i-manager Publications

i-manager's Journal on Electrical Engineering (JEE)

Current Issue Vol. 18 Issue 1

PV-grid Performance improvement through Integrated Intelligent Water Drop Optimization with Neural Network for Maximum Power Point Tracking
A Digital Healthcare Monitoring System with Real-Time Analysis
Advancements in Smart Meter Design and Integration for Enhanced Energy Management and Efficiency
Electric Vehicles in Modern Transportation: Environmental Impacts, Configurations, and Future Trends – A Review
GTO Technique Based Hybrid Power System Controller Design

Most Cited

Volume 9 Issue 4 April - June 2016

Research Paper

A New Maximum Power Point Tracking Control Technique of Solar Photovoltaic Water Pumping System

Amine Daoud*

Associate Professor, Department of Electronics, Faculty of Electrical Engineering, University of Sciences and Technology of Oran, Algeria.

Daoud, A. (2016). A New Maximum Power Point Tracking Control Technique of Solar Photovoltaic Water Pumping System. i-manager’s Journal on Electrical Engineering, 9(4), 1-11. https://doi.org/10.26634/jee.9.4.6034

Abstract

Recently, the importance of photovoltaic systems in the generation of electricity has attracted much attention because of their electrical energy production close to where it is required, no greenhouse gas emission, low maintenance cost, and no noise. However, the promotion of photovoltaic system has been limited by two problems, low conversion rate and maximum power point varying with atmospheric conditions (irradiance, temperature and air mass). Hence, one of the most economical ways to improve utilization efficiency of a photovoltaic system is to ensure that it is always operates at its maximum power point irrespective of the environmental conditions. Thus, it becomes necessary to use MPPT controller in order to ensure the efficient operation of the photovoltaic system. Within this overall context, the present paper focuses specifically on the development of new Maximum Power Point Tracking (MPPT) technique used in Photovoltaic (PV) water pumping systems. Furthermore, using this technique, only the input voltage of a PV array needs to be sensed in order to find and track the MPP. The system under study consists of a PV array, a DC-DC buck-boost converter, a DC motor-pump and an MPPT controller. This pumping system is fully modeled and simulated in MATLAB environment. Analytical models for determining PV array output power, motor-pump flow rate and shaft speed are detailed and explained. The simulation results demonstrate that the proposed MPPT technique can track the MPP perfectly.

References

[1]. M. Kolhe, J.C. Joshi, and D.P. Kothari, (2004). “Performance analysis of a directly coupled photovoltaic water-pumping system”. IEEE Transactions on Energy Conversion, Vol. 19, No. 3, pp. 613–618.

[2]. A.F. Minai, A. Tariq, and Q. Alam, (2010). “Theoretical and Experimental Analysis of Photovoltaic Water Pumping System”. India International Conference on Power Electronics (IICPE), New Delhi, India, pp. 1-8.

[3]. Z.M. Salameh, A. K. Mulpur, and F. Dagher, (1990). “Two-Stage Electrical Array Reconfiguration Controller for PV-Powered Water Pump”. Solar Energy, Vol. 44, No. 1, pp. 51-56.

[4]. V. Salas, E. Olias, A. Barrado, and A. Lazaro, (2006). “Review of the Maximum Power Point Tracking Algorithm for Stand-alone Photovoltaic Systems”. Solar Energy Materials & Solar Cells, Vol. 90, No. 11, pp. 1555-1578.

[5]. T. Esram, and P.L. Chapman, (2007). “Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques”. IEEE Transactions on Energy Conversion, Vol. 22, No. 2, pp. 439-449.

[6]. D.P. Hohm, and M.E. Ropp, (2003). “Comparative Study of Maximum Power Point Tracking Algorithms”. Progress in Photovoltaics: Research and Applications, Vol. 11, pp. 47–62.

[7]. A. Pandey, N. Dasgupta, and K. Ashok Mukerjee, (2007). “A Simple Single-Sensor MPPT Solution”. IEEE Transactions on Power Electronics, Vol. 22, No. 2, pp. 698- 700.

[8]. X-D.Sun, M. Matsui, and K. Yanagimura, (2007). “Novel Single-Voltage-Sensor-Based Maximum Power th Point Tracking Method”. The 7 International Conference on Power Electronics, Daegu, Korea, pp. 847-850.

[9]. V. Salas, E. Olias, A. Lázaro, and A. Barrado, (2005). “New algorithm using only one variable measurement applied to a maximum power point tracker”. Solar Energy Materials & Solar Cells, Vol. 87, No. 1-4, pp. 675-684.

