Conference Proceedings

This research article proposes a novel Economical and Eco-Friendly (EEF) hybrid model of Solar Photovoltaic (SPV) energy integrated with In-Pipe Hydro Energy (HER) recovered from the High Head Water (HHW) flows in the pipelines for Stand-Alone Applications (SOA) in High-Rise Buildings (HRB) such as Residential Apartments. Although the SPV energy is considered as one of the most viable Renewable Energy Resources (RES) in the world, its limitation with off-grid applications is its intermittent nature of power generation. Even the integration of SPV with Battery Storage Backup (BSB) also has limitations such as capacity and peak load constrains, besides the requirement of high initial capital investments. These aspects motivated the authors to carry out the present research study for integrating the SPV with HER, which is the untapped energy of the HHW flows from overhead tanks to the point of consumption. The research study shows that integration of SPV with HER can deliver uninterrupted, reliable and environmental-friendly electric power supply for SOA at an optimal unit cost. A working model of the proposed system has been designed, installed in a typical multistoried apartment building and tested.

Keywords : Economical and Eco-Friendly (EEF), Solar Photovoltaic (SPV), Hydro Energy (HER), Stand-Alone Applications (SOA), Renewable Energy Resource (RES)

Recent

[1] Bakos, G. C., “Feasibility Study of a Hybrid Wind/Hydro Power-System for Low-Cost Electricity Production,” Applied Energy, Vol. 72, No. 3-4, pp. 599-608, 2002 [2] Jaramillo O.A, Borja M.A, Huacuz J.M, “Using hydropower to complement wind energy: a hybrid system to provide firm power”, Renewable Energy, vol. 29, pp. 1887–909, 2004 [3] Bhagwan Reddey,J and D.N. Reddy ―Probabilistic Performance Assessment of a Roof Top Wind, Solar Photo Voltaic Hybrid Energy System, Engineering Science and Education Journal, Vol. 2, No. 4, pp. 281-298, 2008 [4] Jin Wang, Fang Z. Peng, Joel Anderson, Alan Joseph and Ryan Buffen Barger, Low System for Residential Power Generation. IEEE Transaction on Power Electronics, pp.660-687, Vo. 19, No. 5, 2009 [5] Fthenakis, V., Mason, J.E., Zweibel, K., “The technical, geographical, and economic feasibility of solar energy to supply the energy needs of the US”, Energy Policy, vol. 37, pp. 387–399, 2009 [6] Jacobson, M.Z., “Review of solutions to global warming, air pollution, and energy security”, Energy and Environmental Science, vol. 2, pp. 148–17, 2009 [7] Kusakana, K, Munda,J.L, and.Jimoh,A.A, “Feasibility Study of A Hybrid PV-Micr Hydro System for Rural Electrification”, IEEE Xplore: 03 November 2009 [8] Sharaf, A. M. and El-Sayed, M. A. H., “A Novel Hybrid Integrated Wind-PV Micro Co-Generation Energy Scheme for Village Electricity,” Proc. of IEEE International Electric Machines and Drives Conference (IEMDC '09), pp. 1244-1249, 2009 [9] Nema, P, Nema,R.K, and Rangnekar, S, “A current and future state of art development of hybrid energy system using wind and PV-solar”, A Review, Renewable and Sustainable Energy Reviews, vol. 13, pp. 2096-2103, 2010 [10] Gatte MT, Kadhim RA, Rasheed FL, “Using water energy for electrical energy conservation by building of micro hydroelectric generators on the water pipelines that depend on the difference in elevation”, Power Control, vol. 7, pp. 379–383, 2010 [11] Margeta J, and Glasnivic Z, “Feasibility of the green energy production by hybrid solar + hydropower system in Europe and similar climate areas”, Renewable Sustainable Energy, vol. 14, pp. 1580–90, 2010 [12] Gatte MT, Kadhim RA, Rasheed FL, “Using water energy for electrical energy conservation by building of micro hydroelectric generators on the water pipelines that depend on the difference in elevation”, Power Control”, vol. 7, pp. 379–383, 2010 [13] Mark Z.Jacobson and MarkA.Delucchi, “Providing all global energy with wind, water, and solar power, Part II: Reliability, system and transmission costs, and policies”, Energy Policy, vol. 39, pp. 1170– 1190, 2011 [14] Ehsan,M.M, Enaiyat Ghani Ovy , Kazy Fayeen Shariar, Ferdous,S.M, “A Novel Approach of Electrification of the High Rise Buildings at Dhaka City during Load Shedding Hours”, International Journal Of Renewable Energy Research, vol.2, No.1, 2012 [15] Bekele, G. and Tadesse, G., “Feasibility Study of Small Hydro/PV/ Wind Hybrid System for Off-Grid Rural Electrification in Ethiopia,” Applied Energy, Vol. 97, pp. 5-15, 2012

