Arise'14 Ijert

Watermarking of Compressed imageswithImproved

Encryption

Deepa L C

Department of Computer Science, CUSAT

TKM Institute of Technology

Kollam,Kerala,India

[email protected]

Meerakrishna G H Department of Computer Science, CUSAT

TKM Institute of Technology

Kollam,Kerala,India

[email protected]

AbstractMedia data generally Handles In compressed and encrypted form. It is necessary To watermark these compressed

encrypted media Items in the compressed encrypted

domainitselffortamperdetectionorownershipdeclaration

orcopyrightmanagement purposes. It is a challenge to watermark

this media data in compressed and encrypted domain because of

security and visual quality problems. The watermarking in

encrypted domain gives double security. Thus it is necessary to

choose a watermark embedding and encryption scheme for

maintaining both security and visual quality. In this work, a

robust approach for watermarking images in compressed and

encrypted domain is presented. The encryption algorithm here

used is Rijndael encryption algorithm. While the proposed

technique embeds watermark in the compressed-encrypted

domain, the extraction of watermark can be done in the decrypted

domain. The watermark embedding technique used is Rational

Dither Modulation (RDM).

Keywords Compressed and Encrypted domain watermarking, copyright, Visual cryptography, RDM

I. INTRODUCTION

Watermarking has an important role in the digital media

content distribution. It is necessary to watermark these

compressed encrypted media items in the compressed

encrypted domain itself for tamper detection or ownership

declaration or copyright management purposes. Digital Right

management system is an example, where the owner of

multimedia content, distribute it in a compressed and encrypted

format to consumers through multilevel distributor network,

each distributor sometime needs to watermark the content for

media authentication, traitor tracing or proving the

distributorship. Watermarking has an important role in DRM

systems. It helps publishers; copyright protectors etc to keep

track their digital data after sale. It helps the developers to

transfer the media data securely in this domain. In DRM

systems there are multiple levels of distributers and consumers.

The distributors dont have access to the plain text. This paper focus on the watermarking of compressed encrypted images,

where the encryption refers to the ciphering of complete

compressed stream. Watermarking in compressed-encrypted

content saves the computational complexity as it does not

require decompression or decryption, and also preserves the

confidentiality of the content because it doesnt need decryption at the time of watermark embedding.A V

Subramanyam (2012) [1] proposed a robust watermarking

algorithm to watermark jpeg2000 compressed encrypted

images.The technique here used was spread spectrum. But the

problem was that this technique has only low number of bit

capacity. GaoHai-ying, Liu Guo-qiang, and XuYin(1993) [2]

proposed a new robust watermarking algorithm for JPEG2000

images. Here the watermark information is embedded by

modifying the wavelet coefficients in pairs after quantization of

the original image. The main problem of this work was image

quality degradation and the lack of ability to resist attacks. To

overcome this problem Kan Li and Xiao-Ping Zhang(2001) [3]

proposed a robust adaptive watermarking scheme .It was a

compression degree adaptive method .Here the watermark will

be embedded in to the middle frequency wavelet coefficients

after quantization. But this approach couldnt overcome the security problems. Roland Schmitz (2006) [4] proposed a

commutative watermarking encryption method. It was

designed by combining histogram based watermarking scheme

with a permutation cipher. Here the permutation cipher is used

toencrypt the multimedia data. The disadvantage of this work

was that it was not a secure method. Zhi Li and Yong Lian

(2007) [5] introduced a method for content dependent

watermarking and authentication. It had been proposed as a

solution to overcome the potential estimation attack aiming to

recover and remove the watermark from the host signal. A

watermarking scheme based on TCQ quantization scheme was

proposed by D.Goudia(2009) [6]. The main contribution is that

this system allows both quantization of wavelet coefficients

and watermark embedding by using the same quantization

module.

In this paper we focus on watermarking of compressed-

encryptedimages, where the encryption refers to the ciphering

of images in compressed stream. The aim of watermarking is to

provide the digital media content creator with the ability to

keep track of their media data after sale. Watermarking is a

data hiding method. This technique is mainly used in one to

many communications. Watermarking can be done in

encrypted domain or compressed domain. The problem of

watermarking in encrypted domain is that changing a single bit

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International Journal of Engineering Research & Technology (IJERT)

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ARISE' 14 Conference Proceedings

may lead to random decryption and there is no strong security

in compressed domain. So here we choose the compressed and

encrypted domain. In our algorithm the watermark embedder

only have compressed encrypted content. Also the watermark

embedders do not have the key to unencrypt and get the plain

text compressed values. However the proposed system faces

the following challenges.

1) Compressed Domain Watermarking: A small modification in the compressed data may lead to the

degradation of decoded image. Thus we have to find the place

for embedding the data very carefully, so we can reduce the

visual quality degradation.

2) Encrypted Domain Watermarking and Watermark Retrieval: In an encrypted piece of content, changing even a

single bit may lead to a random decryption; therefore the

encryption should be such that the distortion due to embedding

can be controlled to maintain the image quality. It should also

be possible to detect the watermark correctly even after the

content is decrypted. Also, the compression gain should not be

lost as encryption may lead to cipher text expansion.

This paper is organized as follows. Section II describes the

proposed scheme. In section III we discuss the encryption

algorithm, watermark embedding and extraction algorithm .The

experimental results are discussed in Section IV. Section V

concludes the paper. The theoretical analysis and derivations

are given in the Appendix.

II. PROPOSED SCHEME

Overview

At first blue region detection is performed on input image

using HSV color space.Secondly cover image is transformed

in frequency domain. (DWT) This is performed by DWT on

image leading to four subbands.Then payload (number of bits

in which we can hide data) is calculated. Then secret data

embedding is performed in one of the high frequency sub-

band by tracingblue area pixels in that band.Then extract it.

Plain Text ( In form of Image)

Encryption ( Creating shares)

Channel (Cover image , Dither Modulation)

Extraction

Decryption

A. Image Compression

The image compression is divided into five stages. In the

first stage the input image is preprocessed by dividing it into

non-overlapping rectangular tiles, the unsigned samples are

then reduced by a constant to make it symmetric around zero

and finally a multi-component transform is performed. In the

second stage, the discrete wavelet transform (DWT) is applied

followed by quantization in the third stage. Multiple levels of

DWT gives a multi-resolution image. The lowest resolution

contains the low-pass image while the higher resolutions

contain the high-pass image. These resolutions are further

divided into smaller blocks known as code-blocks where each

code-block is encoded independently. Further, the quantized-

DWT coefficients are divided into different bit planes and

coded through multiple passes at embedded block coding with

optimized truncation (EBCOT) to give compressed byte stream

in the fourth stage. The compressed byte stream is arranged

into different wavelet packets based on resolution, precincts,

components and layers in the fifth and final stage. Thus, it is

possible to select bytes generated from different bit planes of

different resolutions for encryption and watermarking.

B. Encryption Algorithm

The encryption method we are using here is Visual

cryptography&Rijndael. The secret image will be divided into

two shares

Share 1

Share2

Stacking the shares reveals the secret.

Fig 1:Visual cryptography

Visual cryptography scheme in computer representation using

nm matrix is as follows:

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Orginalpixel :

Share 1 (S1) :

Share 2 (S :

Using the permutated basis matrices, each pixel from the secret image will be encoded into two sub pixels on each participant's share. A black pixel on the secret image will be encoded on the ith participant's share as the ith row of matrix S1, where a 1 represents a black sub pixel and a 0 represents a white sub pixel. Similarly, a white pixel on the secret image will be encoded on the ithparticipant's share as the ith row of matrix S0.

C..Embedding Algorithm

The embedding algorithm uses color image as cover and

grayscale image as watermark. The color image is decomposed

into Luminance, Intensity and Hue channels. The DWT is

applied on the Luminance channel of color image, which

produces the frequency subband coefficients. From these

subband coefficients the highest texture energy subband is

selected. On this subband apply DWT to obtain the second

level decomposition. From this again select a subband having

hightexture energy. Before embedding the watermark into

selected subbands, the watermark image is split into two shares

by applying (2, 2)V CS scheme using AOD . Out of these two shares one share is embedded into selected subband and other

share is kept secret.

The details of the algorithm is as follows:

Algorithm: Watermark Embedding Algorithm.

Input : Cover (Color) image, Watermark (gray-scale) image.

Output : Watermarked color image.

