (PV) panels are used to convert solar energy into electric power. The solar PV panel output characteristics are dependent on operating conditions such as surrounding temperature and irradiance level. Maximum power points (MPPs) exist on the PV panel characteristic curves at which point the output power from the solar panel is maximum. Maximum power point tracking (MPPT) algorithms and techniques such as perturb and observe (P&O) algorithm, incremental conductance (InCond) algorithm, ripple correlation control (RCC) algorithm, fractional voltage/current MPPT method and neural-network (NN)-based MPPT control has developed to extract the maximum power from the PV panel. The P&O method, which identifies the MPP using the slope of the P V characteristics curve, it is widely used due to its minimalism and ease of implementation. A main disadvantage of the P&O algorithm is that the PV panel operation points oscillate through the MPP which occurs energy loss. InCond algorithms overcome the drawbacks of P&O algorithms by removing the oscillations around the MPPs. However, the InCond MPPT algorithm needs real time calculation of the slope of the PV panel power curve, it is more complicated to be implemented in controller compared to the P&O algorithm. The RCC MPPT algorithm uses the derivatives of the power converter s voltage and current ripples to determine the position of the PV panel operating point. One of its drawbacks in this method is that if the power converter s switching frequency varies, it has to redesign the high pass filter circuit which is used to attain time derivatives of PV panel voltage and current. The fractional voltage/current methods sets the optimal voltage/current reference as a fraction of the PV solar panel s open-circuit voltage or short-circuit current, and therefore, it does not track the real MPP. Even though this method has an acceptable tracking performance under steady state conditions, it may fail to converge to new MPP under transient conditions. The NNbased MPPT controller improves the tracking efficiency of the system by utilizing a multilayer control structure; however, this method involves computational iterations and increases the calculation load of the controller. All the MPPT methods discussed above require the sensing of PV panel voltage and current they need multiplication function to attain the PV panel power values which increase the size and the power consumption of the controller. The load-current-based MPPT method with the fixed step size (FXS) perturbation P&O algorithm has been proposed to realize MPPT functionality by sensing only the load current. Which limts the need for a multiplier that is required to attain the power value in the conventional power-based MPPT methods. Adaptive-perturbation-step IJATIR. All rights reserved.

2 K.MURALIDHAR REDDY, K.MEENENDRANATH REDDY, G.VENKATA SURESH BABU size algorithms are studied to provide fast dynamic convergence speed and high steady-state tracking efficiency. Different from, in which a fixed scaling factor and a fixed MPPT frequency algorithm is used, utilize an adaptive scaling factor and the fixed frequency MPPT algorithm to optimize the controller speed during transient. However, the algorithm becomes more complicated: the algorithm requires the information of the location of the PV panel operation point and the controller is switching between adaptive duty cycle control and fixed duty cycle control. Generally, in a PV system with MPPT control, large perturbation requires longer settling time after perturbation is triggered and small perturbations require shorter settling time. In previous works, which either implement the FXS MPPT algorithm or an adaptive-step-size MPPT algorithm, the period of perturbation is fixed. MPP is valid in the system with a resistive load. The relationship between input power and output current with power stage duty cycle is illustrated in Fig. 2. In the conventional load-current-based P&O algorithm, the duty cycle perturbation step size ΔD is a fixed value. During steady-state MPPT operation, small ΔD reduces the power losses caused by the oscillations around the MPP. During transient MPPT operation, larger ΔD is preferred for faster convergence to the new MPP. This fixed perturbation time period is selected to ensure that the system has sufficient time to settle down when the largest perturbation is triggered. Though, this results in longer MPPT controller response time when the operating point is near to MPP. This issue is addressed to the proposed LCASF MPPT algorithm by using an adaptive-perturbation frequency scheme with higher perturbation frequency when the perturbation is smaller, and vice versa. Digital controllers are increasingly being used in a renewable energy system control because of their ability to perform advanced control algorithms among other advantages such as easy to be reconfigured and upgraded. Therefore, the LCASF MPPT controller is realized by a digital controller. This digital controller is implemented in this paper by using a microcontroller (MCU), but can be also implemented by field programmable gate array. Fig.2. Relationship between input power and output current with power converter duty cycle. Variable step-size algorithms are generally developed in order to attain swapping between the speed and the accuracy of the tracking. The proposed LCASF MPPT digital controller algorithm flowchart is shown in Fig. 3. The control tactic of this algorithm is to continuously adjust the duty cycle perturbation values and adjust the perturbation frequency while observing the load current Io. II. LCASF MPPT ALGORITHM Fig. 1 shows a PV solar system block diagram with the proposed LCASF MPPT controller. The power conversion process from the PV panel to the load (battery load or resistive load) interfaced through a dc dc converter with efficiency equal to η. The dc dc converter regulates the voltage and current of the solar panel and thus it regulates the output power. The MPPT controller keeps adjusting the duty cycle of the power converter to reach the MPP of the solar panel. Fig.1. Block diagram of a PV solar power system with load current MPPT control. In the conventional power-based P&O MPPT algorithm, the derivative of power to voltage dp/dv of a PV panel is used as a tracking parameter. The tracking of zero slope at Fig.3 LCASF MPPT algorithm flowchart.