In this paper, Firefly Algorithm (FA) based design of the optimal PID controller is proposed for the benchmark Automatic Voltage Regulator (AVR) system. The best possible solution (Kp, Ki, Kd) for the PID controller is obtained by minimizing the multi-objective cost function. In this work, the FA explores the three dimensional search space, till it discovers the optimal PID parameters. This paper also presents a comprehensive study various search assisted FA, such as Brownian, Levy and chaotic exploration. The simulation work is implemented using the traditional and modified form of PID controllers. The performance of PID is computed based on the time domain values and the error values. The performances of chosen FA are also assessed based on its run time. From this research work, it can be observed that, all the search techniques tender similar time domain and error values. The iteration time taken for the Chaotic FA is relatively lesser than other FAs. Proposed approach is also authenticated against the other related works existing in the literature and it is noted that, FA based PID controller offers better result.

Keywords : PID Controller; AVR; Firefly Algorithm; Performance Analysis

Recent

[1] V. Rajinikanth, and K. Latha, “Setpoint weighted PID controller tuning for unstable system using heuristic algorithm,” Archives of Control Sciences, vol. 22, no.4, pp.481-505, 2012. [2] Z.L. Gaing, “A Particle Swarm Optimization Approach for Optimum Design of PID Controller in AVR System,” IEEE Transactions on Energy Conversion, vol. 19, no.2, pp.384- 391, 2004. [3] V. Rajinikanth, and Suresh Chandra Satapathy, “Design of controller for automatic voltage regulator using teaching learning based optimization,” Procedia Technology, vol.21, pp. 295-302, 2015. [4] B. Omer, “Continuous Firefly Algorithm for Optimal Tuning of PID Controller in AVR System,” Journal of Electrical Engineering, vol.65, no.1, pp.44-49, 2014. [5] C.C.Wong, S.A. Li, and H.Y. Wang, “Optimal PID Controller Design for AVR System,” Tamkang Journal of Science and Engineering, vol.12, no.3, pp.259-270, 2009. [6] J-Y. Kim, H-S.Lee, and J-H. Park, “A Modified Particle Swarm Optimization for Optimal Power Flow,” Journal of Electrical Engineering & Technology, Vol.2, No.4, pp. 413~419, 2007. [7] D.H. Kim, “Hybrid GA–BF based intelligent PID controller tuning for AVR system,” Applied Soft Computing, Vol.11, No.1, pp.11-22, January 2011. [8] X.S. Yang, “Nature-Inspired Metaheuristic Algorithms,” Luniver Press, Frome, UK, 2nd edition, 2011. [9] X.-S. Yang, “Firefly algorithms formultimodal optimization,” in Stochastic Algorithms: Foundations and Applications, Lecture Notes in Computer Science, vol. 5792, pp. 169–178, 2009. [10] X.