1) Read the cover (color) image I of size N N and watermark

(gray-scale)imageWof size M M

2) Decompose the color image into Luminance (Y ), Intensity (I)

and Hue (Q) channels of size M M

3) Split the watermark by applying V CS using AOD is kept

secret and S1 is used for embedding.

4) Apply DWT on Luminance (Y ) channel to get subband

coefficients (LL1, LH1, HL1 and HH1).

5) Extract the texture property Energy for each subband

coefficient

6) Select the subband frequency coefficients (LL1 or LH1 or

HL1 or HH1 ) which is having high energy.

7) Apply the DWT on selected subband to get second level

decomposition (LL2, LH2, HL2 and HH2).

8) Extract the vector of texture property Energy for each

subband of second level decomposition

9) Select the subband which is having high energy from second

level decomposition (LL2,orLH2 or HL2 or HH2).

10) Embed the share S1 produced in Step 3 into the selected

subband coefficients of Step 9 using following steps.

fori= 1 to M do

forj= 1 to M do

Y_(i, j) = (|Y (i, j)| + )S1(i, j) end for

end for

Where Y_(i, j) represents the modified frequency coefficient of

subband, Y (i, j) represents the original frequency coefficient of

subband, represents the watermark scaling factor. 11) The value of is adjusted such that the texture properties of embedded subband are changed by negligible value

12) Replace the modified subband coefficients into its initial

location and apply twice inverse DWT to get the watermarked

Luminance channel.

13) Combine the watermarked Luminance (Y ) channel with

Intensity (I) and Hue (Q) to get watermarked color image.

D. Extraction Algorithm

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Extraction algorithm is of type blind extraction which uses

only watermarked color image as input. The watermarked color

image is decomposed into Luminance, Intensity and Hue

channels. The DWT is applied on the Luminance channel of

watermarked color image, which produces the frequency

subband coefficients. From these subband coefficient the

highest texture energy subband is selected. On this subband

apply DWT to obtain the second level decomposition. From

this againselect a subbandhaving high texture energy. The

watermark is extracted from these selected subband

coefficients. After extracting the watermark, the watermark

image is superimposed with secret share using V CS scheme as

explained in Section 3. The output of superimposition produces

the extracted watermark. The details of the extraction

algorithm are explained below.

Algorithm: Watermark Extraction Algorithm.

Input : Watermarked (Color) image.

Output : Extracted watermark.

1) Read the watermarked color image I of size N N

2) Decompose the watermarked color image into Luminance

(Y ), Intensity (I) and Hue (Q) channels of size M M

3) Apply DWT on Luminance (Y ) channel to get subband (LL1,

LH1, HL1 and HH1).

4) Extract the texture property Energy for each subband

coefficients.

5) Select the subband frequency coefficients (LL1 or LH1 or

HL1 or HH1 ) which is having high energy.

6) Apply the DWT on selected subband to get second level

decomposition subbands(LL2, LH2, HL2 and HH2)

7) Extract the texture property Energy for each subband of

second level decomposition.

8 Select the subband frequency coefficients which is having

high energy from second level (LL2,orLH2 or HL2orHH2).

9) Extract the share S1 from selected subbandcoefficientsof

Step 9 using following steps.

fori= 1 to M do

forj= 1 to M do

ifY _ _ 0 then

S1(i, j) = 1;

else

S(i, j) = 0;

end if

end for

end for

10) Superimpose extracted share S1with secret share S0using V

CS

III. RESULTS AND DISCUSSION

Security of Encryption Algorithm

To verify the effectiveness of the proposed scheme, a series of

experiments were conducted. By keeping the cipher structure

simple, it becomes accessible to a larger set of people for

evaluation. The simplistic structure also plays a part in

performance and security. The security of the cipher is

amplified by the simple structure. For instance, the rate of

diffusion is improved by several simple steps in the round:

integer multiplication, the quadratic equation, and fixed bit

shifting. The data-dependent rotations are improved, as the

rotation amounts are determined from the high-order bits in f(x),

which in turn are dependent on the register bits. The security

has been evaluated to possess an adequate security margin; this rating is given with familiarity of theoretical attacks, which

were devised out of the multiple evaluations. The AES-specific

security evaluations provide ample breadth and depth to how

RC6 security is affected by the simplicity of the cipher.

Table 1 : Algorithm comparison

Algorithm Key Size Block

size

Algorithm

structure

Rounds Existing

cracks

Rijndael 128,192,256

bits

128 Substitutio

n ,permutat

ion

10,12 or

14

Side channel

attacks

Twofish 128,192,256

bits

128 Feistel

Network

16 Truncated

differential

cryptanalysis

Blowfish 32-448 bit 64 Feistel Network

16 Second order differential

attacks

RC4 Variable Variable

Stream Unknown

Weak key schedule

RC2 8- 128 bit 64 Heavy

Fiestel Network

16 Related key

attacks

TripleDES 112 or 168

bits

64 Feistel

Network

48 Theoritically

possible

DES 56 bits 64 Feistel Network

16 Brute force attacks

IV. CONCLUSION

This paper provides double security through encryption and

watermarking. Encryption provides security by hiding the

content of secret information; while watermarking hides the

existence of secret information. Earlier works were

concentrated on encrypted or compressed domain only.The

proposed system helps to embed a robust watermark in the

compressed encrypted images using the watermarking scheme

spread spectrum. The algorithm is simple to implement as it is

directly performed in the compressed-encrypted domain, i.e., it

does not require decrypting or partial decompression of the

content. This scheme also preserves the confidentiality of

content as the embedding is done on encrypted data. The

homomorphic property of the cryptosystem is exploited, which

allows us to detect the watermark after decryption and control

the image quality as well.

ACKNOWLEDGEMENT

This workwassupportedin partbythe Departmentof

ComputerScience&Engineering, TKMIT,andKollam.We

wouldliketoshow ourgratitudetoProfP.Mohamed

Shameem&Asst.Prof.Meerakrishna G Hfortheirvaluable

guidance.

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REFERENCES

[1] A.V.Subramanyam,SabuEmmanuel,Robustwatermarkingof compressed encrypted JPEG 2000images, IEEEtransactions on multimedia, vol. 14, no.3, june 2012.

[2] Guo-quang,LiuGuo-qiang and Xuyin,A New Robust watermarking algorithm for JPEG2000 images,.

[3] KanLiand Xiao-Ping Zhang, Reliable Adaptive Watermarking Scheme Integrated with JPEG2000,Proceedings of the 3rd International Symposium on Image and Signal Processing and Analysis

(2003).

[4] S. Lian, Z. Liu, R. Zhen, and H. Wang, Commutative watermarking and encryption for media data, Opt. Eng., vol. 45, pp. 13, 2006.

[5] Z. Li, X. Zhu, Y. Lian, and Q. Sun, Constructing secure content dependent watermarking scheme using homomorphic encryption, in Proc. IEEE Int. Conf. Multimedia and Expo, 2007, pp. 627630.

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3D IMAGERY IN ROCKETRY

Soumya V. S M.Tech , Dept of ECE Marian Engineering College

Abstract - 3-D video will become one of the most

significant video technologies in the next-generation. In

rocketry bandwidth is an essential requirement. Due to

the ultra high data bandwidth requirement for 3-D

video, effective compression technology becomes an

essential part in the infrastructure. Thus multiview video

coding (MVC) plays a critical role. MVC is an extended

version of H.264/AVC that improves the performance of

multiview videos. The entire image is divided into

macro blocks. The size of macroblock depends on

codec used. Multi-view video coding (MVC) is an

ongoing standard in which variable size disparity

estimation (DE) and motion estimation (ME) are both

employed to select the best coding mode for each

macroblock (MB). A multidirectional spatial prediction

method is also employed for each macroblock to

reduce spatial redundancy. The multi-view video plus

depth (MVD) coding will give 3D video (3DV). Index Terms- 3D video coding (3DVC), multi-view

video plus depth (MVD), H.264/AVC, multiview video coding (MVC).

I. INTRODUCTION

WITH the development of the technology of 3DTV and free viewpoint TV (FTV), MVC attracts more and more

attention. In recent years, MVC technology is now being

standardized by the Joint Video Team (JVT) as an extension

to H.264 [1].

Subha Varier Scientist/Engineer SG Indian Space Research Organization (ISRO) Thiruvananthapuram.