[10]. N. Dasgupta, A. Pandey, and A.K. Mukerjee, (2008). “Voltage-Sensing-Based Photovoltaic MPPT with Improved Tracking and Drift Avoidance Capabilities”. Solar Energy Materials & Solar Cells, Vol. 92, No. 12, pp. 1552-1558.

[11]. J.A. Gow, and C.D. Manning, (1999). “Development of a photovoltaic array model for use in power electronics simulation studies”. IEEE Proceedings on Electric Power Applications, Vol. 146, No. 2, pp. 193-200.

[12]. S. Roy Chowdhury, and H. Saha, (2010). “Maximum power point tracking of partially shaded solar photovoltaic arrays”. Solar Energy Materials & Solar Cells, Vol. 94, No. 9, pp. 1441-1447.

[13]. H. El-fadil, and F. Giri, (2011). “Climatic Sensorless Maximum Power Point in Photovoltaic Generation Systems”. Control Engineering Practice, Vol. 19, No. 5, pp. 513-521.

[14]. I. Houssamo, F. Locment, and M. Sechilariu, (2010). “Maximum Power Tracker for PV Power System: Development and Experimental Comparison of Two Algorithms”. Renewable Energy, Vol. 35, No. 10, pp. 2381-2587.

[15]. G. Walker, (2001). “Evaluating MPPT converter topologies using a MATLAB PV model”. Journal of Electrical and Electronics Engineering, Vol. 21, No. 1, pp. 9-16.

[16]. D. Fewson, (1998). Introduction to Power Electronics. Arnold Publishers.

[17]. A. K. Rai, N. D. Kaushika, B. Singh, and N. Agarwal, (2011). “Simulation Model of ANN Based Maximum Power Point Tracking Controller for Solar PV System”. Solar Energy Materials & Solar Cells, Vol. 95, No. 2, pp. 773-778.

[18]. A. Hadj Arab, and F. Chenlo, M. (2004). “Benghanem, Loss-of-Load Probability of Photovoltaic Water Pumping Systems”. Solar Energy, Vol. 76, No. 6, pp. 713-723.

[19]. Y. Bakelli, A. Hadj Arab, and B. Azou, (2011). “Optimal sizing of PV pumping system with water tank storage using LPSP concept”. Solar Energy, Vol. 85, No. 2, pp. 288-294.

[20]. Hadj Arab, A., Benghanem, and M., Chenlo, F., (2006). “Motor-pump System Modelization”. Renewable Energy, Vol. 31, No. 7, pp. 905-913.

[21]. M. Jafar, (2000). “A Model for Small-scale Photovoltaic Solar Water Pumping”. Renewable Energy, Vol. 19, No. 1-2, pp. 85-90.

Full Article (HTML)

Pdf

Research Paper

Comparison of Methods of MPPT in Solar PV System

D. Jagadeesh* , T. Nageswara Prasad**

* Postgraduate, Department of Electrical and Electronics Engineering, Sree Vidyanikethan Engineering College, Tirupati, India.

** Professor, Department of Electrical and Electronics Engineering, Sree Vidyanikethan Engineering College, Tirupati, India.

Jagadeesh, D., and Prasad, T. N. (2016). Comparison of Methods of MPPT in Solar PV System. i-manager’s Journal on Electrical Engineering, 9(4), 12-19. https://doi.org/10.26634/jee.9.4.6035

Abstract

In this paper, the Maximum Power Point Tracking (MPPT) of a solar Photovoltaic (PV) system under Partial Shaded Conditions (PSC) is developed using biologically inspired algorithms. The proposed methods are compared with a conventional technique viz., incremental conductance method under partial shaded conditions. The major advantages of the proposed methods are speed of convergence, accuracy in tracking and low power oscillations. The drawback associated with conventional techniques is falling at local MPP instead of global MPP. The improved performance of the proposed method is validated through MATLAB coding in terms of tracking speed, accuracy and power oscillations.

References

[1]. P. Sankar, K. Sundareswaran, and P. Sankaran, (2014). “MPPT of PV systems under partial shaded conditions through a colony of flashing fireflies”. IEEE Trans. Energy Conversion, Vol. 29. No. 2, pp. 463-472.

[2]. H. Patel and V. Agarwal, (2008). “Maximum power point tracking scheme for PV systems operating under partially shaded conditions”. IEEE Trans. Ind. Electron., Vol. 55, No. 4, pp. 1689-1698.