-S. Yang, “Firefly algorithm, L´evy flights and global optimization,” in Proceedings of the 29th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence (AI ’09), pp. 209–218, Springer, December 2009. [11] N.S.M. Raja, K.S. Manic, and V. Rajinikanth, “Firefly algorithm with various randomization parameters: an analysis,” Lecture Notes in Computer Science, vol. 8297, pp. pp 110-121, 2013. [12] M. Araki, H. Taguchi, “Two-Degree-of-Freedom PID Controllers,” International Journal of Control, Automation, and Systems, vol.1, no.4, pp.401-411, 2003. [13] C.C.Chen, H.P. Huang, and H.J. Liaw, “Set-Point Weighted PID Controller Tuning for Time-Delayed Unstable Processes,” Ind. Eng. Chem. Res., vol.47, no.18, pp. 6983–6990, 2008. [14] V. Rajinikanth, and M.S. Couceiro, “RGB histogram based color image segmentation using firefly algorithm,” Procedia Computer Science, vol.46, pp.1449–1457, 2015. [15] N.S.M. Raja, and V. Rajinikanth, “Brownian distribution guided bacterial foraging algorithm for controller design problem,” Advances in Intelligent Systems and Computing, Vol.248, pp 141-148, 2014. [16] N.S.M. Raja, V. Rajinikanth and K. Latha, “Otsu based optimal multilevel image thresholding using firefly algorithm,” Modelling and Simulation in Engineering, vol. 2014, Article ID 794574, 17 pages, 2014. [17] K.S. Manic, R.K. Priya, and V. Rajinikanth, “Image Multithresholding based on Kapur/Tsallis Entropy and Firefly Algorithm,” Indian Journal of Science and Technology, vol.9, no.12, 89949, 2016. [18] V. Rajinikanth, J.P. Aashiha, and A. Atchaya, “Gray-level histogram based multilevel threshold selection with bat algorithm,” International Journal of Computer Applications, vol.93, no.16, pp. 1–8, 2014. [19] V. Rajinikanth, K. Latha, and N.S.M. Raja, “Model parameter estimation procedure for a class of dynamic systems using firefly algorithm,” International Journal of Computational Intelligence Research, vol.9, no.2, pp. 101-114, 2013. [20] K.S .Manic, V. Rajinikanth, S. Ananthasivam, U. Suresh, “Design of Controller in Double Feedback Control Loop–An Analysis with Heuristic Algorithms,” Chemical Product and Process Modeling, vol.10, no.4, pp. 253-262, 2015. [21] V. S. Lakshmi, S.G. Tebby, D. Shriranjani, and V. Rajinikanth, “Chaotic cuckoo search and Kapur/Tsallis approach in segmentation of t.cruzi from blood smear images,” International Journal of Computer Science and Information Security (IJCSIS), vol.14, CIC 2016, pp. 51-56, 2016. [22] S.C. Satapathy, N.S.M. Raja, V. Rajinikanth, A. S. Ashour, and N. Dey, “Multi-level image thresholding using Otsu and chaotic bat algorithm,” Neural Computing and Applications, pp.1-23, 2016. DOI:10.1007/s00521-016-2645-5. [23] V. Rajinikanth, and K. Latha, “Internal model control-proportional integral derivative controller tuning for first order plus time delayed unstable systems using bacterial foraging algorithm,” Scientific Research and Essays, vol.7, no.40, pp. 3406-3420, 2012.

With increasing competition in the global market continuous research are done to optimize the behavior of materials to be used in transformer. Since silicon (Si) comprises a very good crystallographic arrangement then that of iron (Fe), silicon is fused with iron for considerable reduction of leakage flux in it. A novel M19 high grade silicon steel core has been introduced for 1 KVA 415/230V delta to star connected distribution transformer and stray losses are estimated using Ansys Maxwell. The obtained results are validated by experimental test.