3 A Novel Improved Variable Step Size of Digital MPPT Controller For A Single Sensor in Photo Voltaic System The two types of schemes are mainly present in this panel ratings and power converter parameters are identical algorithm they are, adaptive determination of the with the parameters in the system response time analysis in perturbation values ΔD and the adaptive determination of the last section and results as shown in Figs.4 t0 12. perturbation periods T. After ΔD and T values are attained, the duty cycle of the power stage is perturbed by ΔD and after waiting T period of time, the MPPT controller starts the next perturbation. III. ADDITIONAL COMPARISONS WITH OTHER MPPT ALGORITHMS The following is a summary between the proposed LCASF MPPT controller algorithm and the other MPPT algorithms discussed in Section I: General comparison between the proposed LCASF MPPT control and the other MPPT algorithms in terms of MPPT tracking speed: Unlike the LCASF MPPT controller, all the other existing MPPT controllers that are discussed in the literature use a fixed MPPT perturbation period, even when they utilize variable duty cycle or references voltage. perturbation step size, which results in extensively longer MPP tracking time because this fixed perturbation period is set long enough for the case when the duty cycle perturbation step size is largest. MPPT control algorithm and the conventional P&O control algorithm. The conservation of P&O MPPT has necessary as sensing the both PV panel current and voltage. MPPT control algorithm and the conventional InCond MPPT algorithm. Which has both conventional InCond MPPT algorithm and tracking speed of LCASF MPPT controller utilizes the proposed variable MPPT perturbation. Even though same can be seen. MPPT control algorithm and the conventional RCC MPPT algorithm. The RCC MPPT is same as P&O MPPT algorithm except in execution in frequency switching. MPPT control algorithm and the conventional fractional voltage and fractional current method. This methods need only one sensor i.e either voltage or current they provide approximation to the MPP, which tracks low MPP efficiency. MPPT control algorithm and the NN-based MPPT algorithm. The LCASF MPPT control algorithm MPP tracking speed is faster than NN-based MPPT algorithm because NN-based algorithm use fixed algorithm update period i,e 100Hz. V. SIMULATION RESULTS The power converter topology used is a synchronous dc dc buck converter, operating in continuous conduction mode with 100-kHz switching frequency and PWM control. PV Fig.4.,, PV panel voltage, current, and load current waveforms under input transient response of controller with battery load for LCASF algorithm.

4 K.MURALIDHAR REDDY, K.MEENENDRANATH REDDY, G.VENKATA SURESH BABU Fig.5,,. PV panel voltage, current, and load current waveforms under input transient response of controller with battery load for LCA algorithm. Fig.6,,. PV panel voltage, current, and load current waveforms under input transient response of controller with battery load for 1% FXS algorithm.

5 A Novel Improved Variable Step Size of Digital MPPT Controller For A Single Sensor in Photo Voltaic System Fig.7.,,. PV panel voltage, current, and load current waveforms under input transient response of controller with battery load for 5% FXS algorithm. Fig.8,,. PV panel voltage, PV panel current, and load current waveforms under input transient response of controller with resistive load for LCASF algorithm.

6 K.MURALIDHAR REDDY, K.MEENENDRANATH REDDY, G.VENKATA SURESH BABU Fig.9.,, PV panel voltage, PV panel current, and load current waveforms under input transient response of controller with resistive load for LCA algorithm. Fig.10,, PV panel voltage, PV panel current, and load current waveforms under input transient response of controller with resistive load for 1% FXS algorithm.

7 A Novel Improved Variable Step Size of Digital MPPT Controller For A Single Sensor in Photo Voltaic System Fig.11.,, PV panel voltage, PV panel current, and load current waveforms under input transient response of controller with resistive load for 5% FXS algorithm. (d) Fig.12.,,,(d) PV panel voltage, current, load current, and voltage waveforms under load voltage transient with LCASF controller.

8 K.MURALIDHAR REDDY, K.MEENENDRANATH REDDY, G.VENKATA SURESH BABU V. CONCLUSION This paper presented a load-current-based variable-stepsize and variable-perturbation-frequency MPPT digital controller. In addition to utilizing a function to adapt the duty cycle perturbation, the proposed MPPT controller adapts its perturbation frequency as a function of the variable duty cycle perturbation value. As the results presented in this paper showed, the duty cycle adaptivestep-size scheme used in the proposed MPPT controller yields a good tradeoff between the convergence speed and tracking efficiency compared to the FXS algorithm. Furthermore, the novel adaptive perturbation frequency scheme used in the proposed controller results in faster convergence speed compared to existing adaptive-step-size algorithms. The proposed adaptive perturbation frequency scheme could also be used with other MPPT algorithms. VI. REFERENCES [1] H. S.-H. Chung, K. K. Tse, S. Y. R. Hui, C. M. Mok, and M. T. Ho, A novel maximum power point tracking technique for solar panels using a SEPIC or Cuk converter, IEEE Trans. Power Electron., vol. 18, no. 3, pp , May [2] A. I. Bratcu, I. Munteanu, S. Bacha, D. Picault, and B. Raison, Cascaded DC DC converter photovoltaic systems: Power optimization issues, IEEE Trans. Ind. Electron., vol. 58, no. 2, pp , Feb [3] Y. H. Ji, D. Y. Jung, J. G. Kim, J. H. Kim,T. W. Lee, and C. Y.Won, A real maximum power point tracking method for mismatching compensation in PV array under partially shaded conditions, IEEE Trans. Power Electron., vol. 26, no. 4, pp , Apr [4] S. Jain and V. Agarwal, A single-stage grid connected inverter topology for solar PV systems with maximum power point tracking, IEEE Trans. Power Electron., vol. 22, no. 5, pp , Sep [5] L. Zhang, K. Sun, Y. Xing, L. Feng, and H. J. Ge, A modular gridconnected photovoltaic generation system based on DC bus, IEEE Trans. Power Electron., vol. 26, no. 2, pp , Feb [6] Z. Liang, R. Guo, J. Li, and A. Q. Huang, A highefficiency PV moduleintegrated DC/DC converter for PV energy harvest in FREEDM systems, IEEE Trans. Power Electron., vol. 26, no. 3, pp , Mar [7] L. Zhang, W. G. Hurley, and W. H. W olfle, A new approach to achieve maximum power point tracking for PV system with a variable inductor, IEEE Trans. Power Electron., vol. 26, no. 4, pp , Apr [8] L. Zhou, Y. Chen, K. Guo, and F. Jia, New approach for MPPT control of photovoltaic system with mutativescale dual-carrier chaotic search, IEEE Trans. Power Electron., vol. 26, no. 4, pp , Apr [9] G. Petrone, G. Spagnuolo, and M. Vitelli, A multivariable perturb-andobserve maximum power point tracking technique applied to a singlestage photovoltaic inverter, IEEE Trans. Ind. Electron., vol. 58, no. 1, pp , Jan [10] N. Femia, G. Petrone, G. Spagnuolo, and M. Vitelli, Optimization of perturb and observe maximum power point tracking method, IEEE Trans. Power Electron., vol. 20, no. 4, pp , Jul Author s Profile: K. Muralidhar Reddy has received the B.Tech (Electrical And Electronics Engineering) degree from Madina engineering college, Kadapa in 2010 and persuing M.Tech (Electrical Power Systems) in Srinivasa Institute of Technology and Science, Kadapa, AP, India. K. Meenendranath reddy has 4 years of experience in teaching in Graduate and Post Graduate level and he Presently working as Assistant Professor in department of EEE in SITS, Kadapa, AP, India. G.Venkata Suresh Babu has 12 years of experience in teaching in Graduate and Post Graduate level and he Presently working as Associate Professor and HOD of EEE department in SITS, Kadapa, AP, India.