2014
3
9
9
0
Optimal Controller for Single Phase Island Photovoltaic Systems
2
2
Increasing of word demand load caused a new Distributed Generation (DG) to enter to powersystem. One of the most renewable energy is the Photovoltaic System. It is beneficial to use thissystem in both separately as well as connected to power system using power electronics interface.In this paper an optimal PID controller for Photovoltaic System systems has been developed. Theoptimization technique is applied to PID optimal controller in order to control the voltage ofPhotovoltaic System against load variation, is presents. Nonlinear characteristics of loadvariations as plant input, Photovoltaic System operational behavior demand for high qualityoptimal controller to ensure both stability and safe performance. Thus, Honey Bee MatingOptimization (HBMO) is used for optimal tuning of PID coefficients in order to enhance closedloop system performance. In order to use this algorithm, at first, problem is written as anoptimization problem which includes the objective function and constraints, and then to achievethe most desirable controller, HBMO algorithm is applied to solve the problem. In this study, theproposed controller is applied to the closed loop photovoltaic system behavior. Simulation resultsare done for various loads in time domain, and the results show the efficiency of the proposedcontroller in contrast to the previous controllers.
1

1
11


Mohammad Esmaeil
akbar
Iran
makbari@iauahar.ac.ir


Noradin
Ghadimi
Iran
noradin.1364@gmail.com
Photovoltaic System HBMO Optimal Controller PID Controller
[[1] Jiayi H, Chuanwen J, Rong X. A review##on distributed energy resources and##MicroGrid. Renewable and Sustainable##Energy Reviews 2008; 12: 2472–2483##[2] Nikkhajoei H, Iravani R.SteadyState##Model and Power Flow Analysis of##ElectronicallyCoupled Distributed##Resource Units. IEEE Trans. Power Del##2007; 22(1):721728. ##[3] Sao CK, Lehn PW.Control and Power##Management of Converter Fed##Microgrids. IEEE Trans. Power Systems##2008;23(3):10881098.##[4] Chen CL et al. Design of Parallel##Inverters for Smooth Mode Transfer##Microgrid Applications. IEEE Trans.##Power Electron 2010;25(1):615.##[5] Karimi H, Nikkhajoei H, Iravani R.##Control of an ElectronicallyCoupled##Distributed Resource Unit Subsequent##to an Islanding Event. IEEE Trans.##Power Del 2008;23(1):493501.##[6] Katiraei F, Iravani MR, Lehn PW.##MicroGrid Autonomous Operation##During and Subsequent to Islanding##Process. IEEE Trans. Power Del##2005;20(1):248257.##[7] Katiraei F, Iravani MR. Power##Management Strategies for a Microgrid##with Multiple Distributed Generation##Units. IEEE Trans. Power Systems##2006; 21(4):18211831.##[8] Katiraei F, Iravani MR and Lehn PW.##Smallsignal dynamic model of a microgrid##including conventional and##electronically interfaced distributed##resources. IET Gener. Transm. Distrib##2007; 1(3): 369–378.##[9] Cheng PT, Chen CA, Lee TL and Kuo##SY. A Cooperative Imbalance##Compensation Method for Distributed##Generation Interface Converters. IEEE##Trans. Ind. Appl 2009;45(2):805815##[10] Yannis M, Magdalene M, Georgios D##(2011). “Honey bees mating##optimization algorithm for the Euclidean##traveling salesman problem,” Infor. Sci.##181(20):4684–4698##[11] Niknam T (2011). An efficient multiobjective##HBMO algorithm for##distribution feeder reconfiguration.##Expert Syst. Appl. 38(3):2878–2887##[12] Noradin Ghadimi. PI Controller Design##for Photovoltaic Systems in Islanding##Mode Operation. World Applied##Sciences Journal 15 (3): 326330, 2011##]
Digital Watermarking Technology in Different Domains
2
2
Due to high speed computer networks, the use of digitally formatted data has increased many folds.The digital data can be duplicated and edited with great ease which has led to a need for effectivecopyright protection tools. Digital Watermarking is a technology of embedding watermark withintellectual property rights into images, videos, audios and other multimedia data by a certainalgorithm .Digital watermarking is a wellknown technique used for copy rights protection ofmultimedia data. A number of watermarking techniques have been proposed in literature. DigitalWatermarking is the process that embeds data called a watermark into a multimedia object such thatwatermark can be detected or extracted later to make an assertion about the object. A variety oftechniques in different domains have been suggested by different authors to achieve above mentionedconflicting requirements. All the watermarking techniques are different from each other and are usedfor differing applications.
1

12
17


Maryam
Hamrahi
Iran
Watermarking
domain
DCT
DWT
[[1]W. Zhu, et al, ”Multiresolution##Watermarking for Images and Video”,##IEEE Tran. on Circuits & Systems for##Video Technology, Vol.9, No.4, June 1999,##pp.545550.##[2] Bassia P., Pitas I., and Nikolaidis 2001,##“Robust Audio Watermarking in Time##Domain”, IEEE Trans. On Multimedia,##Vol. 3, pp. 232241.##[3] Bender W., Gruhl D., Morimoto N. and Lu##A. 1996, “Techniques for Data Hiding”,##IBM Systems Journal, Vol. 35, No. 3&4,##pp. 313 335.##[4]J. T. Brassil, et al., ”Electronic Marking and##Identification Techniques to Discourage##Document Copying”, IEEE Journal on##Selected Areas in Communications, Vol.13,##No.8, Oct 1995, pp.14951504.##[5]C. Cachin, “An InformationTheoretic##Model for Steganography”, Proceedings of##Workshop on Information Hiding, MIT##Laboratory for Computer Science, May##[6]David Kahn, ”Codebreakers : Story of##Secret Writting”, Macmillan 1967.##[7]David Kahn, ”The History of##Steganography”, Proc. of First Int.##Workshop on Information Hiding,##Cambridge, UK, May30June1 1996,##Lecture notes in Computer Science,##Vol.1174, Ross Anderson(Ed.), pp.17.##[8]F.A.P.Petitcolas, et al., ”Information Hiding## A Survey”, Proceedings of the IEEE,##Vol.87, No.7, July 1999, pp.10621078##[9]R. B. Wolfgang and E. J. Delp, "A##watermark for digital images," Proceedings##of the IEEE International Conference on##Image Processing, Lausanne, Switzerland,##Sept. 1619, 1996, vol. 3, pp. 219222.##[10]Neha Singh and Arnab Nandi , Digital##Watermarking: mark this technology,##http://www.electronicsforu.com/efylinux/ef##yhome/cover/watermar.pdf.##[11]Navas. K A, Sreevidya S, Sasikumar M “A##benchmark for medical image##watermarking”, 14th International workshop##on systems, signals & image processing and##6th EURASIP Conference focused on##speech & image Processing, Multimedia##Communication and services IWSSIP2007##& ECSIPMCS2007, Maribor, Slovenia,##2730 June 2007, pp 249252.##[12]W.Zhu, et al, ”Multiresolution##Watermarking for Images and Video”, ##IEEE Tran. on Circuits & Systems for##Video Technology, Vol.9, No.4, June 1999,##pp.545550.##[13]C. Shoemaker, Hidden Bits: A Survey of##Techniques for Digital Watermarking,##http://www.vu.union.edu/~shoemakc/water##marking/watermarking.html#watermarkobject,##Virtual Union, 2002##[14]N.F. Johnson, S.C. Katezenbeisser, S.C.##Katzenbeisser et al., Eds. Northwood, “A##Survey of Steganographic Techniques” in##Information Techniques for Steganography##and Digital Watermarking, MA: Artec##House, Dec. 1999, pp 4375.##[15]Peter Meerwald and Andreas and Jakob##HaringerStr. , Uhl,A survey of Waveletdomain##Watermarking Algorithms,##Department of Scientific Computing##,University of Salzburg, JakobHaringer##Str. A5020 Salzburg, Austria##]
Load Frequency Control in Power Systems Using Improved Particle Swarm Optimization Algorithm
2
2
The purpose of load frequency control is to reduce transient oscillation frequencies than its nominal valueand achieve zero steadystate error for it.A common technique used in real applications is to use theproportional integral controller (PI). But this controller has a longer settling time and a lot of Extramutation in output response of system so it required that the parameters be adjusted as appropriate . In thispaper, we aim to design a system based on PI controllers using improved particle swarm optimizationalgorithm for load frequency control .Multipopulation approach and local search to improve theoptimization algorithms is used and displayed. That this approach will lead to accelerating the achievementof results, preventing entrapment in a local minimum, and get better system output compared with similarmethods.
1

18
26


Milad
Babakhani Qazijahan
Iran
babakhani.milad@yahoo.com
Load Frequency Control
proportional integral control
improved particle swarm optimization algorithm
FPGA Can be Implemented Using Advanced Encryption Standard Algorithm
2
2
This paper mainly focused on implementation of AES encryption and decryption standard AES128. All the transformations of both Encryption and Decryption are simulated using an iterativedesign approach in order to minimize the hardware consumption. This method can make it avery lowcomplex architecture, especially in saving the hardware resource in implementing theAES InverseSub Bytes module and Inverse Mix columns module. As the S box is implemented bylookuptable in this design, the chip area and power can still be optimized. The new MixColumn transformation improves the performance of the inverse cipher and also reduces thecomplexity of the system that supports the inverse cipher. As a result this transformation hasrelatively low relevant diffusion power .This allows for scaling of the architecture towardsvulnerable portable and costsensitive communications devices in consumer and militaryapplications.
1

27
33


Shahin
Shafei
Iran
shahin_shafei@yahoo.com
AES
Encryption
decryption
FPGA
[1]Daemen J., and Rijmen V, "The Design of##Rijndael: AESthe Advanced Encryption##Standard", SpringerVerlag , 2002##[2]FIPS 197, “Advanced Encryption Standard##(AES)”, November 26, 2001.##[3]Tessier, R., and Burleson, W.,##“Reconfigurable computing for digital signal##processing: a survey”, J.VLSI Signal Process,##2001, 28, (12), pp.727.##[4]Ahmad, N.; Hasan, R.; Jubadi, W.M;##“Design of AES SBox using combinational##logic optimization”, IEEE Symposium on##Industrial Electronics & Applications##(ISIEA), pp. 696699, 2010.##]
SlidingMode Control of the DCDC Ćuk Converter in Discontinuous Conduction Mode
2
2
In this paper, a novel approach for twoloop control of the DCDC Ćuk converter in discontinuousconduction mode is presented using a sliding mode controller. The proposed controller can regulatethe output of the converter in a wide range of input voltage and load resistance. Controllerparameters are selected using PSO algorithms. In order to verify the accuracy and efficiency of thedeveloped sliding mode controller, the proposed method is simulated in MATLAB/Simulink. It isshown that the developed controller has, the faster dynamic response compared with standardintegrated circuit (MIC38C425) based regulators.
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34
45
sliding mode controller
steadystate error
a doubleloop controller
inductor current sampling
Particle Swarm Optimization (PSO) and discontinuous conduction mode
[[1] C. S. and M. R.D., "A new optimum##topology switching DCtoDC converter,"##presented at the IEEE Power Electronics##Specialists Conference, California, 1977.##[2] H. El Fadil and F. Giri, "Robust nonlinear##adaptive control of multiphase##synchronous buck power converters,"##Control Engineering Practice, vol. 17, pp.##12451254, 11// 2009.##[3] M. Salimi, J. Soltani, G. A. Markadeh, and##N. R. Abjadi, "Adaptive nonlinear control##of the DCDC buck converters operating in##CCM and DCM," International##Transactions on Electrical Energy##Systems, vol. 23, pp. 1536–1547, Nov##2013 2013.##[4] R. Leyva, A. CidPastor, C. Alonso, I.##Queinnec, S. Tarbouriech, and L.##MartinezSalamero, "Passivitybased##integral control of a boost converter for##largesignal stability," Control Theory and##Applications, IEE Proceedings, vol. 153,##pp. 139146, 2006.##[5] J. Liu, W. Ming, and F. Gao, "A new##control strategy for improving performance##of boost DC/DC converter based on inputoutput##feedback linearization," in##Intelligent Control and Automation##(WCICA), 2010 8th World Congress on,##2010, pp. 24392444.##[6] M. J. Jafarian and J. Nazarzadeh, "Timeoptimal##slidingmode control for multiquadrant##buck converters," Power##Electronics, IET, vol. 4, pp. 143150,##[7] S. C. Tan, Y. M. Lai, M. K. H. Cheung,##and C. K. Tse, "On the practical design of##a sliding mode voltage controlled buck##converter," Power Electronics, IEEE##Transactions on, vol. 20, pp. 425437, Mar##2005 2005.##[8] R. Venkataramanan, Sliding Mode Control##of Power Converters: California Institute##of Technology., 1986.##[9] L. MartinezSalamero, A. CidPastor, R.##Giral, J. Calvente, and V. Utkin, "Why is##sliding mode control methodology needed##for power converters?," in Power##Electronics and Motion Control##Conference (EPE/PEMC), 2010 14th##International, 2010, pp. S925S931.##[10] Z. Chen, "Double loop control of buckboost##converters for wide range of load##resistance and reference voltage," Control##Theory & Applications, IET, vol. 6, pp.##900910, 2012.##[11] T. SiewChong, Y. M. Lai, C. K. Tse, and##M. K. H. Cheung, "Adaptive feedforward##and feedback control schemes for sliding##mode controlled power converters," Power##Electronics, IEEE Transactions on, vol. 21,##pp. 182192, 2006.##[12] H. J. SiraRamirez and M. Ilic, "A##geometric approach to the feedback control##of switch mode DCtoDC power##supplies," Circuits and Systems, IEEE##Transactions on, vol. 35, pp. 12911298,##[13] T. SiewChong, Y. M. Lai, and C. K. Tse,##"Indirect Sliding Mode Control of Power##Converters Via Double Integral Sliding##Surface," Power Electronics, IEEE##Transactions on, vol. 23, pp. 600611,##[14] S. C. Tan, Y. M. Lai, C. K. Tse, L.##MartinezSalamero, and W. ChiKin, "A##FastResponse SlidingMode Controller ##for BoostType Converters With a Wide##Range of Operating Conditions," Industrial##Electronics, IEEE Transactions on, vol. 54,##pp. 32763286, Dec 2007 2007.##[15] S. C. Tan, Y. M. Lai, C. K. Tse, and L.##MartinezSalamero, "Special family of##PWMbased slidingmode voltage##controllers for basic DCDC converters in##discontinuous conduction mode," Electric##Power Applications, IET, vol. 1, pp. 6474,##Jan 2007 2007.##[16] S. C. Tan and Y. M. Lai, "Constantfrequency##reducedstate sliding mode##current controller for Cuk converters,"##Power Electronics, IET, vol. 1, pp. 466##477, 2008.##[17] C. Zengshi, "PI and Sliding Mode Control##of a Cuk Converter," Power Electronics,##IEEE Transactions on, vol. 27, pp. 3695##3703, 2012.##[18] M. Veerachary, "Twoloop voltagemode##control of coupled inductor stepdown##buck converter," Electric Power##Applications, IEE Proceedings , vol. 152,##pp. 15161524, 2005.##[19] M. Seker and E. Zergeroglu, "A new##sliding mode controller for the DC to DC##flyback converter," in Automation Science##and Engineering (CASE), 2011 IEEE##Conference on, 2011, pp. 720724.##[20] J. Kennedy and R. Eberhart, "Particle##swarm optimization," 1995, pp. 1942##[21] H. Erdem and O. T. Altinoz,##"Implementation of PSObased fixed##frequency sliding mode controller for buck##converter," in Innovations in Intelligent##Systems and Applications (INISTA), 2011##International Symposium on, 2011, pp.##[22] M. Kheirmand, M. Mahdavian, M. B.##Poudeh, and S. Eshtehardiha, "Intelligent##modern controller on DCDC converter,"##in TENCON 2008  2008 IEEE Region 10##Conference, 2008, pp. 15.##]
Efficient ShortTerm Electricity Load Forecasting Using Recurrent Neural Networks
2
2
Short term load forecasting (STLF) plays an important role in the economic and reliable operation ofpower systems. Electric load demand has a complex profile with many multivariable and nonlineardependencies. In this study, recurrent neural network (RNN) architecture is presented for STLF. Theproposed model is capable of forecasting next 24hour load profile. The main feature in this networkis internal feedback to highlight the effect of past load data for efficient load forecasting results.Testing results on the three year demand profile shows higher performance with respect to commonfeed forward back propagation architecture.
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46
53
Short term load forecasting (STLF)
Recurrent neural network (RNN)
hourly load forecast
Load Data normalization
[[1] Eugene A. Feinberg and Dora Genethliou,##"Chapter 12 Load Forecasting" Weather##(2006), Issue: August, Publisher:##Springer, pp. 269285##[2] Milos Bozic, Milos Stojanovic and Zoran##Stajic, "Shortterm electric load##forecasting using least square support##vector machines" Facta Universitatis,##Series: Automatic Control and Robotics##Vol. 9, No 1, pp. 141150,2010##[3] R. C. Garcia, et al., “GARCH Forecasting##Model to Predict Dayahead Electricity##Prices,” IEEE Transactions on Power##Systems, Vol. 20, No. 2, May 2005, pp.##doi:10.1109/TPWRS.2005.846044##[4] M. Stevenson, “Filtering and Forecasting##Spot Electricity Prices in the Increasingly##Deregulated Australian Electricity##Market,” Quantitative Finance Research##Centre, University of Technology,##Sydney, 2001.##[5] N. Hubele, et al., “Identification of##Seasonal Shortterm Load Forecasting##Models Using Statistical Decision##Functions,” IEEE Transactions on Power##Systems, Vol. 5, No. 1, 1990, pp. 405.##doi:10.1109/59.49084##[6] M. ElHawary, et al, “ShortTerm Power##System Load Forecasting Using the##Iteratively Reweighted Least Squares##Algorithm,” Electrical Power Systems##Research, Vol. 19, 1990, pp. 1122.##doi:10.1016/03787796(90)900 03L##[7] V. S. Kodogiannis and E. M.##Anagnostakis, “A Study of Advanced##Learning Algorithms for Shortterm Load##Forecasting,” Engineering Applications##of Artificial Intelligence , Vol. 12, 1999,##pp. 159173. doi:10.1016/S0952##1976(98)000645##[8] G.C. Liao and T.P. Tsao, “Application##of Fuzzy Neural Networks and Artificial##Intelligence for Shortterm load##Forecasting,” Electrical Power Systems##Research, Vol. 70, 2004, pp. 237244.##doi:10.1016/j.epsr. 2003.12.012##[9] H. Yamin, M. Shahidehpour and Z. Li,##“Adaptive shortterm Price Forecasting ##using artificial Neural Networks in the##Restructured Power Markets,” Electrical##Power and Energy Systems, Vol. 26,##2004, pp. 571581.##doi:10.1016/j.ijepes.2004.04.005##[10] A. K. Topalli, I. Erkmen and I. Topalli,##“Intelligent Shortterm Load Forecasting##in Turkey,” Electrical Power and Energy##Systems, Vol. 28, 2006, pp. 437447. doi:##10.1016/j.ijepes.2006.02.004##[11] R.C.Bansal, “Overview and Literature##Survey of Artificial Neural Networks##Applications to Power Systems (1992##2004)”,IE Journal, Vol86, March, 2006.##[12] M.Tarafdar Haque, A.M.Kashtiban,##“Application of Neural Networks in##Power systems: A Review”, Proceedings##of world Academy of Science and##Technology, Vol 6, June 2006##[13] Zbigniew Gontarand Nikos##Hatziargyriou, “Short Term load##forecasting using Radial basis neural##network”, SM, IEEE2001 IEEE Porto##Power Tech Conference, September,##Porto, Portugal.##[14] J Donald. F. Specht, “Probabilistic neural##networks for classification mapping, or##associative memory”, Proc. IEEE Inf.##Conf. Neural Networks, San Diego, CA,##VOI. 1, pp. 525532, July 1988.##[15] P. Mandal, T. Senjyu, N. Urasaki and T.##Funabashi, “A Neural Network Based##SeveralHourAhead Electric Load##Forecasting using Similar Days##Approach,” Electrical Power and Energy##Systems, Vol. 28, 2006, pp. 367373.##doi:10.1016/j.ijepes.2005.12.007.##[16] Bodn, " A guide to recurrent neural##networks and back propagation", Report##from NUTEKsupported project AIS8:##Application of data analysis with learning##systems, 19992001, Holst, A.(ed), SICS##Technical Report T2002:3, SICS, Kista,##Sweden, 2002.##[17] L. Elman, Finding Structure in time,##Cognitive science, 14, pp.179211, 1990.##[18] Jordan, "Attractor Dynamics and##parallelism in a connectionist sequential##machine, In Proceedings of the Eighth##conference of the Cognitive Science##Society, pp.531546, 1986.##[19] ww.energyseec.com/downloadiranedatab##ank.asp. Last visited Jan. 2015##]