Maximum Power Point Tracking: Overview and Challenges

Maximum Power Point Tracking: Overview and Challenges

Shiba Ranjan Paital#, Sapan Kumar Nayak*

# Assistant Professor,Department of Electrical Engineering,RITE,Bhubaneswar.

* Assistant Professor,Department of Electrical Engineering,RITE,Bhubaneswar

Abstract The objective of this paper is to discuss some maximum power point tracking techniques which will work effectively in continuously changing atmospheric conditions. A maximum power point tracking algorithm is absolutely necessary to increase the efficiency of the solar panel as it has been found only 30-40% of energy incident is converted into electrical energy. The proposed research investigates the performance of the maximum power point tracking technique which will work efficiently to maximize the utilization efficiency of PV array efficiency. The suitable algorithm has to be chosen for good performance of PV array. For this purpose, comparison among all algorithms is given in discussion and summary.

Keywords- Maximum power point tracking (MPPT), photovoltaic (PV) power system, maximum power point (MPP), switching mode DC-DC converter, MPPT Algorithms.

1. INTRODUCTION

   As the conventional energy sources are rapidly depleting, the importance of solar photovoltaic (PV) energy has been emerging as replaceable energy resources to human being. Since it is clean, pollution-free, and inexhaustible, researches on the PV power generation system have received much attention, particularly, on many terrestrial applications. The main applications of photovoltaic (PV) systems are in either stand-alone (water pumping, domestic and street lighting, electric vehicles, military and space applications) [1-2] or grid-connected configurations (hybrid systems, power plants) [3]. Unfortunately, PV generation systems have two major problems: i.e. the conversion efficiency of electric power generation is very low (9-17%), especially under low irradiation conditions and the amount of electric power generated by solar arrays changes continuously with weather conditions. Moreover, the solar cell V-I characteristic is nonlinear and varies with irradiation and

   temperature. In general, there is a unique point on the V-I or V-P curve, called the Maximum Power Point (MPP), at which the entire PV system (array, converter, etc.) operates with maximum efficiency and produces its maximum output power. The location of the MPP is not known, but can be located, either through calculation models or by search algorithms. Therefore Maximum

   Power Point Tracking (MPPT) techniques are needed to maintain the PV arrays operating point at its MPP. Many MPPT techniques have been proposed in the literature; examples are the Perturb and Observe (P&O) methods [4- 7], the Incremental Conductance (IC) methods [4-8], the Artificial Neural Network method [9], the Fuzzy Logic method [10], etc.These techniques vary between them in many aspects, including simplicity, convergence speed, hardware implementation, sensors required, cost, range of effectiveness and need for parameterization. In this paper, the effectiveness of these different control algorithms is thoroughly investigated via simulation.

   However, efficient use of a PV panel includes some problems for the following two main reasons.

   1. Because of rotation of the world around the sun and itself ongoing, it may not have a fixed position to receive constant vertical solar radiation continuously. Thereby, PV systems may include some circuits to track the world movements depending on the sun consisting of stepper motor or other devices. These mechanisms are called the mechanical tracking systems and increase the amount of produced PV energy [11, 12].

   2. Due to nonlinear I-V curves of PV cells, output power depends on intersection point of load line with this curve. For solar radiation and cell temperature values taken as examples, there is only one point where maximum power is produced. Therefore, operation of the cell at this point is the right option. This process is called as electrical maximum power point tracking or simply MPPT [11].

2. MATHEMATICAL MODELLING

The simplest equivalent circuit of a solar cell is a current source in parallel with a diode. The output of the current source is directly proportional to the light falling on the cell (photocurrent). During darkness, the solar cell is not an active device; it works as a diode, i.e., a p-n junction. It produces neither a current nor a voltage. Thus, the diode determines the IV characteristics of the cell.

P VI Iph Id Vd V

.

R

(8)

sh

Fig 1: Equivalent electrical circuit of an SC.

