Improved Maximum Power Point Tracking Algorithm and Optimization

International Journal of Emerging trends in Engineering and Development ISSN 2249-6149

Available online on http://www.rspublication.com/ijeted/ijeted_index.htm Issue 2, Vol.5 (July 2012)

Page 255

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Abstract-----This paper acquaints with an improved maximum power point tracking algorithm and performance

optimization technique to a grid connected hybrid system. The hybrid system consists of photovoltaic array and fuel

cell. The Grid connected hybrid system operated in two modes, in constant power mode desired load power is

compensated by a grid as a first mode and in the second mode increased load power compensated by hybrid system

as a hybrid control mode. The reference values of grid and hybrid system are estimated from maximum power point

tracking perturbation and observation algorithm. This system is analysed by The Hybrid Optimization Model for Electric Renewable (HOMER) software. It has been used to perform random selection of sizing and operational

strategy of generating system in order to obtain the finest solution of hybrid renewable energy (solar PV-FC grid

assisted power system) with lowest Total Net Present Cost (TNPC). Also it is presents a scenario for supplying

electricity by using micro grid hybrid power system consisting of renewable energy.

Index Terms----PV array, Fuel cell, Grid connected, Hybrid System Optimization, Power Management,

_______________________________________________________________________________________________________

I. INTRODUCTION

RENEWABLE energy is currently widely used. One of these resources is solar energy. The grid connected

photovoltaic array system is existing already but the disadvantage of PV energy is that the PV output power depends

on weather conditions and cell temperature and it is not available during night time. The photovoltaic (PV) array

normally uses a maximum power point tracking (MPPT) technique to continuously deliver the highest power to the

load when there are variations in irradiation and temperature. In order to overcome these inherent drawbacks,

alternative sources, such as fuel cell should be installed in the hybrid system. Then the hybrid source output

becomes controllable. However, fuel cell, in its turn, works only at a high efficiency within a specific power range

[1], [2].

The hybrid source is connected to the main grid at the point of common coupling (PCC) to deliver power to the

load. When load demand changes, the power supplied by the main grid and hybrid system must be properly

changed. The power delivered from the main grid and PV array as well as fuel cell must be coordinated to meet load

demand. The hybrid source has two control modes: 1) Constant power control (CPC) mode or unit power

control(UPC) mode and hybrid power control (HPC) mode or feeder flow control mode. In the CPC mode,

variations of load demand are compensated by the main grid because the hybrid source output is regulated to

reference power. Therefore, the reference value of the hybrid source output must be determined. This operating

Manuscript received October 9, 2011. (Write the date on which you submitted your paper for review.). Full names of authors are preferred in

the author field, but are not required. Put a space between authors’ initials.

karri v v satyanarayana. PG student of BVC Engineering college odalarevu-533210, ([email protected])

M Srinivasa Rao,Associate professor of EEE in BVC Engineering college odalarevu([email protected]) ,K Muruga

Perumal,Assistant professor of EEE in Regency Institute of Technology ,yanam-533464 ([email protected]) .

Manuscript received October 9, 2011. (Write the date on which you submitted your paper for review.). Full names of authors are preferred in

the author field, but are not required. Put a space between authors’ initials.

karri v v satyanarayana. PG student of BVC Engineering college odalarevu-533210, ([email protected]) M Srinivasa

Rao,Associate professor of EEE in BVC Engineering college odalarevu([email protected]) ,K Muruga Perumal,Assistant professor

of EEE in Regency Institute of Technology ,yanam-533464 ([email protected]) .

Improved Maximum Power Point Tracking

Algorithm and Optimization Technique for

a Grid Connected Hybrid System

*Karri V V Satyanarayana **M.Srinivasa Rao ***K.Muruga Perumal

mailto:[email protected]








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strategy will minimize the number of operating mode changes, improve performance of the system operation, and

enhance system stability.

II. SYSTEM DESCRIPTION

A. Structure of Grid-Connected Hybrid Power System

The system consists of a PV-FC hybrid source with the main grid connecting to loads at the PCC as shown in Fig.

1.The photovoltaic [3], [4] and the PEMFC(proton exchange membrane fuel cell)[5],[6] are modeled as nonlinear

voltage sources. These sources are connected to dc–dc converters which are coupled at the dc side of a dc/ac

inverter. The dc/dc connected to the PV array works as an MPPT controller. Many MPPT algorithms have been

proposed in the literature, such as incremental conductance (INC), constant voltage (CV), and perturbation and

observation (P&O). The P&O method has been widely used because of its simple feedback structure and fewer

measured parameters [7]. The P&O algorithm with power feedback control [8]–[10] is shown in Fig. 2. As PV

voltage and current are determined, the power is calculated.

