iosr-JEEE   Volume-9 ~ Issue-4 ~ July-August 2014

Abstract: In this paper, artificial neural network technique is implemented to predict weekend load. The performance of methodology is compared with the actual data received from a power station operating in northern region of India. This technique accurately forecast the hourly load for weekend days. Results obtained from training and testing of neural network confirms the validity of proposed methodology. In this approach demand sensitivity due to change in some weather variables such as temperature and humidity is also considered. The accuracy of proposed method is given in terms of Mean Absolute Percentage Error (MAPE).

1] S. Ramos, J. Soares, M. Silva, Z. Vale, Short-term Wind Forecasting for Energy Resources Scheduling, European Wind Energy Association (EWEA 2012), April 2012. [2] W. Charytoniuk , E. Don Box , W. J. Lee , M. S. Chen , P. Kotas and P. V. Olinda Neural Network Based Demand Forecasting in a Deregulated Environment, IEEE Transaction Industry Application, 36 (3), 2000, 893 -898.
[3] K. Methaprayoon, L. Wei-Jen, S. Rasmiddatta, et al, Multistage Artificial Neural Network Short-Term Load Forecasting Engine with Front-End Weather Forecast, IEEE Transaction Industry Application., 43 (6), Nov. 2007, 1410-1416.
[4] M. Aydinalp-Koksal, A New Approach for Modeling of Residential Energy Consumption, VDM Verlag Dr. Muller Aktiengesselschaft & Co.Kg, 2008, 9-19.

Abstract:The sizes and weight of various wireless electronic system have rapidly reduced due to the development of modern integrated circuit technology. A Microstrip antenna (MSA) is well suited for wireless communication due to its low profile, conformal nature, light weight, low cost of production, robust nature and compatibility with microwave monolithic integrated circuits (MMICs) and optoelectronic integrated circuits (OEICs) technologies. In this paper the complete discussion is focused on the working principles, limitations and the applications of microstrip patch antenna.

[1] R.Grag. P. Bhartia, I. Bahl, and A. Ittipiboon, Microstrip Antenna Design Handbook, Artech.
[2] K. F. Lee., Advances in microstrip and printed Antenna, John Wiley 1997.
[3] D. M Pozar and D.H Schaubert, Microstrip Antenna: The Analysis and Design of Microstrip Antenna and Arrays IEEE Press, 1995.
[4] S. Makarov, 2002, Antenna and EM modelling with matlab.
[5] J.-F. Zurcher, "The SSGIP: A global concept for high performance broadband plannar antennas", Electronics Letters, vol. 24, pp. 1433-1435 November 1988.

Abstract: In the age of wireless technology and increasing use of renewable energy there is a constant increase in the demand for wireless technology which is environment friendly. The first step in wireless power is providing power to any electronic device wirelessly. If the efficiency of transmitting the power wirelessly is increased slightly further, then wireless power transmission could become a standard means for charging any electronic gadget ,and also if it is by the means of a renewable and a clean power source such as Solar energy it would be an cherry on top of the cake.

[1] H. Lee, "SEEMLESS: Distributed Algorithm for Topology Control of Survivable Energy Efficient Multihop Wireless Sensor Networks Using Adjustable Transmission Power," Proc. Sixth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD'05), Towson, Maryland, May 2005
[2] Wenzhen Fu, Bo Zhang, Dongyuan Qiu, "Study on Frequency-tracking Wireless Power Transfer System by Resonant Coupling," Power Electronics and Motion Control Conference, pp. 2658-2663, May 2009.
[3] Wenzhen Fu, Bo Zhang, Dongyuan Qiu, "Study on Frequency-tracking Wireless Power Transfer System by Resonant Coupling," Power Electronics and Motion Control Conference, pp. 2658-2663, May 2009.
[4] Hassan, Marwa M. Framework for active solar collection systems. Tese PhD, Department of Building Construction: Virginia Polytechnic Institute and State University Blacksburg, 2003, Blacksburg, Virginia.

Abstract: This paper brings two main contributions to the use of learning techniques in a sensor network. First, an approach which combines time series prediction and model selection for reducing the amount of communication called adaptive model selection, is to let the sensors determine in an automated manner a prediction model that does not only fits their measurements, but that also reduces the amount of transmitted data. The second main contribution is the design of a distributed approach for modeling sensed data, based on the principal component analysis. We first show that the sensor measurements can be transformed along a routing tree in such a way that (i) most of the variability in the measurements is retained, and (ii) the network load sustained by sensor nodes is reduced and more evenly distributed.