The sensation of realism can be achieved by visual

presentations that are based on three-dimensional (3D)

im-ages. To generate even more vivid and realistic

informa-tion, it is possible to use two or more cameras

placed at slightly different view-points. This allows the

production of multiview sequences. The Multi-view video structure consists of several video

sequences, which are captured by closely located cameras

in most of the applications. The close location of cameras in

these applications results in a high redundancy between the

sequences from different cameras. 3D video provides a visual experience with depth per-

ception through the usage of special displays that re- pro-ject

a three-dimensional scene from slightly different dir-ections

for the left and right eye. Such displays include stereoscopic

displays, which typically show the two views that were

originally recorded by a stereoscopic camera system. Here,

glasses-based systems are required for mul-tiuser

audiences. Especially for 3D home entertainment, newer

stereoscopic displays can vary the baseline between the

views to adapt to different viewing distances. In addi-tion,

multi-view displays are available, which show not only a

stereo pair, but a multitude of views (typically 20 to more

than 50 views) from slightly different directions. Each user

still perceives a viewing pair for the left and right eye.

However, a different stereo pair is seen when the viewing

position is varied by a small amount. This does not only

improve the 3D viewing experience, but allows the

perception of 3D video without glasses, also for multi-user

audiences. As 3D video content is mainly produced as stereo

video content, appropriate technology is required for

generating the additional views from the stereo data for this

type of 3D displays. For this purpose, different 3D video

formats or representations have been considered. A straight forward method to encode the multi-view

se-quences is simulcast coding, in which each view is

en-coded independently with the state-of-art

H.264/AVC co-dec. Though the H.264/AVC can

achieve a very high cod-ing efficiency for each single

view, statistical results show that there are still

correlations left between different views [2].

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Fig 1: Overall structure of an MVC system

Stereoscopic vision is based on the projection of an object

on two slightly displaced image planes and has an extensive range of applications, such as 3-D television, 3-D

video applications, robot vision, virtual machines, medical surgery

and so on. Two pictures of the same scene taken from two nearby

points form a stereo pair and con-tain sufficient information for

rendering the captured scene depth. The above demanding

application areas re-quire the development of more efficient

compression tech-niques of a stereo image pair or a stereo image

sequence. In a monoscopic video system the compression is based

on the intra-frame and inter-frame redundancy. Typically the

transmission or the storage of a stereo image sequence re-quires

twice as much data volume as a monoscopic video system.

Nevertheless, in a stereoscopic system a more effi-cient coding

scheme may be developed if the in-ter-sequence redundancy is

also exploited. H.264 is the newest international video coding standard.

Compared to prior video coding standards, H.264 mostly enhances

the coding efficiency. So its more possible to resolve the problem of

stereoscopic storage and transmis-sion using coding based on

H.264.Since the multi video approach creates large amounts of data

to be stored or transmitted to the user, efficient compression

techniques are essential for realizing such applications. The

straight-forward solution for this would be to encode all the video

signals independently using a state-of-the-art video codec such as

H.264/AVC [2][4]. However, multiview video contains a large

amount of inter-viewstatistical dependen-cies, since all cameras

capture the same scene from differ-ent viewpoints. These can be

exploited for combined tem-poral/inter-view prediction, where

images are not only predicted from temporally neighboring images

but also from corresponding images in adjacent views, referred to

as Multiview Video Coding (MVC). The overall structure of MVC

defining the interfaces is illustrated in Fig. 1. In this paper, a typical stereoscopic video compression scenario

is mainly studied. The essential requirements are described in

Section II. Section III investigates coding of

stereo views. The prediction structures are presented

in Section IV. Here to obtain 3D view it requires a 3-D

depth impression of the observed scenery. Section V

ex-plains the depth coding approaches. Finally,

Section VI concludes this paper. II. REQUIREMENTS

The central requirement for any video coding standard is high

compression efficiency. In the specific case of MVC, this means

a significant gain compared to inde-pendent compression of

each view. Compression effi-ciency measures the tradeoff

between cost (in terms of bit-rate) and benefit (in terms of video

quality), i.e., the qual-ity at a certain bit-rate or the bit-rate at a

certain quality. However, compression efficiency is not the only

factor un-der consideration for a video coding standard. Some

re-quirements of a video coding standard may even be con-

tradictory such as compression efficiency and low delay in some

cases. Then a good tradeoff has to be found. General

requirements for video coding such as minimum resource

consumption (memory, processing power), low delay, er-ror

robustness, or support of different pixel and color res-olutions,

are often applicable to all video coding standards. III. CODING OF STEREO VIEWS The main difference between classic video coding and

multiview video coding is the availability of multiple cam-

era views of the same scene. As coding efficiency of hy-

brid video coding depends on the quality of the prediction

signal to a great extent, a coding gain can be achieved for

MVC by additional inter-view prediction. If there is no

such gain, independently encoding each camera view

with temporal prediction would already provide the best

pos-sible coding efficiency. A. Disparity-Compensated Prediction

The distance between two points of a superimposed

ste-reo pair that correspond to the same scene point is

called disparity. Disparity compensation is the process

that es-timates this distance (disparity vector or DV),

predicts the right image from the left one and produces

their difference or residual image (disparity compensated

difference or DCD). As a first coding tool for dependent views, the concept of

disparity-compensated prediction (DCP) has been ad-ded as

an alternative to motion-compensated prediction (MCP).

Here, MCP refers to inter-picture prediction that uses already

coded pictures of the same view at different time instance,

while DCP refers to inter-picture prediction

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that uses already coded pictures of other views at the same

time instance. B. Motion Homogeneity Determined

A region with homogeneous motion means that the mo-tions in

the region have homogenous spatial property, and the

corresponding motions in a spatial window are with consistence. A

uniform motion vector field at 4x 4 block level can be generated for

the calculation of motion homo-geneity in each MB. A Block

Matching Algorithm is a way of locating matching blocks in a

sequence of digital video frames for the purposes of motion estimation. The purpose

of a block matching algorithm is to find a match-ing block from a

frame i in some other frame j, which may appear before or after i.

This can be used to discover tem-poral redundancy in the video

sequence, increasing the ef-fectiveness of the interframe video

compression and television standards conversion. Block matching

algorithms make use of an evaluation metric to determine whether a

given block in frame j matches the search block in frame i. IV. PREDICTION STRUCTURES

To the fact that current existing prediction structures lack have

low coding efficiency a Diagonal Interview Pre-diction (DIP) is

presented in this paper, which performs the interview prediction

from the reference pictures of dif-ferent time slots to the encoding

picture. By introducing the DIP, a MVC prediction structure can

support the 3d view of rocketry, while raising the coding efficiency.

In comparison, the traditional interview prediction, in which the

reference picture of the coding picture, is noted as Normal Interview

Prediction (NIP). Figure 2 gives ex-amples of different prediction

structures. Figure 2(a) shows a simple DIP case, in which the en-coding

picture is predicted from two reference pictures of the previous time

slot, in which one is a temporal refer-ence picture, and another one

is an spatial reference picture. Figure 2(b) shows a NIP case, in

which the encod-ing picture is then predicted from a temporal

reference picture and a spatial prediction reference picture but at

the same time slot to the encoding picture. In figure 2(c), the coding

picture is predicted from only one temporal refer-ence picture, and

views are encoded independently, such a coding structure is called

Simulcast coding. In Figure 2(b) structure, the decoding of the current view has

one picture decoding delay compared with the reference view,

i.e. the decoding of picture (T,V) has to wait until the decoding of

picture (T,V-1) is finished.

Figure.2 Diagonal Inter-View Prediction Test Mode. (a) The Diagonal inter-view prediction test mode. (b) Nor -

mal inter-view prediction test mode. (c) Simulcast test But for the structure of DIP in Figure 2(a), the two views

can be decoded simultaneously, as the DIP reference pic-

tures are always been decoded at the previous time slot.

When the number of views becomes very large, the NIP

will cause large decoding delay. As a result, the DIP or

the Simulcast coding mentioned above is a good structure

on the point of decoding delay removing and parallel

comput-ing. Besides the fast algorithm described above, the

motion estimation process in the prediction stage can

be further speed up based on the motion correlation of

different frames. By considering two consecutive

frames of same view motion estimation can be done. V. DEPTH PERCEPTION In the MVC reference software JMVC, different mode

sizes including 16 16, 16 8, 8 16, 8 8, 8 4, 4 8,

and 4 4 are used in the prediction procedures. Large

sizes are usually selected for the macroblocks (MB) in the

regions with homogeneous motion, while small sizes are

selected for the MBs with complex motion. This technique

achieves the highest possible coding efficiency, but

results in extremely large encoding time which obstructs it

from practical use. A depth map represents a relative distance from a cam-

era to an object in the 3D space, it can be regarded as a

grayscale image using dark and bright values to represent far

and close object, and the object depth not only repres-ents

the physical object position in 3D space but also in-dicates

the motion activity of the object itself on the image plane.