The output current I and the output voltage of a solar cell are given by,

Vd

III. ALGORITHM FOR FINDING MAXIMUM POWER

POINT

The maximum power point tracking (MPPT) is a controlled dcdc inverter that monitors a photovoltaic panel (PVP) to operate at its maximum power point (MPP) depending on the state of load, it is inserted between the pv array and its electric load to achieve the optimum characteristic matching, so that pv array is able to deliver maximum available power which is also

I Iph Id

Rsh

(1)

necessary to maximize the photovoltaic energy utilization. Pv cell has a single operating point where the values of the current and voltage of the cell result in a maximum

I I

• I exp

  q.Vd

  1 Vd

  power output. These values correspond to a particular

  ph 0

  (2)

  V Vd Rs.I

  n.k.T Rsh

  1. resistance, which is equal to v/i as specified by ohm's law. Also the pv cell has an exponential relationship between current and voltage, so the maximum power point (mpp)

     Here, Iph is the photocurrent, I0 is the reverse saturation current, Id is the average current through the diode, n is the diode factor, q is the electron charge (q = 1.6*1019), k is the Boltzmanns constant (k = 1.38*1023), and T is the solar array panel temperature. Rs are the intrinsic series resistance of the solar cell; this value is normally very small. Rsh is the equivalent shunt resistance of the solar array, and its value is very large.

     In general, the output current of a solar cell is expressed by,

     occurs at the knee of the curve, where the resistance is equal to the negative of the differential resistance (v/i = – dv/di). Additional current drawn from the array results in a rapid drop of cell voltage, thereby reducing the array power output. The aim of this MPPT sub-system is to determine just where that point is, and to regulate current accordingly and thus to allow the converter circuit to extract the maximum power available from a cell. The control methodology presented in this paper will adopt an approach in which designing of the power converter is done by using the relationship existing between the short-

     I I

     q

• I exp

V R I 1 V RsI

circuit current Isc and the MPP current Im. By simulating with various sample data for Isc and Im it is ascertained

ph 0

n.k.T

s

Rsh

1. that the ratio of Im to Isc remains constant at 0.9. Initially the short circuit current Isc is measured and then the

   In (4) the resistances can be generally neglected, and thus, it can be simplified t

   actual load current adjusted in such a way it is equal to a desired fraction value of 0.9Isc.

   q

   q

   IV. DIFFERENT MPPT TECHNIQUES

   I Iph I 0exp

   .V 1

2. There are different techniques used to track the maximum

   n.k.T

   If the circuit is opened, the output current I = 0, and the open-circuit voltage Voc is expressed by

   power point. Few of the most popular techniques are:-

   • Perturbation and Observation method.

     n.k.T I

     n.k.T I

     • Incremental conductance method.

       Voc

       In

       ph 1

       In

       ph

   • Hill climbing method.

   q

   I 0

   q

   I 0

3. • Fuzzy control method.

     If the circuit is shorted, the output voltage V = 0, the average current through the diode is generally neglected, and the short circuit current Isc is expressed by using

     • Neural network Method etc.

     The choice of the algorithm depends on the time complexity the algorithm takes to track the MPP,

     Isc I

     Iph

     implementation cost and the ease of implementation.

     1

     Rs

     Rsh

1. PERTURB AND OBSERVE ALGORITHIM

   P&O Algorithms are widely used algorithm to track the maximum power point due to its simplest structure and

   Finally, the output power P is expressed by

   fewer required parameters. P&O method finds the

   maximum power point of the PV module by means of iteratively perturbing (i.e. Incrementing and decrementing), observing and comparing the power generated by the PV module. In this we use only one sensor, that is the voltage sensor, to sense the PV array voltage and so the cost of implementation is less and hence easy to implement[5,6].

   In the P&O method, the load of the photovoltaic system is adjusted in order to change the terminal voltage and output power of the photovoltaic module.The variation of output voltage and power before and after change of load of photovoltaic system is observed and compared to the reference voltage and power for increasing and decreasing the load in the next step. If the power is increased, the perturbation will continue in the same direction in the next cycle, otherwise the perturbation direction will be reversed.That means the PV array terminal voltage is perturbed at every maximum power point tracking cycle. Therefore when maximum power point is reached, the P&O algorithm will oscillate around it, resulting in a loss of PV power, especially in case of constant or slowly varying atmospheric condition. It can be observed that regardless of the magnitude of sun irradiance(G) and terminal voltage(V) of PV modules, the maximum power point is obtained while the condition dP/dV= 0 is accomplished. The slope (dP/dV) of the power can be calculated by the consecutive output voltages and output currents. The basic operating procedure of P&O method is shown in figure 3.