B. PV Array Model

The mathematical model [3], [4] can be expressed as

Equation (1) shows that the output characteristic of a solar cell is nonlinear and vitally affected by solar radiation,

.

Fig 1: Grid-connected PV-FC hybrid system

Temperature, and, load condition. Photocurrent is directly proportional to solar radiation

(2)

The short-circuit current of solar cell depends linearly on cell temperature

(3) Thus, photovoltaic current depends on solar irradiance and cell temperature

(4)



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(5)

Fig 2: P&O MPPT algorithm.

C. PEMFC Model

The PEMFC steady-state feature of a PEMFC source is assessed by means of a polarization curve, which shows

the nonlinear relationship between the voltage and current density. The PEMFC output voltage is as follows [5]:

(6) Where ENerst is the “thermodynamic potential” of Nerst, which represents the reversible (or open-circuit) voltage of

the fuel cell. Activation voltage drop is given in the Tafel equation as

(7) Where a, b are the constant terms in the Tafel equation (in volts per Kelvin).The overall ohmic voltage drop can be

expressed as

(8) The ohmic resistance of PEMFC consists of the resistance of the polymer membrane and electrodes, and the

resistances of the electrodes. The concentration voltage drop is expressed as

(9)

D. MPPT Control

Many MPPT algorithms have been proposed in the literature, such as incremental conductance (INC), constant

voltage (CV), and perturbation and observation (P&O). The two algorithms often used to achieve maximum power

point tracking are the P&O and INC methods. The INC method offers good performance under rapidly changing atmospheric conditions. However, four sensors are required to perform the computations. If the sensors require more

conversion time, then the MPPT process will take longer to track the maximum power point. During tracking time,

the PV output is less than its maximum power. This means that the longer the conversion time is, the larger amount

of power loss [7] will be. On the contrary, if the execution speed of the P&O method increases, then the system loss



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will decrease. Moreover, this method only requires two sensors, which results in a reduction of hardware

requirements and cost. Therefore, the P&O method is used to control the MPPT process. In order to achieve

maximum power, two different applied control methods that are often chosen are voltage-feedback control and

power-feedback control [8], [9].

I. CONTROL OF THE HYBRID SYSTEM

The control modes in the micro grid include unit power control, feeder flow control, and mixed control mode. The

two control modes were first proposed by Lasserter [12]. Both of these concepts were considered in [13]–[16]. In

this paper, a coordination of the UPC mode and the FFC mode was investigated to determine when each of the two

control modes was applied and to determine a reference value for each mode. Moreover, in the hybrid system, the

PV and PEMFC sources have their constraints. Therefore, the reference power must be set at an appropriate value so

that the constraints of these sources are satisfied.

II. OPERATING STRATEGY OF THE HYBRID SYSTEM

As mentioned before, the purpose of the operating algorithms to determine the control mode of the hybrid source

and the reference value for each control mode so that the PV is able to work at maximum output power and the

constraint refulfilled Oncethe constraints(fuel cell power lower limit, fuel cell power upper limit, fuel cell power

maximum limit) are known, the control mode of the hybrid source (UPC and FFC modes) depends on load

variations

Fig 3: operating strategy of hybrid source in UPC mode

and the PV output. The control mode is decided by the algorithm shown in Fig. 6, Subsection B. In the UPC mode,

the reference output power of the hybrid source depends on the PV output and the constraints of the FC output. The

algorithm determining hybrid source reference power is presented in Subsection A and is depicted in Fig. 3.

A. Operating Strategy for the Hybrid System in the UPC Mode



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In the UPC mode, the hybrid source regulates the output to the reference value .Then Fig. 3 shows the operation

strategy of the hybrid source in UPC mode to determine hybrid source reference.