Under the condition that cameras are set up in a close

parallelized structure, the depth maps are correlated to the

texture video motion fields. People can see depth because they look at the 3D world

from two slightly different angles (one from each eye). Our

brains then figure out how close things are by determ-ining

how far apart they are in the two images from our

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eyes. The idea here is to do the same thing with a com-puter.

The algorithm is based on Segment-Based Stereo Matching Using Dissimilarity Measure.

The first step is to get an estimate of the disparity at each

pixel in the image. A reference image is chosen, and the other

image slides across it. As the two images slide over one another we subtract their intensity values. Addi-tionally, we

subtract gradient information (spatial derivat-ives). We record

the offset at which the difference is the smallest, and call that

the disparity. Next we combine image information with the pixel dis-parities

to clean up the disparity map. First, we segment the reference

image .Then, for each segment, we look at the associated pixel

disparities. Here assign each segment to have the median

disparity of all the pixels within that segment. This gives depth. VI. CONCLUSION

In rocketry bandwidth is an essential requirement. To achieve good coding efficiency redundancy within a frame and redundancy between views are exploited. Here DE is utilized to exploit inter-view dependencies in MVC.

Although temporal prediction is on average the most efficient

mode in MVC system, there are many reasons for using both DE

and ME to achieve better predictions than using only ME. One

main reason is due to complex motion. In general, the temporal

motion cannot be char-acterized in an adequate way, especially

when there is non-rigid motion (such as zooming, rotational

motion, and deformations of non-rigid objects) or motion edge.

For the former, the ME based on the translational rigid motion

model of blocks fails for zooming, rotational motion and

deformation of non-rigid objects, and thus it produces poor

prediction results. For the latter, the re-gion with motion edges is

usually predicted using small block sizes with large motion

vectors and high residual energy, and thus it has low coding

efficiency. On the other side, usually the disparity which is mainly

determ-ined based on the relative positions of the objects and

cameras is more structured than the temporal motion in complex

motion region. MBs in region with complex motion are more likely

to choose the inter-view predic-tion mode. Thus, the

region with homogeneous motion is more likely to select

temporal prediction mode where inter-view prediction is

not needed, and the region with complex motion is more

likely to select inter-view pre-diction mode. The

comparative experimental results show that the proposed

algorithm not only significantly reduces the complexity of

MVD coding while improves the coding performance, but

also maintain the rendering quality. REFERENCES ISO/IEC/JTC1/SC29/WG11, Multiview Coding Us-ing AVC, Bangkok, Thailand, Jan. 2006. [1] U. Fecker,and A. Kaup, Statistical Analysis of Multi-Reference Block Matching for Dynamic Light Field Cod-ing, Proc. 10th International Fall Workshop Vision, Mod-eling, and Visualization, pp. 445-452, Erlangen, Germany, Nov. 2005. [2] Advanced Video Coding for Generic Audiovisual Services, Version 3, ITU-T Rec. & ISO/IEC 14496-10 AVC, 2005. [3] T. Wiegand, G. J. Sullivan, G. Bjntegaard, and A. Lu-thra, Overview of the H.264/AVC video coding standard, IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 7, pp. 560560, Jul. 2003. [4] G. Sullivan and T. Wiegand, Video compression

From concepts to the H.264/AVC standard, Proc. IEEE,

Special Issue on Advances in Video Coding and

Delivery, vol. 93, no. 1, p. 18, Jan. 2005.

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Enhanced Grid Synchronization of a DG system

based on Positive Sequence Estimation and Current

Control

S.Manoharan Dr.K.Gnanambal R.Girija

Department of EEE, Department of EEE, Department of EEE,

K.L.N College of Engineering, K.L.N College of Engineering, K.L.N College of Engineering,

Madurai,Tamil Nadu, India Madurai,Tamil Nadu, India Madurai,Tamil Nadu, India

[email protected] [email protected]

AbstractDistributed Generation (DG) System is a small scale electric power generation which encompasses a wide

range of technologies such as wind energy, fuel cell, solar

power, micro turbines etc. Grid synchronization has been

identified as the most significant barrier to the control of

inverters connected to the grid. A Wind turbine based on

direct drive permanent magnet synchronous generator

(PMSG) is connected to the grid. The proper operation of grid

connected inverter system is determined by grid voltage

conditions such as phase, amplitude and frequency. A phase-

locked loop (PLL) is used to track the phase angle in order to

improve the synchronization systems response in adverse grid

conditions. Using the enhanced synchronization structure the

fundamental positive-sequence component of grid voltages in

asymmetric and distorted three-phase systems is estimated.

The - stationary frame is used to obtain the pulsation for grid inverter using a space vector pulse width modulation

(SVPWM) technique. The performance of the proposed

structure is verified through simulations using a grid set of

ideal and non-ideal grid conditions (three-phase voltage

unbalance, variation in frequency, variation in amplitude and

phase shift).The simulation results demonstrates that the

proposed method is very effective in digital structure

synchronization .

KeywordsDistributed Generation (DG), permanent magnet

synchronous generator (PMSG), discrete phase-locked loop (PLL),

synchronization systems, positive-sequence component, SVPWM,

non-ideal grid conditions.

I. INTRODUCTION

The Distributed Generation (DG) systems are highly

sporadic power generation system and their power output

depends heavily on the natural conditions. Wind power

generation based on direct drive permanent magnet

synchronous generator has received much attention due to its

self excitation capability and high efficiency operation [1].

Various grid code requirements must be met to connect the

DG systems with the utility grid. To ensure safe and reliable

operation of power system based on DG system [2], usually

power plant operators should satisfy the grid code

requirements such as fault ride through, power quality

improvement, grid synchronization, grid stability and power

control etc.

The grid synchronization techniques can be adversely

affected by the application of a disturbing influence (influence

quantity) on the electrical input signals. Due to the increase in

number of Distributed Generation (DG) Systems has lead to

complexity in control while integrating into grid. As a result

requirements of grid connected inverters have become stricter

to meet very high power quality standards.

Grid voltage conditions such as phase, amplitude and

frequency determine the proper operation of a grid connected

system. In such applications, a fast and accurate detection of

the phase angle, frequency and amplitude of the grid voltage is

essential. These factors, together with the implementation

simplicity and the cost are all important when examining the

credibility of a synchronization scheme. Therefore an ideal

phase-detection scheme must be used to promptly and

smoothly track the grid phase through various short-term

disturbances [3] [4] and long term disturbances to set the

energy transfer between the grid and the power converter.

One of the earliest methods used for tracking the phase

angle is Zero Crossing Detector (ZCD) method [5], but the

performance of ZCD is badly affected by power quality

phenomena [6]. The Linear PLL is mainly used to detect phase

for single phase supply. Use of voltage controlled oscillators

(VCOs) resulted in more rigid controllers such as the Phase

Locked Oscillator systems and the Charge-Pump PLLs.

However with the development of discrete devices such as

microcontrollers, various high performance synchronization

methods have been introduced.

The most recently proposed technique that can be used for

grid synchronization is the phase-locked loop (PLL); it is a

control system that generates an output signal whose phase is

related to the phase of an input "reference" signal [7].Some

significant applications are active power filters [8] [9],

uninterruptible power supplies [10], power-factor control [11],

[12], distributed power generation [13] and flexible ac

transmission systems [14]. Synchronous reference framephase-locked loops (SRF-s) are the most widely used systems

for synchronizing signals [15].

A fast and accurate estimation of fundamental positive-

sequence component [16] of grid voltage is essential for

different applications involving FACTS, power devices and

grid connected power converters. It is essential to estimate for

both monitoring and control in order to satisfy grid codes, and

to obtain high performance response.

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This paper proposes an enhanced synchronization structure based on PLL and fundamental positive-sequence components which is used to synchronize the component of grid voltages in three-phase systems that can include distorted and asymmetric voltage terms. Finally, the performances of the digital synchronization structure are investigated in the presence of both ideal and non-ideal grid conditions such as amplitude variation, frequency variation, phase jump and improper phase shift. The analysis is carried out in MATLAB/SIMULINK environment and the obtained results are discussed for effectiveness of the study.