[1] D.W. Aha. Lazy learning. Kluwer Academic Publishers Norwell, MA, USA, 1997. [2] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci. Wireless Sensor Networks:A Survey. Computer Networks, 38(4):393–422, 2002. [3] I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci. Wireless sensor networks:a survey. Computer Networks, 38(4):393–422, 2002. [4] ST Alexander. Adaptive Signal Processing: Theory and Applications. Springer-Verlag New York, Inc. New York, NY, USA, 1986.

Abstract: Microwaves refer to the electromagnetic waves in the frequency range of 300MHz to 300GHz. Once microwave energy is absorbed, polar molecules and ions inside the food will rotate or collide according to the alternating electromagnetic field and heat is subsequently generated for cooking. The use of microwave oven provides a convenient way to thaw, cook and reheat foods. However, the safety of the microwaved food has on and off aroused some public interest. This paper reviewed the basic principles, structure and characteristics of microwave heating. The biological effect and safety on users is also examined.

Keywords: Electromagnetic field, Food, Microwave, Microwave Heating, Safety.

[1] F.E. Gardiol, Introduction to microwaves, Artech House , Dedham, mass., 1984.

[2] R. Hoogenboom, T.F.A. Wilims, T. Erdmenger, and U. S. Schubert Microwave Assisted Chemistry: a Closer Look at Heating Efficiency. Aust J Chem 62, 2009. 236- 243.

[3] A.S. Mujumdar, Handbook of Industrial Drying, 3rd edition National University of Singapore

[4] T. Ohlsson, Domestic use of microwave ovens. In: Macrae R, Robinson, RK and Sadler, MJ, editors. Encyclopaedia of food science food technology and nutrition. Vol. 2. London: Academic Press; 1993. p. 1232-1237.

[5] R.J. Meredith, Engineers' Handbook of Industrial Microwave Heating. 1998.

Abstract: Electrical storage system comprising of single storage unit is often heavy, especially using lead acid batteries. One way to deal with this issue is to use number of small storage units where each storage unit is capable of driving a load for a minimum duration of time. This concept of electrical storage system is modular storage system. Apart from advantages of light weight, modular systems would require lower charging power, making it energy efficient system. Modular storage system could be used for stand alone power system applications such as for home lighting, shop lighting, unmanned aerial vehicles and robotics. Such storage systems should lower the cost of solar panel in off-grid solar photovoltaic applications. This paper introduces the concept of modular storage system and demonstrates Pb-acid based modular storage system along with its charging using time-division multiplexing method. Time-division multiplexing method utilizes pulsed charging method which reduces the charging power requirement and charging time of the divided system

Keywords: TDM, PB-acid battery, modular storage, pulsed charging, charging time

[1] V. Petrovic, Rapid battery charging method and Apparatus, US patent no. US 6388425 B1, 2001.
[2] M. Yilmaz, P. T. Krein, Review of Battery Charger Topologies, Charging Power Levels, and Infrastructure for Plug-In Electric and Hybrid Vehicles, IEEE Transactions on Power Electronics, 28(5), 2012, 2151-2169.
[3] S. R. Clarke, B-LAB: Changing the Game for Lead Acid, The Battcon 2011 Proceedings. Orlando, FL, 2011.
[4] M. Oswal, J. Paul, R. Zhao, A comparative study of Lithium-Ion Batteries, University of South California, 2010.
[5] http://mahindrareva.com/product/specifications.aspx: Accessed June 2014.

Abstract: This work presents a new control method to track the maximum power point of a single-phase grid-connected photovoltaic (PV) system. This converter is built on two stages: a DC/ DC stage and a DC/ AC stage. The two blocks are bound by a DC voltage intermediate bus. We seek the achievement of three control objectives: (i) maximum power point tracking (MPPT) of (PV) module. (ii) tight regulation of the DC bus voltage and (iii) unity power factor (PF) in the grid. To meet these objectives, a multi-loop controller is designed using the sliding mode technique based on an averaged nonlinear model of the whole controlled system. It is formally shown, through analysis and simulation results that the developed strategy control actually meets its objectives.

Keywords: photovoltaic system, maximum power point (MPP), boost converter, sliding mode, unity power factor, lyapunov.

[1] Enrico Bianconi, Javier Calvente, Roberto Giral, Emilio Mamarelis, Giovanni Petrone, Carlos Andres Ramos-Paja, Giovanni Spagnuolo, Massimo Vitelli. (2013) "Perturb and Observe MPPT algorithm with a current con-troller based on the sliding mode". International Journal of Electrical Power and Energy Systems (IJEPES), Vol.44, pp: 346-356.

[2] Yong Yang, Fang Ping Zhao. (2011) "Adaptive perturb and observe MPPT technique for Grid connected Pho-tovoltaic Inverters." Procedia Engineering,Vol.23,pp:468-473.