[3]. Ministry of New and Renewable Energy (MNRE). Retrieved from www.mnre.gov.in

[4]. Subudhi and R. Pradhan, (2013). “A comparative study on maximum power point tracking techniques for photovoltaic power systems”. IEEE Trans. Sustainable Energy, Vol. 4, No. 1, pp. 89-98.

[5]. Antonio Luque and Stain Hegedus, (2003). Photovoltaic Science & Engineering. A. John Wiley & Sons Ltd Publications, England.

[6]. Truptishree Dutta, (2014). “Global MPPT technique in a solar PV array under partially shaded conditions”. M.Tech Thesis, NIT Rourkela.

[7]. N. Fernia, G. Petrone, G. Spagnuolo, and M. Vitelli, (2005). “Optimization of perturb and observe maximum power point tracking method”. IEEE Trans. Power Electron, Vol. 20, No. 4, pp. 963–973.

[8] T. Noguchi, S. Togashi, and R. Nakamoto, (2002). “Short-current pulse-based maximum-power-point tracking method for multiple photovoltaic and converter module system”. IEEE Trans. Ind. Electron., Vol. 49, No. 1, pp. 217–223.

[9]. B. N. Alajmi, K. H. Ahmed, S. J. Finney, and B. W. Williams, (2011). “Fuzzy logic-control approach of a modified hill-climbing method for maximum power point in microgrid standalone photovoltaic system”. IEEE Trans. Power Electron., Vol. 26, No. 4, pp. 1022–1030.

[10]. Debashis Das, and Shishir Kumar Pradhan, (2011). “Modeling and simulation of PV array with boost converter”. B.Tech Thesis, NIT Rourkela.

[11]. GN. Tiwari and Swapnil Dubey, (2010). Fundamentals of Photovoltaic Modules and their Applications. RSC Publications, Cambridge.

[12]. E. V. Paraskevadaki and S. A. Papathanassiou, (2011). “Evaluation of MPP voltage and power of mc-Si PV modules in partial shading conditions”. IEEE Trans. Energy Convers., Vol. 26, No. 3, pp. 923–932.

[13] . X.-S. Yang (2009). “Firefly algorithms for multimodal optimization”. In Proc. Stochastic Algorithms Foundations Appl. , Vol. 5792, pp. 169–178.

[14]. www.learnabout-electronics.org

[15]. Muhammad H. Rashid, (2004). Power Electronics Circuits, Devices & Applications. Pearson Education, Inc., rd 3 edition.

[16]. Satyobroto Talukder, (2011). “Mathematical Modeling and Applications of Particle Swarm Optimization”. MS Thesis, School of Engineering - Blekinge Institute of Technology (Sweden).

[17]. Y.-H. Liu, S.-C. Huang, J.-W. Huang and W.-C. Liang, (2012). “A particle swarm optimization-based maximum power point tracking algorithm for PV systems operating under partially shaded conditions”. IEEE Trans. Energy Convers., Vol. 27, No. 4, pp. 1027–1035.

[18] K. Ishaque and Z. Salam, (2013). “A deterministic particle swarm optimization maximum power point tracker for photovoltaic system under partial shading condition”. IEEE Trans. Ind. Electron., Vol. 60, No. 8, pp. 3195–3206.

[19]. Merwan Saad Saouq, Hadj Ahmad Abbassi, and Salem Kermiche, (2013). “Improved incremental conductance method for MPPT using Cuk converter”. WSEAS Trans. Power Systems, Vol. 8, No. 3, pp. 124-133.

Full Article (HTML)

Pdf

Research Paper

STATCOM with d-q Decoupled Control for Wind Energy Conversion Systems

G. Muni Reddy* , T. Gowri manohar, V. Jyothsna Priya*

* Research Scholar, Department of Electrical and Electronics Engineering, S.V University, Tirupati, Andhra Pradesh, India.

Professor, Department of Electrical and Electronics Engineering, S.V University, Tirupati, Andhra Pradesh, India.

* Assistant Professor, Department of Electrical and Electronics Engineering, SKIT, Srikalahasti, Andhra Pradesh, India.

Reddy, GM., Manohar, T.G., and Priya, V. J. (2016). Statcom with d-q Decoupled Control for Wind Energy Conversion Systems. i-manager’s Journal on Electrical Engineering, 9(4), 20-28. https://doi.org/10.26634/jee.9.4.6036

Abstract

The electric power generation from renewable energy sources like wind energy has increased in recent years due to environmental problems and the shortage of conventional energy sources in the near future. More and more wind farms are being integrated into power system grid. Integration of large scale of wind farms into power system presents challenges such as voltage and reactive power control, frequency control, grid stability and power quality. This paper demonstrates the power quality problems due to integration of wind turbine with the grid. In this proposed scheme, STATic COMpensator (STATCOM), with decoupled control of d and q current components, is connected at a point of common coupling with a battery energy storage system to reduce the effect of power quality issues. The STATCOM with decoupled control of d and q current components control scheme is employed for the grid connected wind energy conversion system is simulated using MATLAB/SIMULINK. The effectiveness of the decoupled control of d and q current components control scheme is, it takes care of the reactive power requirement of the load and the induction generator and thus improving the source side power factor and there will be a marked reduction in the Total Harmonic Distortion.

References

[1]. 20% Wind Energy by 2030, (2008). Retrieved from http://www.osti.gov/bridge

[2]. Wind Energy Benefits, (2011). Retrieved from http://www.eere.energy.gov/wind/pdfs/49053.pdf

[3]. T. Ackermann, (2005). Wind Power in Power Systems. John Wiley & Sorus, Ltd, ISBN 0-470-85508-8.

[4]. India Wind Energy Outlook – 2012 (November, 2012)

[5]. B. Singh, and S.N. Singh, (2009). “Wind Power Interconnection into the Power System: A Review of Grid Code Requirements”. The Electricity Journal, Vol. 22, No. 5, pp. 54-63.

[6]. Liuchen Chang, (2002). “Wind energy conversion systems”. IEEE Canadian Review, Spring, 2002, No. 40.

[7]. R. C. Bansal, Ahmed F. Zobaa, and R. K. Saket, (2005). “Some Issues Related to Power Generation Using Wind Energy Conversion Systems: An Overview”. International Journal of Emerging Electric Power Systems, Vol. 3, No. 2.

[8]. N.G. Hingorani and L. Gyugi, (2000). “Understanding FACTS: Concepts and technology of Flexible AC Transmission Systems”. IEEE, New York, 2000, ISBN 0-7803- 3455-8.

[9]. Chi Yongning, Li Yan, Sun Wei, Liu Chao, and Wei Linjun, (2011). “Research on Dynamic Var Compensate Strategy of Wind Farm with Statcom”. IEEE Power and Energy Engineering Conference (APPEEC), 2011 Asia- Pacific, Wuhan, pp. 1-5.

[10]. Philippe Maibach, Jonas Wernli, Peter Jones, and Mujo Obad, (2007). “STATCOM technology for wind parks to meet grid code Requirements”. EWEC 2007.

[11]. B. Ronner, P. Maibach and T. Thurnherr, (2009). “Operational experiences of STATCOMs for wind parks”. IET Renewable Power Generation, Vol. 3, No. 3, pp. 349- 357.

[12]. Arindam Chakraborty, Shravana K. Musunuri, Anurag K. Srivastava, and Anil K. Kondabathini, (2012). “Integrating STATCOM and Battery Energy Storage System for Power System Transient Stability: A Review and Application”. Hindawi Publishing Corporation, Advances in Power Electronics, Article ID 676010.

[13]. Mirjana Milosevic, (2003). “Decoupling Control of d and q Current Components in Three-Phase Voltage Source Inverter”. Technical Report, Zurich, 2003, pp. 1-11.

[14]. Chen Shen, Zhiping Yang, Mariesa L Crow, and Stan Atcitty, (2000). “Control of STATCOM with energy storage device”. Proceedings of IEEE Power Engineering Society Winter Meeting (2000), Vol. 4, pp. 2722-2728.

Full Article (HTML)

Pdf

Research Paper

Effect of Automation Intensity Levels on Distribution System Reliability

V. S. S. Sailaja*

* Associate Professor, Department of Electrical and Electronics Engineering, Vasavi College of Engineering, Hyderabad, India.

** Professor, Department of Electrical Engineering, University College of Engineering, Osmania University, Hyderabad, India.

Sailaja, V.S.S.,and Prasad, P.V.N. (2016). Effect of Automation Intensity Levels on Distribution System Reliability. i-manager’s Journal on Electrical Engineering, 9(4), 29-36. https://doi.org/10.26634/jee.9.4.6039

Abstract

Electric power distribution systems are responsible for delivering the electrical energy from the bulk power systems to the customers. Radial operation, aging infrastructures, poor design and operation practices and high exposure to environmental conditions have caused the electric power distribution systems as the main contributor to the system reliability problems. Generally, about 80 to 90 percents of the customer reliability problems originate from the electric power distribution systems. In this paper, the effect of two automation intensity levels on the reliability of radial distribution system is compared with system without automation. Partial automation and complete automation are considered. The effects of automation intensity levels on the outage time of the components considering the sequence of fault diagnosis activities that will take place from the initiation of fault to the service restoration and the reliability of the system is measured in terms of SAIDI, CAIDI, SAIFI and ENS. These reliability indices are calculated for the Roy Billinton Test System (RBTS) Bus2 using Failure Modes and Effects Analysis technique.