II. OVERVIEW OF PROPOSED SYSTEM

A. Wind Turbine based DG

The PMSG-based wind turbine is fed to an ac-dc-ac

converter so as to maintain the ac output voltage at specified

frequency and amplitude. One of the main challenges is to

provide inverter control to present the customers with

balanced supply voltage. The wind speed is maintained

constant so as to keep the modulation index 1 in the load side

inverter.

B. Synchronous reference frame based PLL

A phase-locked loop is a control system that generates an

output signal whose phase is related to the phase of an input

"reference" signal [6]. Frequency is the time derivative of

phase. Keeping both the input and output phase in lock step

implies keeping the input and output frequencies in lock step.

Consequently it can track an input frequency or it can generate

a frequency that is a multiple of the input frequency. At present Synchronous Reference Frame PLL (SRF-PLL)

is the one of the most employed PLL topology. If the single-

phase voltage input V, is an internally generated signal that is a 90 degrees shifted version of V .The transformation blocks changes the reference frame, bringing the voltages system

from an - stationary reference frame to a d-q rotating synchronous reference frame.

The feedback loop controls the angular position of this d-q

reference frame. In particular the utility voltage vector is

totally lined up to the q-axis. In this way it coincides with all

its q-component; consequently the d-component is made equal

to zero. The q-component describes the voltage vector

amplitude course.

After studying the various Phase Locked Loop schemes

used today in modern power system, we observe that the

Synchronous Reference Frame PLL method provides a simple

yet effective way to measure the phase angle. In case of a

single phase system we obtain the quadrature signal by

delaying the available sinusoid or adopting some other similar

structure, however in 3 phase system this problem is greatly

reduced due to the availability of three phase shifted signals.

Hence by using arithmetic manipulation we obtain the

required orthogonal signal necessary for SRF-PLL

implementation.

C. Current control with PI Regulator:

The PI controller is a linear controller and one of the most

common controllers used in control system. It is based on the

principal of control loop feedback. The error of the measured

and reference output signal is the function of the control

response which will produce an output until it matches the

value of reference. There are two actions to be performed

namely proportional and integral action in the controller. The

proportional term control action is to simply proportional to

the control error. The proportional term output is given by

multiplying the error by a constant Kp(0.08) which is called

the proportional gain constant. The integral term objective in

PI controller is to eliminate control error in steady state. It

calculates and accumulates a continuous sum of the error

signal. The accumulated error is then multiplied by constant

Ki(200) which is called the integral gain constant and gives

the integral control output.

D. Space vector pulse width modulation:

It is used for the control of pulse width modulation. To

implement space vector modulation a reference signal is

sampled with fundamental frequency. The reference signal

needed is generated from the Clarke transformation from three

phase voltage source.

Fig. 1. Synchronization sytem structure

III. PROBLEM FORMULATION

The operation of the proposed synchronized structure is

implemented by considering three phase supply voltage source

Va, Vb and Vc. In order to track the phase angle a discrete

three phase PLL is used. It controls the internal voltage

source. The output consists of estimated phase synchronous

angle and (sin , cos ) for the dq transformation blocks. In steady state sin will be in phase with the fundamental positive sequence of the -component. The PLL also measures the frequency and generates a signal t locked on the variable frequency of system voltage. The sin , cos values estimated using the PLL are used to obtain d, q and zero components

using Park transformation.

))3/2sin()3/2sin(sin(3/2 tItItII cbad

(1)

))3/2cos()3/2cos(cos(3/2 tItItIIq cba

(2)

)(3/10 cba IIII (3)

The current control is usually performed in a d-q synchronous

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reference frame. A distortion free, balanced, constant magnitude three-phase voltage has d components only, while the q and 0 components will be zero. Hence a reference current for Iq is set zero. The controller gains calculated for the PI regulator are Kp=0.08 and Ki=200. The output obtained is again converted into Iabc using Park transformation. The dq0_to_abc Transformation is commonly used in three-phase electric machine models. It transforms three quantities such as direct axis, quadratic axis and zero-sequence components. It is also expressed in a two-axis reference frame back to phase quantities. The following transformation is used:

0)cos()sin( ItItII qda (4)

0)3

2cos()

3

2sin( ItItII qdb

(5)

0)3

2cos()

3

2sin( ItItII qdc

(6)

Fig. 2. Simulation model for positive sequence estimation and current control.

A SVPWM is used to obtain the pulsation for the DC-AC

inverter with U and U as the reference signal obtained by using Clark transformation.

)5.05.0(*3/2 VcVbVaU (7)

)*2/3*2/3(*3/2 VcVbU (8)

IV. RESULT AND DISCUSSION

To verify the effectiveness of the proposed synchronization

system structure, some significant cases have been simulated

are performed using Matlab-Simulink software.

The main objective is to estimate the fundamental positive-

sequence component from the three phase supply voltages

which contains distortion asymmetries. The fundamental grid

frequency is 50 Hz and the sampling frequency used is 5 kHz. 1) Case test-1: The proposed structure is initially tested

with ideal condition without considering any distortion. The

grid positive sequence amplitude is set as 380V.

2) Case test-2: A three-phase voltage unbalance is applied

with a voltage reduction of 50V in each phase.

3) Case test-3: A three-phase frequency unbalance is

produced by a variation of 5Hz from the fundamental grid

frequency of 50Hz.

4) Case test-4: The amplitude is varied by 50V in phase-A

of the grid supply voltage.

Case test-5: Improper phase-shift is produced by having

constant frequency but not the proper phase shift of 120

relative to each other. A phase shift of 5 variation is applied

to the balanced three phase voltage. If you have an odd

number of affiliations, the final affiliation will be centered on

the page; all previous will be in two columns.

Fig. 3. Simulated results for PLL output, grid voltage and current.

Fig. 4. Simulated results for current control.

Waveforms presented in Figs. 5-9 show the simulated

output for the cases described. All of the cases first include

(top plot) the V and V that corresponds to the grid voltages in the - frame. The central plots show the fundamental positive sequence grid voltages V+ and V+ in the - frame. The bottom plots show the phase angle of the

fundamental positive sequence of grid voltages.

Fig. 5. Simulated result for case 1 (ideal condition).

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Fig. 6. Simulated results for case 2 (Three phase voltage unbalance).

Fig. 7. Simulated results for case 3 (Three phase frequency unbalance).

Fig. 8. Simulated results for case 4(voltage unbalance).

Fig. 9. Simulated results for case 5(Improper phase shift).

Different non-ideal conditions were simulated and most were handled well by the system. Unbalances in the three phase input signals were overall handled well by the system. The estimation of fundamental positive sequence component and phase angle tracking was performed well by the system. Although the system could handle the non-ideal cases fairly well it was sometimes slow.

V. CONCLUSION

A PLL can be used to obtain magnitude, frequency and

phase information for estimation of fundamental positive-

sequence component of grid voltage. Accurate and fast

estimation of these quantities can be used for control and

protection of the system. Overall the wind turbine integrated

grid synchronization system based on positive-sequence

estimation is able to handle non-ideal conditions well. The

positive-sequence phase angle is tracked within acceptable

margins and therefore the PLL system as given with the

positive sequence estimation could indeed operate in a real life

application.

ACKNOWLEDGMENT

The authors are grateful to the principal and management of K.L.N college of Engineering, Sivagangai for providing all facilities for the research work

REFERENCES

[1] C.N. Bhende, S.Mishra and Siva Ganesh Malla, Permanent magnet synchronous generator-based standalone wind energy supply system, IEEE Transactions on Sustainable Energy, vol. 2, no. 4, October 2011.

[2] F. Blaabjerg, R. Teodorescu, M. Liserre, and A. V. Timbus, Overview of control and grid synchronization for distributed power generation systems, IEEE Trans. Ind. Electron., vol. 53,no. 5, pp. 1398-1409,Oct. 2006.

[3] J. Svensson, Synchronisation methods for grid-connected voltage source converters, Proc. Inst. Elect. Eng., vol. 148, no.3, pp.229-235,May 2001.

[4] M. Karimi-Ghartemani and M. Iravani, A method for synchronization of power electronic converters in polluted and variable-frequency environments,IEEE Trans. Power syst., vol.19, no. 3,pp. 1263-1270, Aug.2004.

[5] F. M. Gardner, Phase Lock Techniques. New York:Wiley, 1979.

[6] Francisco D. Freijedo, Jesus Doval-Gandoy, Oscar Lopez, Carlos Martinez-Penalver, Alejandro G. Yepes, Pablo Fernandez-Comesana, Andres Nogueiras, JanoMalvar, Nogueiras, Jorge Marcos and Alfonso Lago, Grid-synchronization methods for power converters, Proc. Of IEEE 35th Annual Conference on Industrial Electronics, IECON 2009, pp. 522-529.