Keywords : M19 Silicon Core, Straylosses, Eddy Current, Distribution Transformer

Recent

[1] S.V. Kulkarni, S.A. Khaparde, “Transformer Engineering Design and Practice” a book Indian Institute of Technology, Bombay in 2004. [2] Indrajit Dasgupta, “Design of transformers” a book published by Tata McGraw Hill Education in 2002. [3] “Non-oriented M-19 through M-47 Electrical Steels” by Allegheny Technology. [4] Kulkarni, S.V., “Stray losses in power transformer evaluation and experimental Verification” by IIT, Bombay, India, 2000. [5] Winders Jr. John J., “Power Transformers, Principles and Applications” PPL Electric utilities Allentown, Pennsylvania in 2002. [6] Andrew R. Hileman., “Insulation Coordination for Power Systems” CRC Press, Monroeville, Pennysylvia, 1999. [7] JohnJ.Winders,Jr.,“Power Transformers Principles and Applications”. [8] “Steel Products Manual on Flat Rolled Electrical Steel” American Iron and Steel Institute, January, Washington, D. C., 1983. [9] Cullity, D.B., “Introduction to Magnetic Materials” Addison Wesley, Published by John Wiley & Sons, Inc., Hoboken, New Jersey, 1972. [10] Heck, Carl, “Magnetic Materials and Their Applications” N. Y., Crane, Russak & Company, Inc., London Butterworth’s, 1974. [11] Emil Mechkov, Raina Tzeneva, Valentin Mateev and Ivan Yatchev, “Thermal analysis using 3D FEM model of oil immersed distribution transformer” 19th IEEE International Symposium on Electrical Apparatus and Technologies (SIELA) , PP.1 – 3, June 2016. [12] Zhiyuan Xie, Sisi Han and Lichong Wang, “The Magnetic Modulation of DC Transformer Core Characteristics Analysis” 3rd IEEE International Conference on Information Science and Control, PP.1433 - 1438, July 2016. [13] Chao Wang, Honghua Xu, Jiewei Gong and Hongzhong Ma, “Finite element analysis of large transformer winding looseness” IEEE China International Conference on Electricity Distribution (CICED), PP.1 – 4, August 2016.

This paper addresses an improved PSO algorithm based PID controller tuning for a model biochemical reactor. Biochemical reactor is a highly nonlinear process and exhibits multiple steady states. To increase the productivity and to achieve the required performance, it is necessary to use optimised PID controller parameters. The work presented in this article, deals with the I-PD based controller design using PSO algorithm in order to minimise the effect of proportional and derivative kick. The gain (set point) scheduling is simulated with a switching unit controlled by a comparator. The simulation result shows a better performance for set point tracking and disturbance rejection.

Keywords : Biochemical Reactor, PID, PSO, Scheduling

Recent

[1] Aidan O’Dwyer. (2009). Hand book Handbook of PI and PID controller tuning rules, 3rd Edition, Imperial College Press, London. [2] Chang, W-D., and Shin, S-P. (2010), PID controller design of nonlinear systems using an improved particle swarm optimization approach , Communications in Nonlinear Science and Numerical Simulation, Elsevier, Volume 15 (11), 3632-3639. [3] Giriraj Kumar, S.M., Jain, R., Anantharaman, N., Dharmalingam, V., and Sheriffa Begam, K.M.M.(2008). Genetic Algoritha Based PID Controller Tuning for a Model Bioreactor, Indian Institute of Chemical Engineers, Vol.50, No.3, 214-226. [4] Hiroya Seki, and Takashi Shigemasa. (2010). Retuning Oscillatory PID control loops based on plant operation data, Journal of Process Control, 20, 217-227. [5] Kennedy, J and Eberhart, R.(1995). Particle Swarm Optimization, in proceedings of IEEE International Conference on Neural, 1942- 1948. [6] Michael A. Johnson, Mohammad H. Moradi. (2005).PID Control: New Identification and Design Methods, Springer-Verlag London Limited. [7] Padma Sree, R. and Chidambaram, M. (2006). Control of Unstable Systems, Narosa Publishing House, India. [8] Panda, Ramesh C. (2009). Synthesis of PID controller for unstable and integrating processes, Chemical Engineering Science, 64, 2807-2816. [9] Rajinikanth,V., Latha, K.(2010). Identification and Control of Unstable Biochemical Reactor, International Journal of Chemical Engineering and Applications, Vol. 1, No. 1,106 -111. [10] Sabura Banu, U., and Uma,G.(2008).Fuzzy Gain Scheduled Continuous Stirred Tank Reactor with Particle Swarm Optimization based PID control Minimizing Integral Square Error, Instrumentation Science & Technology, Volume 36 (4), 394 – 409. [11] Wayne Bequette, B. (2003). Process Control – Modeling, Design and Simulation, Prentice – Hall of India Pvt Ltd. [12] You-Bo Wang, Xin Peng, and Ben-Zheng Wei. (2008). A New Particle Swarm Optimization Based Auto-Tuning of PID Controller, in proceedings of 7th International Conference on Machine Learning and Cybernetics, IEEE press, pp.1818-1823.