(10) The algorithm includes two areas: Area1 and Area 2. In Area 1,Ppv is less than Ppv1, and then the reference

power is set at fuel cell upper limit power where

(11) Area 2 is for the case in which PV output power is greater than Ppv1. As examined earlier, when the PV output

increases to Ppv1, the FC output will decrease to its lower limit. If PV output keeps increasing, the FC output will

decrease below fuel cell lower limit. In this case, to operate the PV at its maximum power point and the FC within its

limit, the reference power must be increased. As depicted in Fig. 3, if PV output is larger than Ppv1, the reference

power will be increased by the amount

Of ΔPms , and we obtain

(12) Fig.4.shows the control algorithm diagram for determining the reference power automatically .If increases the

number of change of will decrease and thus the performance of system operation will be improved. However, C

should be small enough so that the frequency does not change over its limits

Fig 4: Control algorithm diagram in UPC Mode

To avoid the oscillations around the boundary, a hysteresis is included and its control scheme to control is depicted

in Fig. 5.

B. Overall Operating Strategy for the Grid-Connected Hybrid System

The purpose of the algorithm is to decide when each control mode is applied and to determine the reference value

of the feeder flow when the FFC mode is used. This operating strategy must enable the PV to work at its maximum

power point, FC output, and feeder flow to satisfy their constraints .If the hybrid source works in the UPC mode, the

hybrid output is regulated to a reference value and the variations in load are matched by feeder power. On the other

hand, when the hybrid works in the FFC mode, the feeder flow is controlled to a reference value and, thus, the

hybrid source will compensate for the load variations. In this case, all constraints must be considered in the



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operating algorithm. The operation algorithm in Fig. 6 involves two areas (Area I and Area II) and the control mode

depends on the load power. If load is in Area I, the UPC mode is selected. Otherwise, the FFC mode is applied with

respect to Area II.

In the UPC area, the hybrid source output is hybrid source reference power. If the load is lower than reference

power, the redundant power will be transmitted to the main grid. Otherwise, the main grid will send power to the load side to match the load demand.

Fig 5: Hysteresis control scheme for Hybrid reference value

Fig 6: Overall operating strategy



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In the above algorithm the reference parameters show in table.1

III. SIMULATION RESULT

Fig. 7 shows the simulation results when hysteresis was included with the control scheme shown in Fig. 5. From

12 s to 13 s and from 17 s to 18 s, the variations of

Fig 7: Operating strategy of the hybrid source without hysteresis

Fig 8 (a-d): Improving operation performance by using hysteresis



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Reference hybrid power [Fi8 (b), line] are eliminated and, thus, the system works more stably. Fig. 8(d) shows the

frequency variations when load changes or when the hybrid source reference power changes (at 12 s and 18 s). The

parameter C was chosen at 0.03 MW and, thus, the frequency variations did not reach over its limit.

IV. PERFORMANCE OPTIMIZATION TECHNIQUE

The above discussed hybrid system is subjected into performance optimization through creation of Hybrid

Optimization Model for Electric Renewable (HOMER)

A. Operational Scheme

The intended hybrid energy system is incorporated of Renewable source PV and FC grid supply. Hear Fuel cell

getting hydrogen fuel from hydrogen tank which was filled by electrolyser. This electrolyser supplied by DC bus.

This integrated system is totally designed for supply electrification to the selected sample load. i.e., 150KWh/d, 13KW peak loads. For operational measurement a software HOMER (Hybrid Optimization Model for Electric

Renewable) is assigned [10]. This software is used for cost optimizing with different sensitivity variables. Here, the

varying subjects are load, global solar irradiation, wind speed, PV azimuth and converter design. Model organization

of Homer has been addressed in Figure 10.

Fig 9: Operational Scheme.

Cited place for this project (RIT-Yanam) is a river base land. It’s latitudes 16°42′ N to ′16°43′ North and

longitudes 82°11′to 82°19 East respectively. Here, the load is counted by yearly observation.

B. Solar resource and PV cost inputs

With this latitude and longitude HOMER software has automatically collected the global solar rate for the

place. The average solar irradiation is 5.21 kWh / m2 /day. The site is located at GMT+05:30 Zone. The initial size

of PV array used for this project .it’s Price for 1 KW capacity is retained at INR 40,000 /- [6] and replacement cost

is INR 20,000 /-. Different sensitivity variables have been used up to 100KW, as well as different PV azimuths have

been set for a lifetime of 25 years.[10]

Fig 10: Month wise Clearness Index and Solar Radiation



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C. Fuel cell

With the help of Electrolyser and Hydrogen tank the fuel cell obtain require amount of Hydrogen fuel. The

cost for 1KW fuel cell is INR 30,000/- [6] with the replacement cost of INR 15,000/-

D. Converter

Selected converter with 90% of inverter efficiency and rectifier efficiency 85% its life time 20 years of 1KW

power. if the inverter can operate at the same time as one or more AC generators. Inverters that are not able to operate this way are sometimes called switched inverters.