[3] Panagiotis E. Kakosimos, Antonios G. Kladas. (2011) "Implementation of photovoltaic array MPPT through fixed step predictive control technique".Renewable Energy, Elsevier, Vol. 36, pp: 2508-2514.

[4] Lalili D, A. Mellit, N. Lourci, B. Medjahed, E.M. Berkouk.(2011) "Input output feedback linearization control and variable step size MPPT algorithm of a grid-connectedphotovoltaic inverter". Renewable Energy, Elsevier,Vol.36,pp:3282-3291.

[5] Georgios Tsengenes, Georgios Adamidis. (2011) "Investigation of the behavior of a three phase grid-connected photovoltaic system to control active and reactive power". Electric Power Systems Research, Vol. 81, pp: 177-184.

Abstract: In this paper utilization of a boost converter for control of photovoltaic power using Maximum Power Point Tracking (MPPT) control mechanism is presented. First the photovoltaic module is analyzed using SIMULINK software. For the main aim of the project the boost converter is to be used along with a Maximum Power Point Tracking control mechanism. The MPPT is responsible for extracting the maximum possible power from the photovoltaic and feed it to the load via the boost converter which steps up the voltage to required magnitude. The main aim will be to track the maximum power point of the photovoltaic module so that the maximum possible power can be extracted from the photovoltaic. The algorithms utilized for MPPT are generalized algorithms and are easy to model or use as a code. The algorithms are written in m files of MATLAB and utilized in simulation. Both the boost converter and the solar cell are modelled using SimPower Systems blocks.

Key words: Boost Converter, MPPT, solar cell, MATLAB, SIMULINK.

[1]. Literature survey on maximum power point tracking (mppt) technique for photovoltaic (pv) system, Umesh T. Kute, Preeti S. Ratnaparkhi, IJAREAS Vol. 2 No. 12 December 2013.
[2]. Modeling of Maximum Power Point Tracking Algorithm for Photovoltaic Systems, Ioan Viorel Banu,Marcel Istrate "Gheorghe Asachi" Technical University of Iasi.
[3]. Comparison of MPPT Algorithms for DC-DC Converters Based PV Systems, A.Pradeep Kumar Yadav, S.Thirumaliah, G.Haritha, IJAREEIE Vol. 1, Issue 1, July 2012.
[4]. Modeling & simulation of a photovoltaic energy system, Sonam mishra, Manju gupta, IJEEER Vol. 3, Issue 1, Mar 2013, 61-66.
[5]. Modeling and Simulation of PV Array and its Performance Enhancement Using MPPT (P&O) Technique, T.Chaitanya, Ch.Saibabu, International Journal of Computer Science & Communication Networks,Vol 1(1),September-October 2011.
[6]. Converter topology for PV system with maximum power point tracking, Shridhar Sholapur, K.R.Mohan, IJSR Vol 3 Issue 5, May 2014.

Abstract: Using numerical calculations based on a mathematical model, this paper shows how the axial trapping efficiency (Qz) and the radial trapping efficiency (Qr) of optical tweezers depend on specific parameters such as size of the dielectric particle (r), numerical aperture of the microscope objective (NA), refractive index of the dielectric particle (np) to be trapped and the refractive index of the surrounding medium (nm) in which the particle is being trapped. The model is used to calculate the trapping efficiencies and the forces acting on a particle. The calculations are done for two types of laser beams: Gaussian and Laguerre-Gausssian. Results for both types are then compared in terms of effective trapping. For all of the simulations, the particle being trapped is considered to be a micrometer-sized spherical polystyrene bead.

Keywords: Axial Trapping Efficiency, Gaussian Beams, Laguerre-Gaussian Beams, Optical Tweezers, Radial Trapping Efficiency, Sub-micron Dielectric Particles.

[1]. Steffen Tallieu, Holographic optical trapping, master thesis, Ghent University, Ghent, Belgium, 2011-2012
[2]. Yuxiang Liu, Fiber optical tweezers for microscale and nanoscale particle manipulation and force sensing, doctoral dissertation, University of Maryland, College Park, Maryland, 2011
[3]. Aruna Ranaweera, Investigations with Optical Tweezers: Construction, Identification, and Control, doctoral dissertation, University of California, Santa Barbara, 2004

[4]. Valeria Garbin,Optical Tweezers for the study of microbubble dynamics in ultrasound, dissertation, The University of Trieste, Italy, 2005-6

[5]. Heckenberg, N. R., Friese, M. E. J., Nieminen, T. A., & Rubinsztein-Dunlop, H. (2003), Mechanical effects of optical vortices, arXiv preprint physics/0312007