References

[1]. Allan, R. N., Billinton, R., Sjarief, I., Goel, L., and So, K. S. (1991). “A reliability test system for educational purposesbasic distribution system data and results”. Power Systems, IEEE Transactions on, Vol. 6, No. 2, pp. 813-820.

[2]. Bhargava, C., P. S. R. Murty, and P. Sreevani. (2013). "Reliability Assessment of Radial distribution system incorporating weather effects." International Journal of Engineering Research and Development, Vol. 6, No. 7, pp. 45-51.

[3]. Ebeling, C. E. (2004). An Introduction to Reliability and Maintainability Engineering. Tata McGraw-Hill Education.

[4]. Allan, R. N. (2013). Reliability Evaluation of Power Systems. Springer Science & Business Media.

[5]. Neha Gaur, and Priyanka Gaur, (2012). “Automation in Power Distribution System: Present Status”. Journal of Engineering Research and Studies, Vol. 3, No. 2.

[6]. Gautam Agrarwal, Dharmbir Prasad and Santosh Kumar Singh, (n.d.). “Automation of Power Distribution”. Supreme & Co Pvt Ltd.

[7]. Kazemi, S. (2011). “Reliability evaluation of smart distribution grids”. (Doctoral dissertation, Department of Electrical Engineering, School of Electrical Engineering, Aalto University, Esfoo, Finland).

[8]. Billinton, R., and Wang, P. (1999). “Teaching distribution system reliability evaluation using Monte Carlo simulation”. Power Systems, IEEE Transactions on, Vol. 14, No. 2, pp. 397-403.

[9]. Wilson, R. (2007). Control and Automation of Electrical Power Distribution Systems. CRC Press.

[10]. Staszesky, D. M., Craig, D., and Befus, C. (2005). “Advanced feeder automation is here”. Power and Energy Magazine, IEEE, Vol. 3, No. 5, pp. 56-63.

[11]. Billinton, R., and Allan, R. N. (1992). Reliability Evaluation of Engineering Systems. New York: Plenum press, pp. 155-173.

Full Article (HTML)

Pdf

Research Paper

Implementation of Perturb and Observe (P&O) Method to Track the Maximum Power Point Using Buck Converter

Bal Mukund Sharma* , Kuldeep Sahay**

* Research Scholar, Department of Electrical Engineering, Dr. A.P.J. Abdul Kalam Technical University, (Formerly UPTU), Lucknow, India.

** Professor, Department of Electrical Engineering, Institute of Engineering and Technology, Lucknow, India.

Sharma, B.M., and Sahay, K. (2016). Implementation of Perturb and Observe (P&O) Method to Track the Maximum Power Point Using Buck Converter. i-manager’s Journal on Electrical Engineering, 9(4), 37-46. https://doi.org/10.26634/jee.9.4.6038

Abstract

This study presents a new kind of Maximum Power Point Tracking algorithm based on perturb and observe algorithm. A generalized photovoltaic array simulation model in Matlab/Simulink environment is developed and presented in this paper. The model includes PV module and array for easy use on simulation platform. The proposed model is designed with a user-friendly icon and a dialog box like simulink block libraries. Considering the effect of solar irradiance and temperature changes, the output current and voltage of PV modules are simulated and optimized using this model. A perturb and observe algorithm based maximum power point tracker is also developed using the presented model in Matlab/Simulink. It can successfully track the maximum power point more accurately and quicker than other conventional method based controller in these situations. The general model was implemented on Matlab scrip file, and accepts irradiance and temperature as variable parameters and outputs the I-V characteristic. A particular typical 800W solar panel was used for model evaluation and results.

References

[1]. Bal Mukund Sharma and Kuldeep Sahay, (2014). “A Comprehensive Survey of Maximum Power Tracker Techniques for Photovoltaic System”. i-manager's Journal on Electrical Engineering. Vol. 8(1) Jul-Sep 2014, Print ISSN 0973-8835, E-ISSN 2230-7176, pp. 39-55.

[2]. K.H. Hussein, I. Muta, T. Hoshino, and M. Osakada, (1995). “Maximum photovoltaic power tracking: An algorithm for rapidly changing atmospheric conditions”. Generation, Transmission and Distribution, IEEE Proceedings, Vol. 142, No. 1, pp. 59 - 64.

[3]. Trishan Esram, and Patrick L. Chapman, (2007). “Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques”. IEEE Transactions on Energy Conversion, Vol. 22, No. 2, pp. 439-449.

[4]. R. Faranda, S. Leva, and V. Maugeri, (2008). “MPPT techniques for PV Systems: energetic and cost comparison”. Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21 Century, pp. 1 - 6.

[5]. E. I. O. Rivera, (2008). “Maximum Power Point Tracking using the Optimal Duty Ratio for DC-DC Converters and Load Matching in Photovoltaic Applications”. Applied Power Electronics Conference and Exposition, 2008, APEC 2008. 23 Annual IEEE, pp. 987-991.

[6]. R. Gules, J. De Pellegrin Pacheco, H. L. Hey, and J. Imhoff, (2008). “A maximum power point tracking system with parallel connection for PV stand-alone applications”. IEEE Trans. Ind. Electron., Vol. 55, No. 7, pp. 2674–2683.

[7]. W. Xiao, N. Ozog, and W. G. Dunford, (2008). “Topology study of photovoltaic interface for maximum power point tracking”. IEEE Trans. Ind. Electron., Vol. 54, No. 3, pp. 1696–1704.

[8]. Arun Kumar Verma, Bhim Singh and D.T Sahani, (2012). “Grid Interfaced Solar Photovoltaic Power Generating System with Power Quality Improvement at AC Mains”. Proc. of IEEE ICSET, Kathmandu, Nepal, pp. 177- 182.

[9]. G. Bhuvaneswari and R. Annamalai, (2011). “Development of a solar cell model in MATLAB for PV based generation system”. Proc. of Annual IEEE India Conference (INDICON), pp.1-5.

[10]. W. Xiao, W. Dunford, P. Palmer, and A. Capel, (2007). “Regulation of photovoltaic voltage”. IEEE Trans. Ind. Electron., Vol. 54, No. 3, pp. 1365–1374.

[11]. I.H. Altas and A.M. Sharaf, (2007). “A Photovoltaic Array Simulation Model for Matlab-simulink GUI Environment”. 2007 International Conference on Clean Electrical Power, pp. 341-345.

[12]. Tsai H.-L., Tu C.-S., and Su Y.- J., (2008). “Development of Generalized Photovoltaic Model Using Matlab/Simulink”. Proceedings of the World Congress on Engineering and Computer Science, San Francisco, USA, pp. 846–851.

[13]. Trishan Esram, Jonathan W. Kimball, Philip T. Krein, Patrick L. Chapman, and Pallab Midya, (2006). “Dynamic maximum power point tracking of photovoltaic arrays using ripple correlation control”. IEEE Transactions on Power Electronics, Vol. 21, No. 5, pp. 1282-1291.

[14]. B. Singh and S.R. Arya, (2013). “Adaptive Theory- Based Improved Linear Sinusoidal Tracer Control Algorithm for DSTATCOM”. IEEE Transactions on Power Electronics, Vol. 28, No. 8, pp. 3768-3778.

[15]. Yuncong Jiang, J.A.A. Qahouq and T.A. Haskew, (2013). “Adaptive Step Size With Adaptive-Perturbation- Frequency Digital MPPT Controller for a Single-Sensor Photovoltaic Solar System”. IEEE Trans. Power Electronics, Vol. 28, No. 7, pp. 3195-3205.

[16]. M.A. Elgendy, B. Zahawi and D.J. Atkinson, (2013). “Assessment of the Incremental Conductance Maximum Power Point Tracking Algorithm”. IEEE Transactions on Sustainable Energy, Vol. 4, No.1, pp.108-117.

[17]. Bos, M.J., Abhijith, S., Aswin, V., Basil, R., and Dhanesh R., (2014). “Fuzzy Logic Controlled PV Powered Buck Converter with MPPT”. Int. J. Adv. Res. Electr. Electron. Instrum. Eng., Vol. 3, pp. 9370–9377.

[18]. H. Renaudineau et al.,(2015). “A PSO-based global MPPT technique for distributed PV power generation,” IEEE Trans. Ind. Electron., Vol. 62, No. 2, pp. 1047–1058.

Full Article (HTML)

Pdf

Review Paper

A Review on Novel Hybrid Approximate Method Using Firefly, Wavelet, Algorithm and Day Ahead Power Cost Forecasting

Mukh Raj Yadav* , Kishan Bhushan Sahay**

* PG Scholar, Department of Electrical Engineering, MMMUT, Gorakhpur, India.