   Fig. 3 Basic operating procedure of P&O method

   Let Point A be the starting point with voltage V at power P1.The load of the PV system is adjusted in order to change the terminal voltage and output power of the PV module.Let for a perturbation of ,Operating point moves from point-A to point-B. Due to which there is a decrease in power of the PV system[7].

   When weather condition is steady.If solar radiation increases in one sampling period, then the power curve Moves from P1-P2.and the operating point moves from A- D instead of A-B.Due to which power is increased but the voltage still moves towards the V direction.

   The operating point is further away from the maximum power point .i.e. point- C is the operating point but not the maximum power point.With increase in solar radiation, the change in voltage increases but the operating point shifts

   away from the maximum power point which results in power loss of PV module and efficiency reduces. However the method does not take account of the rapid change of irradiation level (due to which MPPT changes) and considers it as a change in MPP due to perturbation and ends up calculating the wrong MPP. To avoid this problem we can use incremental conductance method.

   Restrictions of Perturb & Observe algorithm:

   In a situation where the irradiation changes quickly, the Maximum Power Point also moves on the right hand side of the curve. The algorithm takes it as a change due to perturbation and in the next iteration it changes the direction of perturbation and hence goes away from the MPP as shown in the figure.

   Case	Conditions	Position	Control Action
   1.	PK>0, VK>0	Left of MPP	Increase
   2.	PK>0, VK<0	Right of MPP	Decrease
   3.	PK<0, VK>0	Right of MPP	Decrease
   4.	PK>0, VK<0	Left of MPP	Increase

   The advantages of the P&O method are

   • Simple structure, easy implementation and less required parameters.

     The shortcomings of the P&O method can be summarized:

     • The power tracked by the P&O method will oscillate and perturb up and down near the maximum power point. The magnitude of oscillations is determined by the magnitude of variations of the output voltage. There is a misjudgment phenomenon for the P&O method when weather conditions change rapidly.

     • The PV system cannot always operate at the maximum power point due to the slow trial and error process, and thus the solar energy from the PVarrays are not fully utilized.

   • The PV system may always operate in an oscillating mode even with a steady-state sunshine condition, leading to fluctuating inverter output

   • The operation of the PV system may fail to track the maximum power point due to the sudden changes in sunshine.

   Flow Diagram of Perturb & Observe algorithm:

   Fig.4. Flow diagram for P&O Method.

   Summary of P&O Algorithm Cases

2. INCREMENTAL CONDUCTANCE ALGORITHM

Incremental conductance method uses two voltage and current sensors to sense the output voltage and current of the PV array. The incremental conductance method is to determine the variation direction of the terminal voltage for PV modules by measuring and comparing the incremental conductance and instantaneous conductance of PV modules. If the value of incremental conductance is equal to that of instantaneous conductance, it represents that the maximum power point is found.Incremental conductance method is used to overcome the disadvantages of P&O algorithm. The change in the array power is due to the change in array terminal voltage perturbation. In incremental conductance algorithm the array voltage is always adjusted according to its value relative to MPOP voltage[4,5].

The main difference between Incremental conductance algorithm and P&O algorithm is the judgment on

determining the direction of voltage perturbation.When static conductance Gs is equal to dynamic Conductance Gd, the maximum power point is found.

Mathematically,

The output power from the source can be expressed as, P = V.I

The fact that P = V.I and the chain rule for the derivative of products yields:-

dP/dV = d (V I) / dV

= I dV / dV + V dI / dV

= I + V dI / dV

(1/V) dP/dV = (I/V) + dI/dV (9) Lets define the source conductance:

G = -I/V (10)

And the source incremental conductance: