Resincap Journal of Science and Engineering
Volume 4, Issue 6, June 2020 ISSN: 2456-9976
1056
The Maximum Power Point Tracking for Stand-Alone PV System Using Current Control Based Approach
Mr.Khushal A Warake PG Student Electrical Engg.Dept.
SSGBCOET Bhusawal, [email protected]
Prof. Girish K Mahajan Associate Professor
Electrical Engg.Dept.
SSGBCOET Bhusawal, [email protected]
Prof. Rajesh C Patil Associate Professor Electrical Engg.Dept.
SSGBCOET Bhusawal, [email protected]
ABSTRACT
The main aim of this paper is the analysis of the performance of a photovoltaic power plant controlled by a dedicated algorithm. A photovoltaic (PV)system directly converts sunlight into electricity. The basic device of a PV system is the PV cell. Cells may be grouped to form panels or arrays.
Photovoltaic (pv) power generation is evolving as one of the most prominent renewable energy sources because of its merits such as eco-friendly nature, less maintenance, and no noise. The fundamental component of PV system is a PV cell.
Series connection of PV cells forms modules, and series and parallel connection of modules forms arrays. In order to study electronic converters for PV systems, one first need to know how to model the PV device that is attached to the converter.
The point at which available maximum power can be extracted from the PV module is called maximum power point (MPP). So far, a large number of maximum power point tracking (MPPT) techniques have been developed to increase the efficiency of the PV system.
Keywords
– Simultion without MPPT, With Incremental conductance MPPT, With P&O MPPT, Adaptive Voltage-Sensor-Based MPPT1.
INTRODUCTION
Photovoltaic (PV) power generation is evolving as one of the most prominent renewable energy sources because of its merits such as eco-friendly nature, less maintenance, and no noise. The fundamental component of PV system is a PV cell.
Series connection of PV cells forms modules, and series and parallel connection of modules forms arrays. The characteristics of a PV module will vary with solar insolation and atmospheric temperature. The efficiency of the PV system mainly depends on the operating point on the characteristic curve of the PV module. The point at which available maximum power can be extracted from the PV module is called maximum power point (MPP). So far, a large number of maximum power point tracking (MPPT) techniques have been developed to increase the efficiency of the PV system.
This chapter introduces photovoltaic (PV) power generation systems. The characteristics of the PV panels and modelling of the PV cell are discussed.
1.1 Solar Cell
Solar cells are the basic components of photovoltaic panels.
Most are made from silicon even though other materials are also used. Solar cells take advantage of the photoelectric effect: the ability of some semiconductors to convert electromagnetic radiation directly into electrical current. The charged particles generated by the incident radiation are separated conveniently to create an electrical current by an appropriate design of the structure of the solar cell.A solar cell is basically a p-n junction which is made from two
different layers of silicon doped with a small quantity of impurity atoms: in the case of the n-layer, atoms with one more valence electron, called donors, and in the case of the p- layer, with one less valence electron, known as acceptors.
When the two layers are joined together, near the interface the free electrons of the n-layer are diffused in the p-side, leaving behind an area positively charged by the donors. Similarly, the free holes in the p-layer are diffused in the n-side, leaving behind a region negatively charged by the acceptors. This creates an electrical field between the two sides that is a potential barrier to further flow. The equilibrium is reached in the junction when the electrons and holes cannot surpass that potential barrier and consequently they cannot move. This electric field pulls the electrons and holes in opposite directions so the current can flow in one way only: Electrons can move from the p-side to the n-side and the holes in the opposite direction. A diagram of the p-n junction showing the effect of the mentioned electric field is illustrated in Figure 1.
Fig.No.1 Solar cell
1.2 Equivalent Circuit of A Solar Cell
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Fig.No.2. Equivalent circuit of a solar cell.
The solar cell can be represented by the electrical model shown in Figure 2. Its current voltage
Characteristic is expressed by the following equation (1):
( ( ) ) (1)
where I and V are the solar cell output current and voltage respectively, I0 is the dark saturation current, q is the charge of an electron, A is the diode quality (ideality) factor, k is the Boltzmann constant, T is the absolute temperature and Rs and Rsh are the series and shunt resistances of the solar cell. Rs is the resistance offered by the contacts and the bulk semiconductor material of the solar cell. Rsh is related to the non-ideal nature of the p–n junction and the presence of impurities near the edges of the cell that provide a short- circuit path around the junction [1][2]. In an ideal case Rs would be zero and Rsh infinite. However, this ideal scenario is not possible and manufacturers try to minimize the effect of both resistances to improve their products. A PV panel is composed of many solar cells, which are connected in series and parallel so the output current and voltage of the PV panel are high enough to the requirements of the grid or equipment.
2. LITERATURE REVIEW
2.1 PV Modules-Maximum Power Point
PV modules have inverse diode characteristics which is non- linear in nature. Power v/s voltage characteristics can be obtained from non-linear current voltage characteristics. A set of curves can be obtained for different irradiation and temperatures, where maximum of each curve is called maximum power point (MPP) for that corresponding condition as shown in Figure 3
Fig.No.3. Maximum Power Point
MPP is tracked by the power conditioning unit (PCU) which couples the PV array with AC load or the grid. The operating point of the PV array is the point of intersection of the I-V characteristic curve and the load line. The closed-loop control PCU trackers, aim to drive the operating point closer to the maximum power point of the I-V curve at any given condition. Many MPPT algorithms are suggested in literature, each vary in tracking efficiency, convergence speed, complexity, number of sensors required and type of
implementation hardware. Few of the popular methods are discussed in the following sections.
2.2 Maximum Power Point Tracking
Fig.No.4.Maximum Power Point Tracking MPPT algorithms are necessary in PV applications because the MPP of a solar panel varies with the irradiation and temperature, so the use of MPPT algorithms is required in order to obtain the maximum power from a solar array. The most important component of the solar photovoltaic modules for extracting the peak power are the maximum power point trackers (MPPT). The operating point is rarely at the maximum power point when the PV module is directly connected to the load for given temperature and irradiance value. So always a dc-dc converter is bridged between the load and the PV module [2]. The MPPT algorithm itself adjusts the duty cycle for varying irradiance values so that the power transferred to the load from the module is highly efficient. Over the past decades many methods to find the MPP have been developed and published. These techniques differ in many aspects such as required sensors, complexity, cost, range of effectiveness, convergence speed, correct tracking when irradiation and/or temperature change, hardware needed for the implementation or popularity, among others.
MPPT algorithms such as fractional open-circuit voltage, fractional short-circuit current, hill climbing, perturb and observe (P&O), incremental conductance (IncCond), incremental resistance developed to extract the maximum power from the PV arrays.Four MPPT methods are studied in this paper; the P&O method, the Incremental Conductance method, the fuzzy logic method and only current measurement method.
Among these techniques, the P&O and the InCond algorithms are the most common. These techniques have the advantage of an easy implementation but they also have drawbacks, as will be shown later. Other techniques based on different principles are fuzzy logic control, neural network, fractional open circuit voltage or short circuit current, current sweep, etc. Most of these methods yield a local maximum and some, like the fractional open circuit voltage or short circuit current, give an approximated MPP, not the exact one. In normal conditions the V-P curve has only one maximum, so it is not a problem.
However, if the PV array is partially shaded, there are multiple maxima in these curves. In order to relieve this
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problem, some algorithms have been implemented as in In the next section the most popular MPPT techniques are discussed.
The MPPT is a charge controller that compensates for the changing Voltage Current characteristic of a solar cell. The MPPT fools the panels into outputting a different voltage and current allowing more power to go into the battery or batteries by making the solar cell think the load is changing when you really are unable to change the load. The MPPT monitors the output voltage and current from the solar panel and determines the operating point that will deliver that maximum amount of power available to the batteries. If our version of the MPPT can accurately track the always-changing operating point where the power is at its maximum, then the efficiency of the solar cell will be increased.
2.2.1 Incremental Conductance Technique
A good MPPT algorithm balances between the tracking speed and steady-state performance. In accordance with these requirements, the INC algorithm can be used even if it can fail in some cases and in this study, it will be modified in order to improve its performance. INC algorithm is founded in the fact that slope of characteristic is zero at the MPP. The point at which available maximum power can be extracted from the PV module is called maximum power point (MPP). So far, a large number of maximum power point tracking (MPPT) techniques have been developed to increase the efficiency of the PV system
.
Fig.No.5 Flowchart of Maximum Power Point Tracking The step size for the INC MPPT method is generally fixed.
The power drawn from the PV array with a lager step size contributes to faster dynamics but excessive steady state oscillations, resulting in a comparatively low efficiency. This situation is reversed while the MPPT is running with a smaller step size. Thus, the MPPT with fixed step size should make a satisfactory trade-off between the dynamics and oscillations.
Such design dilemma can be solved with variable step size iteration.[7]
MPPT algorithms control techniques have been developed to extract the maximum power from the PV arrays. Among the various MPPT techniques, fractional open-circuit voltage and
short-circuit current techniques provide a simple and effective way to extract maximum power, but they require periodical measurement of open-circuit voltage or short-circuit current for reference, causing more power loss.[6]
An MPPT method with only voltage sensing is more efficient in terms of reduced power loss and low cost. The main function of an MPPT is to adjust its input voltage, which is also the PV panel input voltage, so that it corresponds to the voltage where the panel delivers maximum power. The incremental conductance algorithm seeks to overcome the limitations of the P&O algorithm by using the PV array’s incremental conductance to compute the sign of dP/dV without a perturbation.[7]
At its output, the MPPT always provides the voltage required by the battery or machine pump load.[6] The output of the PV integrated MPPT should be capable of matching all traditional loads, e.g., for batteries or water pumps, using series or parallel configurations.
The principle operation of the Incremental Conductance (INC) algorithm [8] is based on the slope of the power-voltage curve. The photovoltaic module which is positive to the left of peak point, negative to the right of peak point and is zero at the peak power point and is given by equations (1), (2) and (4). During rapidly changing atmospheric conditions the INC algorithm offers a better performance and is highly efficient due to which the losses are reduced. This algorithm gives a more stable output as it adjusts the duty ratio with no oscillations.
The basic equations of INC algorithm are given by the following equations:
dI/dV = -(I/V) at MPP (1)
dI/dV<-(I/V)right of MPP (2) dI/dV > -(I/V) left of MPP (3) The MPPT algorithm block consists of the control algorithms.
These algorithms are implemented for direct duty ratio control due to which the duty ratio is adjusted to operate always on maximum power point for varying irradiance values. The duty ratio acts as an input for the boost converter which maintains the peak power of the solar cells. The load will be then connected to the boost converter.
3. ADAPTIVE VOLTAGE-SENSOR- BASED MPPT
The conventional MPPT methods are usually implemented with a fixed perturbation step size determined by the trade-off between efficiency and tracking speed requirements. Variable step size MPPT methods are used to reduce the tracking time as well as to improve the steady state performance. The step size is defined as a function of either derivative of power to voltage (dP/dV) or derivative of power to duty cycle (dP/dD).
The adaptive MPPT algorithms immensely increase the efficiency of the system by reducing the tracking time and power loss in steady state.
Among the various MPPT techniques P&O and Incremental Conductance are the most widely used techniques. To implement P&O and IncCond methods, both voltage and current sensors are required. In general current sensing is done by using a shunt resistor in differential amplifier configuration, but power losses will occur in current conducting path and the bandwidth is limited by the amplifier.
Hall-effect current sensor can provide an alternative option with low loss and good accuracy, but at a higher price and moreover they are inherently noisy in nature. Thus, an MPPT method with only voltage sensing is more efficient in terms of reduced power loss and low cost. Voltage sensor based MPPT
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technique with fixed step size has been developed and is validated for an interleaved dual boost converter. Later an adaptive voltage sensor based MPPT with a constant start-up scaling factor has been developed by considering dP/dD as an objective function, where P is the power of PV module and D is the duty cycle of the converter. A variable scaling factor is applied in the proposed voltage based adaptive MPPT technique to obtain fast tracking response and reduced steady state oscillations. Steady state behaviour and drift phenomena are the main concern of any MPPT algorithm to determine the tracking efficiency. These analyses for most popular MPPT methods like P&O and IncCond methods are well exist in the literature, but there is no existence of literature analysing steady state behaviour and drift phenomena for voltage sensor based MPPT method.[14]
Fig.No.6 Algorithm of Adaptive Voltage-Sensor-Based In this paper, voltage sensor based algorithm with voltage reference control technique is developed and the corresponding flowchart is given in Fig.12. Among the various MPPT techniques, P&O and IncCond are the most efficient and widely employed algorithms in PV systems.
However, these algorithms require both voltage and current sensors, which results in more implementation cost. The voltage can be easily sensed by a resistive potential divider circuit, but current sensing is difficult and it has some demerits like presence of undesired signals (i.e., noise) in response, power loss, and expensive. Hence, an MPPT method by sensing only PV module voltage is a good choice for minimizing the power loss and price reduction. Voltage- sensor based MPPT algorithm has been validated for interleaved boost and buck converter. An adaptive MPPT with a single voltage sensor has been developed for SEPIC converter and its tracking performance analysis is presented.
However, the algorithm with fixed step size will operate at a non-MPP for a decrease in solar irradiance. The issues with the voltage sensor based method are addressed and a solution is presented in this paper. The MPPT controller is implemented by using SEPIC converter, because of its many advantages. MPPT control algorithms can be implemented by
using direct duty cycle control or closed loop (voltage/current reference) control. The conventional MPPT methods with direct duty cycle control are generally implemented by considering a fixed perturbation in duty cycle (∆D) based on the desired tracking performance. The problem of choosing a proper ∆D can be solved by using variable step size adaptive MPPT techniques. The direct duty cycle control based adaptive methods are developed by defining ∆D as a linear function of either ∆P/∆V or ∆P/∆D. In literature, it is observed that most of the direct duty cycle control based adaptive techniques have been developed with a constant scaling factor, which is chosen based on trial and error. Thus, these adaptive techniques are not an optimal solutions to increase the tracking efficiency of the PV system. Whereas, the adaptive techniques based on closed loop control methods are developed through an analytic design of PI controller. For reducing the tracking time to reach MPP, voltage reference control is preferred rather than current reference control.
Because, the difference in MPP voltages is less compared to the MPP currents for various irradiance and temperature conditions. An MPPT with PI controller gives better performance than direct duty cycle method because of the former inherent adaptive capabilities and the various advantages of using PI controller with MPPT algorithm are discussed.[15]Among all, P & O is a widely used algorithm due to its simplicity and ease of implementation. The limitation of P & O is that it oscillates around MPP, which leads to energy loss and increases convergence time of the algorithm.[15] However, the incremental conductance algorithm improves the efficiency by minimizing oscillation with an accurate calculation of the time derivative of the PV voltage and current, which makes its implementation complex for high-frequency converters with a low-speed controller.
Furthermore, the high-speed heuristic controllers such as neural network and fuzzy logic based have increased tracking efficiency with more computational burden. The methods discussed above are based on the input parameters which use fixed step size (FSS) perturbation and two sensors (input voltage and current). Similarly, FSS output parameter based techniques require sensing of only one parameter (either load current or voltage) by eliminating the necessity of power calculation. Moreover, MPPT performance is largely affected by the perturbation step size having either less steady state tracking efficiency or slow dynamic response. To deal with all these, the adaptive step size MPPT algorithms are gaining more attention for high-speed controllers with a faster dynamic response. However, some of the earlier proposed adaptive techniques overcome these problems with increased implementation complexity and computational burden. In conventional MPPT with fixed step size (FSS) perturbation, it is difficult to achieve fast dynamic response and low oscillation at steady state operation (SSO). For better steady- state operation, ∆D should be small to reduce the power loss due to oscillation around MPP, whereas for transient operation, ∆D should be large to get faster tracking response.
To overcome this problem, an adaptive step size based MPPT technique is proposed which improves the tracking speed and gives a better steady-state response.[16].
1060 4. SIMULATION AND RESULTS
One of the objectives of this thesis is to develop a model to test the dynamic performance of different MPPT algorithms independently of the converter used. The model proposed here was developed in Matlab/Simulink and Matlab/Simscape. It consists of a model of the PV array, the DC-link capacitor,DC-DC converter and load. The MPPT Control block generates the reference voltage using the MPPT algorithm under test.
The parameters of the system used in all the simulations performed in this thesis are as follows:
i) Solar panel specification:
� Open circuit voltage: 22.25 V
� Voltage at MPP: 17.44 V
� Short circuit current: 8.66 A
� Current at MPP: 8.01 A ii) DC-Link Capacitor:1000 µF
iii) Solar irradiation: The irradiance values are given as step input for the PV module.
Fig.No.7 Solar Irradiation
Irradiation will vary from 1000 to 800 at 2 sec, it will fall to 400 at 4 sec. The irradiation will rise from 400 to 700 at 6 sec.
Again it will rise to 1000 at 8 sec.
Fig.No.8 Simulation without MPPT
In this system PV array is fed with the irradiation shown in figure 5.2. The PV array will convert the solar energy into
electrical energy. The resistive load is connected . The voltage
& current are measured for the performance analysis.
The performance analysis of this system can be observed in Figure 5.3. When this irradiation is 1000, the voltage of this system is 19.2 volts, the current is 1.92 amps and the power is 36.88 watts. When the irradiations reduced to 800 at 2 sec the voltage get reduced to 18.94 volts. The current will be the same and power will drop to 35.85 watts. When the irradiations falls to 400 at 4 sec the voltage get drop to 17.92 volts. The current will be the same and power will drop to 32.12 watts.
Fig.No.9 PV voltage, current & power without MPPT The solar irradiations will rise to 700 at 6 sec the voltage will get rise to 18.77 volts. The current will be approximately same and power will rise to 35.21 watts. In the end the solar irradiation will be at 1000. The voltage will rise to 19.2 volts, current will be The same and power will be at 36.87 watts.
The simulink model of PV array with dc-dc boost converter and Inc MPPT algorithm is shown in figure 4.2.2. The step size for the INC MPPT method is generally fixed. The power drawn from the PV array with a lager step size contributes to faster dynamics but excessive steady state oscillations, resulting in a comparatively low efficiency. This situation is reversed while the MPPT is running with a smaller step size.
Thus, the MPPT with fixed step size should make a satisfactory tradeoff between the dynamics and oscillations.
Such design can be solved with variable step size iteration. In this project, modified variable step size algorithm for the INC MPPT method which is dedicated to find a simple and effective way to improve tracking accuracy as well as tracking dynamics are used.
Fig.No.10 PV System with Incremental Conductance MPPT
In this system consist of PV array is fed with the irradiation, DC-DC converter, DC-link capacitor & load. The MPPT
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Control block generates the reference voltage using the MPPT algorithm under test. When the voltage is at its largest or smallest value, if there is variation being applied, the power value will be affected. Hence, to increase power, the voltage can be applied in the same direction. Oscillations can also occurs in this MPP due to noise and errors, increasing computational time and slower sampling frequency from the algorithm.
Fig.No.11 Controller of Incremental conductance MPPT Fig. 11 shows simulation of controller diagrams of Incremental conductance. The MPP tracking is achieved by connecting a dc-dc converter between the PV array and load.
The PV output power is used to directly control the power converter duty cycle to reduce well the complexity of the system. The Controller Logic of With Incremental Conductance MPPT algorithm. Figure no 12 Where the converter duty cycle iteration step size is automatically tuned.
Fig.No.12 Result – Voltage, Current & Power
Fig.No.13 Result – Voltage, Current & Power The above figure 12 shows the results of Incremental conductance MPPT. At starting, when the irradiation is 1000, the voltage of this system is 28.2 volts, the current is 3.92 amps and the power is 81.32 watts. When the irradiations take down to 800 at 2 sec, the voltage get decreased to 27.94volts.
The current will be the same and power will drop to 73.85 watts. When the irradiations take down to 400 at 4 sec, the voltage get fall to 19.32 volts. The current will get reduced to 2.75amps and power will take down to 36.12 watts. The solar irradiations will boost to 700 at 6 sec, the voltage will get rise to 25.37 volts. The current will grow to 3.72 amps and power will rise to 63.21 watts. At the end the solar irradiation will be at 1000. The voltage will rise to 37.2 volts, current will be the same and power will be at 81.57 watts.
CONCLUSION
In this paper, an adaptive voltage-sensor-based MPPT algorithm has been implemented. Most of the MPPT algorithms which can find the real MPP were reviewed. For simplicity and effectiveness reasons, P&O and Incremental conductance were selected for further analysis. The tests confirmed the problems of P&O and Incremental conductance algorithms as reported in the literature. The performances of the modified P&O, Incremental conductance algorithms &
adaptive voltage-sensor-based MPPT were compared and based on the results of the dynamic efficiency tests, it was concluded that the adaptive voltage-sensor-based MPPT perform better than the all methods. The proposed system is designed, and the functionality of MPPT control has been proved. The simulation and experimental results prove that the proposed system is able to track the maximum power from the PV module; moreover, the steady-state two-level operation and the drift-free phenomena are the merits of this tracking algorithm. Hence, this method improves the efficiency of the PV system and reduces power loss in steady state. From the results obtained, it is noticed that, with a well- designed system, including a proper converter and an efficient MPPT algorithm, the MPPT can be developed with less complexity and reduced cost.
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