** Assistant Professor, Department of Electrical Engineering, MMMUT, Gorakhpur, India.

Yadav, M.R.,and Sahay, K.B. (2016). A Review on Novel Hybrid Approximate Method Using Firefly, Wavelet, Algorithm and Day Ahead Power Cost Forecasting. i-manager’s Journal on Electrical Engineering, 9(4), 47-54. https://doi.org/10.26634/jee.9.4.6037

Abstract

This paper shows a novel half and half insightful calculation using an information sifting method taking into account Wavelet Transform (WT), a streamlining method with Fuzzy Firefly (FF) calculation. Furthermore, a delicate registering model taking into account Fuzzy ARTMAP (FA) system, keeping in mind the end goal to conjecture day-ahead power costs in the Ontario market. An extensive near examination with other delicate registering and cross breed models demonstrate a noteworthy change in conjecture mistake about maximum 40% for every day and monthly cost gauges, by utilization of an expected cross breed model. Besides, minimum code acquired to estimate the Mean Square Error (MSE) and mean supreme blunder shows maximum level of exactness to the expected model. Vigor to the expected crossover wise models are determined by utilizing factual list (blunder change). Also, the great figure execution and the fast versatility of the proposed half and half model are likewise assessed utilizing the PJM market information.

References

[1]. R. Garcia, J. Contreras, M. Van Akkeren, and J. Garcia, (2005). “A GARCH forecasting model to predict day-ahead electricity prices”. IEEE Trans.Power Syst., Vol. 20, No. 2, pp. 867– 874.

[2]. F. Nogales, J. Contreras, A. Conejo, and R. Espinola, (2002). “Forecasting next-day electricity prices by time series models”. IEEE Trans. Power Syst., Vol. 17, No. 2, pp. 342-348.

[3]. Wang A, Ramsay B, (1997). “Prediction of system marginal price in the UK power pool using neural networks”. IEEE, International Conference on Neutral Networks, Vol. 4, pp. 2116-2120.

[4]. G. Li, C.-C. Liu, C. Mattson, and J. Lawarree, (2007). “Day-a head Electricity price forecasting in a grid environment”. IEEE Trans. Power Syst., Vol. 22, No. 1, pp. 266–274.

[5]. Y. Y. Hong and C.-Y. Hsiao, (2002). “Locational marginal price forecasting in deregulated electricity markets using artificial intelligence”. Proc. Inst. Elect. Eng., Gen., Transm., Distrib., Vol. 149, No. 5, pp. 621–626.

[6]. P. Mandal, A. Srivastava, and J.-W. Park, (2009). “An effort to optimize similar days parameters for ANN-based electricity price forecasting”. IEEE Trans. Ind. Appl., Vol. 45, No. 5, pp. 1888-1896.

[7]. M. Stevenson, (2001). “Filtering and Forecasting Spot Electricity Prices in the Increasingly Deregulated Australian Electricity Market”. Quantitative Finance Research Centre, University of Technology, Sydney.

[8]. P. Mandal, T. Senjyu, N. Urasaki, T. Funabashi, and A. Srivastava, (2007). “A novel approach to forecast electricity price for PJM using neural network and similar days method”. IEEE Trans. Power Syst., Vol. 22, No. 4, pp. 2058-2065.

[9]. K. Meng, Z. Dong, and K. Wong, (2009). “Selfadaptive radial basis function neural network for shortterm electricity price forecasting”. IET Gen.,Transm., Distrib., Vol. 3, No. 4, pp. 325–335.

[10]. Vemuri V.R. and Rogers R.D, (1994). “Artificial Neural Networks Forecasting Time Series”. IEEE Computer Society Press.

[11]. Yamin, H., Shahidehpour, S., Li, Z, (2004). “Adaptive short-term electricity price forecasting using artificial neural networks in restructured power markets”. Electrical Power and Energy Systems, Vol. 26, No. 8, pp. 571- 581.

i-manager's Journal on Electrical Engineering (JEE)

Current Issue Vol. 18 Issue 1

Most Read

Most Cited

Volume 9 Issue 4 April - June 2016

A New Maximum Power Point Tracking Control Technique of Solar Photovoltaic Water Pumping System

Amine Daoud*

Associate Professor, Department of Electronics, Faculty of Electrical Engineering, University of Sciences and Technology of Oran, Algeria.