E. Economics and Constraints

Annual interest rate of the project is 6% and the project life time has been set to 20 years and consider this

project fixed capital cost INR 10,000/-. For constraints Minimum renewable fraction has been fixed 50 %.

Maximum annual capacity storage 10 %.system operating reserve for hourly load 10% and annual peak load is 4%.

V. SENSITIVITY ANALYSIS OF THE HYBRID SYSTEM

HOMER performs the optimization process in order to determine the best configuration of hybrid renewable

energy

System based on several combinations of equipments. Hence, multiple possible combinations of equipments could

be obtained for the hybrid renewable energy system due to different size of PV array system, number of batteries

and size of DC-FC converter. In the optimization process will simulate every combination system configuration in

the search space. The feasible one will be displayed at optimization result sorted based on the Total Net Present Cost

(TNPC) [11]-[14].The combination of system components is arranged from most effective cost to the least effective cost. The optimization results of hybrid renewable energy system are obtained for every selection of sensitivity

variables.

Table 2 shows a list of optimization results for the hybrid renewable energy system with considering the

sensitivity variables. The results represent different combination of components which are PV array system, AC grid

supply, battery and converter. However, sensitivity variables should be taken into account in order to obtain a

rational result of hybrid renewable energy system [14].

Table 2: Optimization Result for selected Hybrid Power System



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The average annual solar radiation, Grid supply cost, component price, Technology advance and it’s cost

change

Variables considered for the optimal design of the system.

A. Cost Summary of System

Based on analysis the system takes $ 113,000 for capital investment .Total system cost including replacement

and operational cost it need $ 13,599 .the summery based on the total cash flow, categorized either by component

or by cost type.

Fig 11: Cash flow Summary

B. Operational strategy of Power generation

In this part of simulation we can identify details about the production and consumption of electricity by the

system is tabulated in table 3 and 4.

Table 3: Power Production from hybrid system

Component Production

In KWh/Yr

Percent

Fraction

PV array 178,092 87

Fuel Cell 1,476 1

Grid purchases 25,358 12

Total 204,927 100

Table 4: Power Consumption from system

Load Consumption

In KWh/Yr

Percent

Fraction

AC primary load 54,738 46

Electrolyzer load 19,619 17

Grid sales 43,503 37

Total 117,861 100

Table 5: Excess Electricity production from system

Quantity Value Percent

Excess electricity 78,968 38.5

Renewable fraction 0.876

mk:@MSITStore:C:\PROGRA~1\HOMERE~1\HOMER\HOMER.CHM::/page-details-cost-summary.htm



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From the Table 5 the renewable fraction value can be calculated and the figure 12 clearly shown month wise

Electric power production

Fig 12: Month wise Electric Power Production

C. P V module performance

In this part of simulation used to determine roof top PV module power generation performance based on month

wise .The total hours of operation is 4,314 hr/yr

Table 6: performance Data of PV module

Details of PV Value Units

Rated capacity 100 kW

Mean output 488 kWh/d

Hours of operation 4,314 hr/yr

Mean output 20 kW

Maximum output 110 kW

Fig 13: PV Array Power output monthly average

D. Fuel cell performance

The fuel cell giving overall performance as based with following parameter.

mk:@MSITStore:C:\PROGRA~1\HOMERE~1\HOMER\HOMER.CHM::/page-details-pv.htm



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Fig 14: monthly Average hydrogen production.

Table 7: Fuel Cell performance

Quantity Values Units

Hours of operation 82 hr/yr

Number of starts 81 starts/yr

Operational life 488 yr

Capacity factor 0.843 %

Fixed generation cost 2.15 $/hr

Marginal generation cost 0.000000223 $/kWh

Electrical production 1,476 kWh/yr

Mean electrical output 18.0 kW

Min. electrical output 0.644 kW

Max. electrical output 20.0 kW

Hydrogen consumption 417 kg/yr

Specific fuel consumption 0.282 kg/kWh

Fuel energy input 13,886 kWh/yr

Mean electrical efficiency 10.6 %

E. Grid Performance

In this part of simulation we can identify details about the purchases from grid and sales to the grid if the system

is grid-connected and about the breakeven grid extension. If the system is not grid-connected.

