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In this paper, the fault location and types of them are recognized and analyzed in the distributed system by using wavelet and feed-forward neural network and radial basis function neural network. When fault occurring in the system, the system behaviors are examined and signals are measured which can be seen as distorted waveforms. These distorted waveforms are self-possessed of different frequency components and are needed to be represented in time–frequency domain for fault analysis. For this representation of signal, discrete wavelet transform (DWT) is offered. It extracts the features and the datasets are formed which are forwarded to FFNN and RBFNN for classification of fault occurred in the distributed power system. The proposed method is implemented in MATLAB/simulink platform. This work is validated using statistical parameters, such as accuracy, sensitivity, and specificity and is compared with each other.

This area proposes about the optimal location for fixing fuel cells in a distribution system by an innovative technique. The innovation of this method is the combined performance of the Genetic Algorithm and Artificial Intelligence (RNN) technique, thus integrating GA in two stages and Artificial Intelligence (RNN) technique. The optimum placement of fuel cell is attained by the GA first stage (Mohammadi and Nasab in Res J Appl Sci Eng Technol 3:838–842, 2011 [1]). The RNN is suitably trained by the target fuel cell size and the corresponding inputs such as load variation and bus number. The main objective helps to enhance the bus voltage profile and reduce power loss (Zayandehroodi et al. in Int J Phys Sci 6:3999–4007, 2011 [2]). Thus, this approach is implemented in MATLAB/simulink. Its performance is evaluated by comparing different methods like GA, PSO and other hybrid PSO techniques (Mohammadi and Nasab in Res J Appl Sci Eng Technol 2:832–837, 2011 [3]). The comparison result is explicitly demonstrated the supremacy of this method and confirm its sterling potentiality to solve the problem (Chowdhury et al. in IEEE Trans Ind Appl 39:1493–1498, 2003 [4]).

Considering the intermittent natural energy resources and the seasonal un-balance, a phtovoltaic-wind hybrid electrical power supply system was developed to accommodate remote locations where a conventional grid connection is inconvenient or expensive. However, the hybrid system can also be applied with grid connection and owners are allowed to sell excessive power back to the electric utility. The proposed set-up consists of a photo-voltaic solar-cell array, a mast mounted wind generator, lead-acid storage batteries, an inverter unit to convert DC to AC, electrical lighting loads, electrical heating loads, several fuse and junction boxes and associated wiring, and test instruments for measuring voltages, currents, power factors, and harmonic contamination data throughout the system. The proposed hybrid solar-wind power generating system can be extensively used to illustrate electrical concepts in hands-on laboratories and also for demonstrations in the Industrial Technology curriculum. This paper describes an analysis of local PV-wind hybrid systems for supplying electricity to a private house, farmhouse or small company with electrical power depending on the site needs. The major system components, work principle and specific working condition are presented.

This article presents a simple method for investigating the problem of contemporaneously choosing optimal location and size of shunt capacitors in three-phase unbalanced radial distribution systems...

This article presents a simple reconfiguration algorithm that is specially suited for balanced and unbalanced radial distribution systems. The proposed algorithm involves less complex mathematical expressions, and a more efficient network configuration can be obtained with reduced power losses. The choice of the switches to be closed is based on the calculation of bus voltages and the minimum total system losses using a power flow program. This method takes a smaller number of switchings and less CPU time. Results obtained on one balanced system and two unbalanced systems are also presented and compared with the existing methods.