[7] FANG Xiong, WANG Yue, LI Ming, WANG Ke and LEI Wanjun,A novel PLL for grid synchronization of power electronic converters in unbalanced and variable-frequency environment, Proc. of IEEE International Symposium on Power Electronics for Distributed Generation Systems: pp. 466-471, 2010.

[8] C. Lascu, L. Asiminoaei, I. Boldea, and F. Blaabjerg, High performance current controller for selective harmonic compensation in active power filters, IEEE Trans. Power Electron., vol. 22,no. 5,pp. 1826-1835,Sep. 2007.

[9] M. Routimo, M. Salo, and H. Tuusa, Comparison of voltage-source and current-source shunt active power filters, IEEE Trans. Power Electron.,vol. 22, no. 2,pp. 636-643, March 2007.

[10] J. M. Guerrero, L. Hang, and J. Uceda, Control of dis tributed uninterruptible power supply systems, IEEE Trans. Ind. Electron., vol. 55, no. 8,pp. 2845-2859, Aug. 2008.

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[11] A. I. Maswood and F. Liu, A unity-power-factor converter using the synchronous-reference-frame-based hysteresis current control, IEEE Trans. Ind. Appl., vol. 43,no. 2, pp. 593-599, Mar./Apr. 2007.

[12] B.Wang, G. Venkataramanan, and A. Bendre, Unity power factor control for three-phase three-level rectifiers without current sensors, IEEE Trans. Ind. Appl., vol. 43, no. 5,pp.1341-1348, Sep./Oct.2007.

[13] T. Ahmed, K. Nishida, and M. Nakaoka, A novel stand-alone induction generator system for AC and DC power applications, IEEE Trans. Ind Appl., vol. 43, no. 6, pp. 1465-1474, Nov./Dec.2007.

[14] H. Awad, J. Svensson, and M. J. Bollen, Tuning software phase-locked loop for series-connected converters, IEEE Trans. Power Del., vol. 20, no. 1,pp. 300-308, Jan.2005.

[15] A. Timbus, M. Liserre, R. Teodorescu, P. Rodriguez, and F. Blaabjerg, Evaluation of current controllers for distributed power generation systems, IEEE Trans. Power Electron., vol. 24,no. 3,pp. 654-664,Mar. 2009.

[16] Pedro Roncero-Sanchez, Xavie del Toro Garcia, Alfonso Parreno Torres, and Vinvente Feliu, Fundamental positive-and negative-sequence estimator for grid synchronization under highly disturbed operating coditions, IEEE Trans. Power Electronics., vol. 28, no.8, August. 2013.

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Reduction of Lower Order Harmonics in a Grid-

connected Single-phase PV Inverter Using Adaptive

Harmonic Compensation Technique

#1

Ananda Raj. A.J

Final Year Student,Department of EEE,

Valliammai Engineering College,

Chennai, India

[email protected]

#2Pratheebha. J,

Assistant Professor,Department of EEE,

Valliammai Engineering College,

Chennai, India

[email protected]

Abstract This paper proposes a novel inverter current control method to mitigate lower order harmonics in a single-phase grid-

connected photovoltaic (PV) inverter. The circuit under

consideration is composed of a PV array, a boost section, a single-

phase inverter with an inductive filter and a step-up transformer

interfacing the grid or the load. The lower order harmonics,

which may be caused by non-ideal factors such as distorted

magnetizing current in transformer due to core saturation, dead

time of inverter, on-state voltage drops in switching etc., need to

be eliminated in order for the PV inverter to meet IEEE

standards. An inverter current control technique, wherein a

modification to the conventional PR controller (proportional-

resonant controller) is done is put forward. This novel controller,

named as proportional-resonant-integral (PRI) controller,

eliminates the dc component in the control system, which

introduces even harmonics in the grid current. An adaptive

harmonic compensation technique, which makes use of an LMS

adaptive filter to eliminate a particular harmonic component in

the output current, is proposed for the lower order harmonic

compensation. The complete design has been validated with

simulation results and the THD of the output voltage/ current

waveforms has been found to be in conformance with the IEEE

standards.

Keywordsodd and even harmonics, MPPT algorithm, boost converter, PRI controller, THD

I. INTRODUCTION

In recent years, distributed generation (DG) systems have

started making use of renewable energy sources owing to the

depletion of conventional energy sources. Distributed

generation allows collection of energy from many sources and

may give lower environmental impacts and improved security

of supply. In this paper, a system utilizing solar energy as the

source and a photo-voltaic inverter to supply the power

generated to the grid is elucidated. The topology of the solar

inverter system[1]

consists of the following three power circuit

stages:

1) a boost converter stage to perform maximum power

point tracking (MPPT)

2) a low-voltage 2-bridge VSI inverter

3) an inductive filter and an RL load

The objective of the paper is to mitigate the lower order

harmonics in this system. The system will not have any lower

order harmonics in the ideal case. However, harmonics are

generated due to the following aspects: distorted magnetizing

current drawn by the transformer due to the nonlinearity in the

BH curve of the transformer core, the dead time introduced between switching of devices, on-state voltage drops on the

switches, distortion in the grid voltage etc.

Harmonics have a negative impact on distribution networks

and influence the behaviour of system components and loads:

For example, conductors suffer from losses and skin effects,

eddy current losses can have detrimental effects on

transformers, with consequent equipment overheating,

capacitors may be affected by resonance phenomena with

potential breakdown, and machines can suffer from vibration

phenomena.

These harmonics need to be mitigated so that the PV

inverter meets standards such as IEEE 519-1992 and IEEE

1547-2003. This paper focuses on the design of an inverter

current control to achieve a good attenuation of the lower

order harmonics.

Fig.1: Schematic diagram of the circuit

Fig.1 shows the circuit block diagram of a single phase grid

connected PV inverter. The DC output from the solar array is

boosted using MPPT scheme. The goal of MPPT technique is

to automatically find the voltage VMPP or current IMPP at which

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a PV array should operate to obtain the maximum power

output PMPP under a given temperature and irradiance. The

boost converter stage employs duty ratio control during

MPPT.

Fig. 2 Power Circuit Topology of single-phase PV System

Fig.2 shows the power circuit topology of a single-phase

PV inverter connected to a grid. The controller employed here

is a PRI (proportional-resonant-integral) controller. This is a

modification to the conventional PR (proportional-resonant)

controller wherein any dc offset in a control loop will

propagate through the system and results in drawing of even

harmonics from the grid. Thus, an integral block is used along

with the PR controller to ensure that there is no dc in the

output current of the inverter. This would automatically

eliminate the even harmonics. The complete scheme is

verified experimentally and the results show a good

correspondence with the analysis.

The organization of this paper is as follows: Section II

discusses the sources of lower order harmonics in the system.

Section III explains the MPPT algorithm used, Section IV

about the design of fundamental current control using a PRI

controller. In Section V, design of the system using MATLAB

and the simulation results are elucidated. In Section VI, the

hardware details are provided. Conclusions are given in

Section VII.

II. LOWER ORDER HARMONICS

A. Harmonics

Harmonics are electric voltages and currents that appear

on the electric power system as a result of non-linear electric

loads. When a non-linear load is connected to the system, it

draws a current that is not sinusoidal. These result in

distortions, termed as harmonics. Harmonic frequencies in the

power grid are a frequent cause of power quality problems.

Some of the major effects of power system harmonics are:

increases the current in the system.

causes poor power factor

transformer and distribution equipment overheating

sensitive equipment failure

B. Lower order harmonics

Harmonics are steady-state distortions to current and

voltage waves and repeat every 50 hertz or 60 hertz cycle.

They occur as integral multiples of the fundamental frequency.

As the frequency increases, the magnitude decreases

gradually, thus making the lower order harmonics the most

predominant and harmful.

For instance, the third harmonic causes a sharp increase

in the zero sequence current, and therefore increases the

current in the neutral conductor. This effect can require special

consideration in the design of an electric system to serve non-

linear loads.

The origin of odd and even harmonics is discussed below:

1) Odd Harmonics: The following are the primary causes for

the lower order odd harmonics:

Distorted magnetizing current drawn by the transformer due to the nonlinear characteristics of the

BH curve of the core

Inverter dead time[2] (proportional to the dead time, switching frequency, and the dc bus voltage)

Semiconductor device voltage drops

Distortion in the grid voltage

Voltage ripple in the dc bus

2) Even Harmonics: The system is susceptible to the presence

of dc offset in the inverter terminal voltage. The dc offset is

caused by one or more of the following factors:

Varying power reference given by a fast MPPT block

Offsets in the A/D converter and the sensors.

C.Evaluation of harmonics:

Harmonics can be quantified using the Fourier series. It

provides a mathematical analysis of distortions to a current or

voltage waveform. Based on Fourier series, harmonics can

describe any periodic wave as summation of simple sinusoidal

waves which are integer multiples of the fundamental

frequency.

The harmonic voltage amplitude for a hth harmonic can

be expressed as

where td is the dead time,

Ts is the device switching frequency, and

Vdc is the dc bus voltage

III. MPPT ALGORITHM

Maximum power point tracking (MPPT) is a technique

that grid connected inverters, solar battery chargers and

similar devices use to get the maximum possible power from

one or more photovoltaic devices, typically solar panels. Solar

cells have a complex relationship between solar irradiation,

temperature and total resistance that produces a non-linear

output efficiency which can be analyzed based on the I-V

curve. It is the purpose of the MPPT system to sample the

output of the cells and apply the proper resistance (load) to

obtain maximum power for any given environmental

conditions. MPPT devices are typically integrated into

an electric power converter system that provides voltage or

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current conversion, filtering, and regulation for driving various

loads. Tracking the maximum power point (MPP) of a photovoltaic (PV) array is a crucial part of a PV system. Many

MPP tracking (MPPT) algorithms have been developed and

implemented. In this paper, the Perturb and Observe (P&O)

algorithm is made use of. That is, in this system, a PV array is

connected to a power converter. Thus, perturbing the duty

ratio of power converter perturbs the PV array current and

consequently perturbs the PV array voltage.

The graphical representation of the algorithm is shown in

Fig 3. It is clear from the graph that incrementing the voltage

increases the power when operating on the left of the MPP

(maximum power point) and decreases the power when on the

right of the MPP. Therefore, if there is an increase in power,

the subsequent perturbation should be maintained to reach the

MPP and if there is a decrease in power, the perturbation must

be reversed.

Fig. 3: P&O algorithm graphical representation

The process is repeated periodically until the MPP is

reached. The system then oscillates about the MPP. The

oscillation can be minimized by reducing the perturbation step

size.The block of MPPT used in the MATLAB simulink is

shown in Fig.4

Fig. 4: MPPT block in MATLAB

IV. DESIGN OF PRI CONTROLLER

This controller uses three blocks- a proportional controller,

a resonant controller and an integral controller.

A proportional control system is a type of

linear feedback control system. In the proportional control

algorithm, the controller output is proportional to the error

signal, which is the difference between the set point and

the process variable. In other words, the output of a

proportional controller is the multiplication product of the

error signal and the proportional gain.

The addition of a resonant block results in a PR controller.

For low order harmonic compensation, PR controllers are

good alternatives to PI(proportional-integral) controller,

especially in grid-connected distributed generation systems.

PR filters can be used for generating the harmonic command

reference precisely in an active power filter and for

implementing selective harmonic compensation.

Yet another development has been made in the controller

by the inclusion of an integral block. If the main controller

used is a PR controller, any dc offset in a control loop will

circulate through the system and the inverter terminal voltage

will have a nonzero average value. The integral block ensures

that there is no dc in the output current and eliminates the even

harmonics.

Fig.5: Block diagram of the fundamental current

control with the PRI controller.

The transfer function of the PR controller is:

The plant transfer function is formed as

where Vdc is the gain of inverter to the voltage reference

generated by the controller impedance (Rs + sLs ) is the

impedance offered by the controller given in s-domain.

Rs and Ls are the net resistance and inductance referred to the

primary side of the transformer, respectively.

Ls includes the filter inductance and the leakage inductance of

the transformer.

Rs is the net series resistance due to the filter inductor and the

transformer.

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First, a PR controller is designed for the system assuming

that the integral block is absent, i.e., KI = 0. Design of a PR

controller is done by considering a PI controller in place of the

PR controller.

With the PI controller as the compensator block in Fig. 4 and

without integral block, the forward transfer function will be

The closed-loop transfer function for Fig. 4 is given by

Without the integral block, the closed-loop transfer function

would be

Now the plant transfer function is,

where M = Vdc/Rs and T=Ls/Rs

The model of PRI controller used in the simulation is

shown in Fig.6.A discrete virtual PLL controller is used in

addition to the PRI controller for the sinusoidal waveform.

Fig.6: PRI Controller block using MATLAB

V. SIMULATION RESULTS

TABLE I

PV INVERTER PARAMETERS

Parameter Meaning Value

Vdc DC bus voltage 40 V

1:n Transformer turns ratio 1:15

wbw Bandwidth of current

controller 84.8 X 103 rad/s

Rs Net series resistance referred

to primary 0.28

Ls Net series inductance referred

to primary 1.41 mH

S1-S4, Sboost Power MOSFETs

IRF

Z44(VDS,max=60V,

ID,max=50A)

Cdc DC bus capacitance 6600 F, 63V

fsw Device switching frequency 40 kHz

Kp Proportional term 3

Kr Resonant term 594

KI Integral term 100

Kadapt Gain in harmonic

compensation block 25.6

Ta Time constant 0.03s

The circuit topology was built in laboratory for a max

power rating of 150W. The various power circuit and control

circuit parameters are listed in Table II. All the design related

plots and the simulation result have the parameters as listed in

Table II.

Fig.7. shows the grid connected single-phase PV inverter

using MATLAB Simulink

Fig.7. Grid connected single-phase PV Inverter

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From the simulation the output voltage waveform from

the solar panel is shown in Fig.8.And by implementing the

Maximum Power Point Tracking Techinque the output voltage

from the inverter is boosted to the maximum voltage and is

shown in Fig.9.

Fig.8. PV voltage with the load .This is the dc output

voltage from the solar panel.

Fig 9. Boosted output DC voltage waveform.

This boosted (i.e.,) Maximum power is passed to the filter

to remove the harmonic content. Harmonic of high frequency

will be eliminated using the filter. The ac voltage from the

transformer is shown in Fig.10.The r.m.s voltage of the output

voltage is 230V .is connected to the grid.This voltage is free

from lower order harmonics.

Fig.10. AC output voltage with the load connected to

grid.

A. FFT Analysis with load

This is the fast fourier transform analysis for the

given circuit. Here it is seen that the harmonics value is

reduced and the THD is only 1.30%

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Fig. 11: FFT Analysis of output voltage.

The above Fig.11 shows the FFT analysis for the output

voltage waveform in the grid where the load is connected. The

Total Harmonic Distortion is found to be 1.30% for 5 cycles

and this is within the IEEE standard. Thus the quality of

power is improved and the lower order harmonics are reduced.

VI. HARDWARE DETAILS

A. Specifications

Transformer 230/15v step-down transformer

MOSFET switches IRF840 (400v, 5A)

Inductor 47microH, 10mH, 100microH

Capacitors 1000F, 2200 F, 10 F, 0.01 F

PN junction diodes 1N4007

Microcontroller dsPIC33FJ64MC802

Voltage sensors 15v/5v (potential divider type)

Current sensors ACS714(hall effect sensor)

MOSFET driver&

Optocoupler IRS2110

B. Hardware snapshots

The hardware setup of a single-phase PV inverter

connected to RL load is shown in Fig. 12. The MOSFET

IRF840 of voltage rating 400V and current rating 5A is taken.

Peripheral Integral Controller of 33FJ64 family is used. In the

driver circuit, IRS2110 has been used. The value of the

resistance is 50 Ohm and inductor 1 mH respectively. The

output voltage across the load RL is shown in Fig. 13.

Fig 12. Hardware setup

Fig 13. Output Voltage waveform

VII. CONCLUSION

Modification to the inverter current control for a grid

connected single-phase photovoltaic inverter has been

proposed in this paper, for ensuring high quality of the current

injected into the grid. For the power circuit topology

considered, the dominant causes for lower order harmonic

injection are identified as the distorted transformer

magnetizing current and the dead time of the inverter. It is also

shown that the presence of dc offset in control loop results in

even harmonics in the injected current for this topology due to

the dc biasing of the transformer. A novel solution is proposed

to attenuate all the dominant lower order harmonics in the

system. The estimated current is converted into an equivalent

voltage reference using a proportional controller and added to

the inverter voltage reference. The design of the gain of a

proportional controller to have an adequate harmonic

compensation has been explained. To avoid dc biasing of the

transformer, a novel PRI controller has been proposed and its

design has been presented. The interaction between the PRI

controller and the adaptive compensation scheme has been

studied.