Table 8: Power Scenario of Grid

Month

Energy

Purchased

Energy

Sold

Net

Purchases

Peak

Demand

Energy

Charge

Demand

Charge

(kWh) (kWh) (kWh) (kW) ($) ($)

Jan 2,206 3,693 -1,487 9 36 0

Feb 1,874 3,654 -1,780 9 5 0

Mar 2,035 3,844 -1,809 9 11 0

Apr 2,309 3,560 -1,251 10 53 0

May 2,433 3,514 -1,080 10 68 0

Jun 2,442 3,132 -691 10 88 0

Jul 2,462 3,295 -833 10 81 0

Aug 1,995 3,514 -1,519 9 24 0

Sep 2,039 3,300 -1,261 9 39 0

Oct 2,076 3,827 -1,751 9 16 0

Nov 1,699 4,014 -2,315 9 -31 0

Dec 1,788 4,156 -2,368 9 -29 0

Annual 25,358 43,503 -18,145 10 361 0

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F. Converter Performance

We can find details about the operation of the inverter and rectifier, including capacity, electrical input and

output, hours of operation, and losses. Total hours of operation are 4,389 hrs/yr and total loss in converter is 8,097

kWh/yr.

Fig 15: Inverter output performance

G. Emissions

We can find annual pollutants emitted by the system. It can use for find carbon credit

Table 9: Statics of Emission (kg/yr)

Pollutant Emissions

(kg/yr)

Carbon dioxide -17,967

Carbon monoxide 2.71

Unburned Hydrocarbons 0.3

Particulate matter 0.204

Sulfur dioxide -49.7

Nitrogen oxides -0.153

VI. CONCLUSION

This paper has presented an available method to operate a

Hybrid grid-connected system and its performance based optimization. The hybrid system, composed of a PV array

and PEMFC, was considered. The operating strategy of the system is based on the UPC mode and FFC mode. The

purposes of the proposed operating strategy presented in this paper are to determine the control mode, to minimize

the number of mode changes, to operate PV at the maximum power point, and to operate the FC output in its high-

efficiency performance band. The main operating strategy, shown in Fig. 6, is to specify the control mode; the

algorithm shown in Fig. 3 is to determine in the UPC mode. With the operating algorithm, PV always operates at

maximum output power, PEMFC operates within the high-efficiency range , and feeder power flow is always less

than its maximum value . The change of the operating mode depends on the current load demand, the PV output, and

the constraints of PEMFC and feeder power. With the proposed operating algorithm, the system works flexibly,

exploiting maximum solar energy.

The technical and economical feasibility of a solar PV-FC grid assisted hybrid power system to supply

electricity and energy for a selected sample load. This hybrid power system has been sized, simulated and evaluated

using HOMER software. The yearly average daily solar radiation intensity received at the Yanam campus has

around 5.82 kWh/ m2/ day and is a sufficient amount of energy resource for a Hybrid PV power system. From the

simulation results, it is found that for a hybrid system with RF of 0.88, the NPC of the hybrid system is US$ 125,374

and the COE is $0.197 per KWh which is reasonable for energy generation based on renewable energy. The

findings of this study suggest that the solar PV-FC Grid system should be implemented since it is a more economical



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and cleaner source of power as compared to the conventional energy power system. This hybrid system is a step

towards a cleaner and greener future

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Karri v v satyanarayana. Pursuing M.Tech in BVC Engineering college odalarevu.His specialization is power

electronics. He received his B.Tech in Electrical and Electronic Engineering from KIET Engineering college,jntu

Hyderabad ([email protected])

M Srinivasa Rao is currently working as a Associate Professor in Electrical and Electronics Engineering

Department,BVC Engineering College odalarevu. He obtained his M.Tech Degree in power system from J N T U

kakinada. He received B.E in Electrical and Electronic Engineering from Adhiyamaan college of Engineering.

University of Madras. He research interes includes renewable energy, power system,micro grid,smart grid

([email protected])

K.Muruga Perumal is currently working as Assistant Professor in Electrical and Electronics Engineering department, RIT-Yanam .He received his M.Tech in Power System with emphasis on High voltage engineering

from JNTU-Kakinada. He obtained his B.E in Electrical and Electronic Engineering from VRS college of Engg-

Arasur, Anna University. His research interests include renewable energy, micro-grid, and smart-

[email protected]

http://www.ren21.net/pdf

http://homerenergy.com/download.asp




Improved Maximum Power Point Tracking Algorithm and Optimization

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