Daoud, A. (2016). A New Maximum Power Point Tracking Control Technique of Solar Photovoltaic Water Pumping System. i-manager’s Journal on Electrical Engineering, 9(4), 1-11. https://doi.org/10.26634/jee.9.4.6034

Abstract

References

Full Article (HTML)

Pdf

Comparison of Methods of MPPT in Solar PV System

D. Jagadeesh* , T. Nageswara Prasad**

* Postgraduate, Department of Electrical and Electronics Engineering, Sree Vidyanikethan Engineering College, Tirupati, India. ** Professor, Department of Electrical and Electronics Engineering, Sree Vidyanikethan Engineering College, Tirupati, India.

Jagadeesh, D., and Prasad, T. N. (2016). Comparison of Methods of MPPT in Solar PV System. i-manager’s Journal on Electrical Engineering, 9(4), 12-19. https://doi.org/10.26634/jee.9.4.6035

Abstract

References

Full Article (HTML)

Pdf

STATCOM with d-q Decoupled Control for Wind Energy Conversion Systems

G. Muni Reddy* , T. Gowri manohar**, V. Jyothsna Priya***

Reddy, GM., Manohar, T.G., and Priya, V. J. (2016). Statcom with d-q Decoupled Control for Wind Energy Conversion Systems. i-manager’s Journal on Electrical Engineering, 9(4), 20-28. https://doi.org/10.26634/jee.9.4.6036

Abstract

References

Full Article (HTML)

Pdf

Effect of Automation Intensity Levels on Distribution System Reliability

V. S. S. Sailaja*

* Associate Professor, Department of Electrical and Electronics Engineering, Vasavi College of Engineering, Hyderabad, India. ** Professor, Department of Electrical Engineering, University College of Engineering, Osmania University, Hyderabad, India.

Sailaja, V.S.S.,and Prasad, P.V.N. (2016). Effect of Automation Intensity Levels on Distribution System Reliability. i-manager’s Journal on Electrical Engineering, 9(4), 29-36. https://doi.org/10.26634/jee.9.4.6039

Abstract

References

Full Article (HTML)

Pdf

Implementation of Perturb and Observe (P&O) Method to Track the Maximum Power Point Using Buck Converter

Bal Mukund Sharma* , Kuldeep Sahay**

* Research Scholar, Department of Electrical Engineering, Dr. A.P.J. Abdul Kalam Technical University, (Formerly UPTU), Lucknow, India. ** Professor, Department of Electrical Engineering, Institute of Engineering and Technology, Lucknow, India.

Sharma, B.M., and Sahay, K. (2016). Implementation of Perturb and Observe (P&O) Method to Track the Maximum Power Point Using Buck Converter. i-manager’s Journal on Electrical Engineering, 9(4), 37-46. https://doi.org/10.26634/jee.9.4.6038

Abstract

References

Full Article (HTML)

Pdf

A Review on Novel Hybrid Approximate Method Using Firefly, Wavelet, Algorithm and Day Ahead Power Cost Forecasting

Mukh Raj Yadav* , Kishan Bhushan Sahay**

* PG Scholar, Department of Electrical Engineering, MMMUT, Gorakhpur, India. ** Assistant Professor, Department of Electrical Engineering, MMMUT, Gorakhpur, India.

Yadav, M.R.,and Sahay, K.B. (2016). A Review on Novel Hybrid Approximate Method Using Firefly, Wavelet, Algorithm and Day Ahead Power Cost Forecasting. i-manager’s Journal on Electrical Engineering, 9(4), 47-54. https://doi.org/10.26634/jee.9.4.6037

Abstract

References

Full Article (HTML)

Pdf

* Postgraduate, Department of Electrical and Electronics Engineering, Sree Vidyanikethan Engineering College, Tirupati, India.

** Professor, Department of Electrical and Electronics Engineering, Sree Vidyanikethan Engineering College, Tirupati, India.

G. Muni Reddy* , T. Gowri manohar, V. Jyothsna Priya*

* Associate Professor, Department of Electrical and Electronics Engineering, Vasavi College of Engineering, Hyderabad, India.

** Professor, Department of Electrical Engineering, University College of Engineering, Osmania University, Hyderabad, India.

* Research Scholar, Department of Electrical Engineering, Dr. A.P.J. Abdul Kalam Technical University, (Formerly UPTU), Lucknow, India.

** Professor, Department of Electrical Engineering, Institute of Engineering and Technology, Lucknow, India.

* PG Scholar, Department of Electrical Engineering, MMMUT, Gorakhpur, India.

** Assistant Professor, Department of Electrical Engineering, MMMUT, Gorakhpur, India.