It is shown that there is minimal interaction between

the fundamental current controller and the methods

responsible for dc offset compensation and adaptive harmonic

compensation. The PRI controller and the adaptive

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compensation scheme together improve the quality of the

current injected into the grid. The complete current control

scheme consisting of the adaptive harmonic compensation and

the PRI controller has been verified experimentally and the

results show good improvement in the grid current THD once

the proposed current control is applied.

The transient response of the whole system is studied

by considering the startup transient and the overall

performance is found to agree with the theoretical analysis. It

may be noted here that these methods can be used for other

applications that use a line interconnection transformer

wherein the lower order harmonics have considerable

magnitude and need to be attenuated.

REFERENCES

[1] S. B. Kjaer, J. K. Pedersen, and F. Blaabjerg, A review of single-phase grid-connected inverters for photovoltaic

modules, IEEE Trans. Ind. Appl., vol. 41, no. 5, pp. 12921306, Sep./Oct. 2005.

[2] S.-G. Jeung and M.-H. Park, The analysis and compensation of deadtime effects in PWM inverters, IEEE Trans. Ind. Electron., vol. 38, no. 2, pp. 108114, Apr. 1991. [3] J.-W. Choi and S.-K. Sul, A new compensation strategy reducing voltage/current distortion in PWM VSI systems

operating with low output voltages, IEEE Trans. Ind. Appl., vol. 31, no. 5, pp. 10011008, Sep./Oct. 1995. [4] A. R.Munoz and T. A. Lipo, On-line dead-time compensation technique for open-loop PWM-VSI drives, IEEE Trans. Power Electron., vol. 14, no. 4, pp. 683689, Jul. 1999.

[5] A. C. Oliveira, C. B. Jacobina, and A. M. N. Lima,

Improved dead-time compensation for sinusoidal PWM inverters operating at high switching frequencies, IEEE Trans. Ind. Electron., vol. 54, no. 4, pp. 22952304, Aug. 2007.

[6] L. Chen and F. Z. Peng, Dead-time elimination for voltage source inverters,IEEE Trans. Power Electron., vol. 23, no. 2, pp. 574580, Mar. 2008. [7] IEEE Recommended Practices and Requirements for

Harmonic Control in Electrical Power Systems, IEEE

Standard 519-1992, 1992.

[8] IEEE Standard for Interconnecting Distributed Resources

With the Electric Power System, IEEE Standard 1547-2003,

2003.

[9] T. Esram and P. L. Chapman, Comparison of photovoltaic array maximum power point tracking techniques, IEEE Trans. Energy Convers., vol. 22, no. 2, pp. 439449, Jun. 2007.

[10] R. Kadri, J.-P. Gaubert, and G. Champenois, An improved maximum power point tracking for photovoltaic

grid-connected inverter based on voltage-oriented control, IEEE Trans. Ind. Electron., vol. 58, no. 1,pp. 6675, Jan. 2011.

[11] T. Kitano, M. Matsui, and D. Xu, Power sensorlessMPPT control scheme utilizing power balance at

DC linkSystem design to ensure stability and response, in Proc. 27th Annu. Conf. IEEE Ind. Electron. Soc., 2001, vol. 2,

pp. 13091314.

[12] Y. Chen and K. M. Smedley, A cost-effective single-stage inverter with maximum power point tracking, IEEE Trans. Power Electron., vol. 19, no. 5, pp. 12891294, Jun. 2004.

[13] Q. Mei, M. Shan, L. Liu, and J. M. Guerrero, A novel improved variable step-size incremental-resistance MPPT

method for PV systems, IEEE Trans. Ind. Electron., vol. [14] A. K. Abdelsalam, A. M. Massoud, S. Ahmed, and P. N.

Enjeti, High-performance adaptive perturb and observe MPPT technique for photovoltaic-based microgrids, IEEE Trans. Power Electron., vol. 26, no. 4, pp. 10101021, Apr. 2011.

[15] P. Mattavelli, A closed-loop selective harmonic compensation for active filters, IEEE Trans. Ind. Appl., vol. 37, no. 1, pp. 8189, Jan./Feb. 2001. [16] X. Yuan, W. Merk, H. Stemmler, and J. Allmeling,

Stationary-frame generalized integrators for current control of active power filters with zero steady-state error for current

harmonics of concern under unbalanced and distorted

operating conditions, IEEE Trans. Ind. Appl., vol. 38, no. 2, pp. 523532, Mar./Apr. 2002. [17] J. Allmeling, A control structure for fast harmonics compensation in active filters, IEEE Trans. Power Electron., vol. 19, no. 2, pp. 508514, Mar. 2004. [18] C. Lascu, L. Asiminoaei, I. Boldea, and F. Blaabjerg,

High performance current controller for selective harmonic compensation in active power filters, IEEE Trans. Power Electron., vol. 22, no. 5, pp. 18261835, Sep. 2007. [19] D. De and V. Ramanarayanan, A proportional + multiresonant controller for three-phase four-wire high-

frequency link inverter, IEEE Trans. Power Electron., vol. 25, no. 4, pp. 899906, Apr. 2010. [20] R. Cardenas, C. Juri, R. Penna, P.Wheeler, and J. Clare, The application of resonant controllers to four-leg matrix converters feeding unbalanced or nonlinear loads, IEEE Trans. Power Electron., vol. 27, no. 3, pp. 1120 1128, Mar. 2012.

[21] A. G. Yepes, F. D. Freijedo, O . Lopez, and J. Doval-

Gandoy, Highperformance digital resonant controllers implemented with two integrators, IEEE Trans. Power Electron., vol. 26, no. 2, pp. 563576, Feb.2011. [22] A. G. Yepes, F. D. Freijedo, J. Doval-Gandoy, O. Lopez,

J. Malvar, and P. Fernandez-Comesana, Effects of discretization methods on the performance of resonant

controllers, IEEE Trans. Power Electron., vol. 25, no. 7, pp. 16921712, Jul. 2010. [23] P. Mattavelli and F. P.Marafao, Repetitive-based control for selective harmonic compensation in active power filters, IEEE Trans. Ind. Electron., vol. 51, no. 5, pp. 10181024, Oct. 2004.

[24] R. Costa-Costello, R. Grino, and E. Fossas, Odd-harmonic digital repetitive control of a single-phase current

active filter, IEEE Trans. Power Electron., vol. 19, no. 4, pp. 10601068, Jul. 2004. [25] S. Jiang, D. Cao, Y. Li, J. Liu, and F. Z. Peng, Low-THD, fast-transient, and cost-effective synchronous-frame

repetitive controller for three-phase UPS inverters, IEEE Trans. Power Electron., vol. 27, no. 6, pp. 29943005, Jun. 2012.

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Rapid Tracking of MPPT with Buck-Boost

Converter #1

Subash.T,

#Department of EEE, Paavai Engineering College,

Namakkal, Tamilnadu,India [email protected]

#2Thinesh.S,

#Department of EEE, Paavai Engineering College,

Namakkal, Tamilnadu,India

Abstract The power obtained from the sun through the solar

panel is the research work performed in this paper, to extract the

power effectively i.e up to the benchmark of the solar panel

capacity, the effective maximum power point technique (MPPT)

needs to be implemented. there are three types of algorithms

available they are Po, Incremental conductance algorithm . In

this proposed work, a combination of linear approximation and PO Algorithm to achieve maximum-power-point tracking (MPPT)

for PV arrays is proposed. The LA is based on that the

trajectories of maximum power point varying with temperature

are approximately linear. With theLA a maximum power point

can be determined very closer. Moreover,. In the paper a

corresponding LA is made by coding in the panel design which is

simple. As a result, the proposed circuit is cost-effective and can

be with PV arrays easily. Therefore the fluctuations in the steady

state can be minimized .And by using Buck-Boost converter the

voltage has been maintained in the desired level, by having both

combination of step-up and step-down process. The proposed

MPPT method has advantages of faster tracking fewer fluctuation

and higher accuracy over the conventional methods.

Key words:PVarray,MPPT, LA, Buck-Boost Converter, Mosfet

I. INTRODUCTION

Photovoltaic is the technology that uses solar cells or an array

of them to convert solar energy directly into electricity .The

power produced by the array of depends directly from the

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