This paper presents a simple three phase power flow method for solution of three-phase unbalanced radial distribution system (RDN) with voltage dependent loads. It solves a simple algebraic recursive expression of voltage magnitude, and all the data are stored in vector form. The algorithm uses basic principles of circuit theory and can be easily understood. Mutual coupling between the phases has been included in the mathematical model. The proposed algorithm has been tested with several unbalanced radial distribution networks and the results are presented in the article. 8- bus and IEEE 13 bus unbalanced radial distribution system results are in agreements with the literature and show that the proposed model is valid and reliable., {"references":["D. Das, D. P. Kothari, and A. Kalam, 1995. Simple and efficient\nmethod for load flow solution of radial distribution networks,\nElectrical Power and Energy Systems, 17(5):335-346.","S. Ghosh, D. Das, 1999. Method for load flow solution of radial\ndistribution networks, IEE Proc. Generation, Transmission and\nDistribution, 146(6):641-648.","P. Aravindhababu, 2003. A new fast decoupled power flow method\nfor distribution systems, Electric Power Components and Systems,\n31(9):869-878.","R. D. Zimmerman and H. D. Chiang, 1995. Fast decoupled power\nflow for unbalanced radial distribution systems, IEEE-PES Winter\nMeeting, paper no. 95, New York.","S. K. Goswami and S. K. Basu, 1991. Direct solution of distribution\nsystems, IEE Proc. C, 188(1):78-88.","D. Thukaram, H. M. Wijekoon Banda, and J. Jerome, 1999. A Robust\nthree phase power flow algorithm for radial distribution systems,\nElectric Power System Research, 50(3):227-236.","W. M. Lin, Y. S. Su, H. C. Chin, and J. H. Teng, 1999. Three-Phase\nunbalanced distribution power flow solutions with minimum data\npreparation, IEEE Trans. on Power Systems, 14(3):1178-1183.","P. A. N. Garcia, J. L. R. Pereira, S. Carnerio, V. M. da Costa, and N.\nMartins, 2000. Three-Phase power flow calculations using the current\ninjection method, IEEE Trans. on Power Systems , 15( 2):508-514.","P. A. N. Garcia, J. L. R. Pereira, and S. Carneiro, Jr., 2001. Voltage\ncontrol devices models for distribution power flow analysis, IEEE\nTrans. Power Syst., 16(4):586-594.\n[10] P. A. N. Garcia, J. L. R. Pereira, and S. Carneiro, Jr., 2004.\nImprovements in the representation of PV buses on three-phase\ndistribution power flow, IEEE Trans. Power Del., 19(2):894-896.\n[11] K. N. Mui and H. D. Chiang, 2000. Existence, uniqueness and\nmonotonic properties of the feasible power flow solution for radial\nthree phase distribution networks, IEEE Trans. Circuit and Syst.,\n47(10):1502-1514.\n[12] W. M. Lin and J. H. Teng, 2000. Three-Phase distribution networks\nfast decoupled power flow solutions, Electric Power and Energy\nSystems, 22(5):375-380.\n[13] T. H. Chen, M. S. Chen, K. J. Hwang, P. Kotas, and E. A. Chebli,\n1991. Distribution system power flow analysis-a rigid approach,\nIEEE Trans. on Power Delivery, 6(3):1146-1153.\n[14] J. H. Teng, 2002. A Modified gauss-seidel algorithm of three-phase\npower flow analysis in distribution network, Electrical Power and\nEnergy Systems, 24(2):97-102.\n[15] J. H. Teng, 2000. A Network-Topology-based Three-Phase Load\nPower Flow for Distribution Systems, Proceedings of National\nScience Council ROC (A), 24(4):259-264.\n[16] L. L. Grgsby: Editor-in-Chief, The Electric Power Engineering\nHandbook, CRC Press 1999, pages 6-53 to 6-62.\n[17] W. H. Kersting, Distribution System Modeling and Analysis, CRC\nPress 2002, chapter 9.\n[18] J. Nagarath and D. P. Kothari, Power system Engineering, New\nDelhi: Tata McGraw Hill Publications, 2nd edition, 1998.\n[19] D. Shirmohammadi and Carol S. Cheng, 1995. A Three phase power\nflow method for real time distribution system analysis, IEEE Trans.\non Power System, 10(2):671-679.\n[20] IEEE Distribution System Analysis Subcommittee, 1991. Radial\ndistribution test feeders, IEEE Trans. on Power Systems, 6(3):975-\n985.\n[21] Radial Distribution test feeders -\nweb:http://www.ewh.ieee.org/soc/pes/dsacom/testfeeders.html."]}

To minimize power losses, it is important to determine the location and size of local generators to be placed in unbalanced power distribution systems. On account of some inherent features of unbalanced distribution systems, such as radial structure, large number of nodes, a wide range of X/R ratios, the conventional techniques developed for the transmission systems generally fail on the determination of optimum size and location of distributed generators (DGs). This paper presents a simple method for investigating the problem of contemporaneously choosing best location and size of DG in three-phase unbalanced radial distribution system (URDS) for power loss minimization and to improve the voltage profile of the system. Best location of the DG is determined by using voltage index analysis and size of DG is computed by variational technique algorithm according to available standard size of DGs. This paper presents the results of simulations for 25-bus and IEEE 37- bus Unbalanced Radial Distribution system., {"references":["T. Ackermann, G. Anderson, L. Söder, 2001. Distributed generation: a\ndefinition. Electrical Power System Research, 57: 195-204.","G. Pepermans, J. Driesen, D. Haeseldonckx, R. Belmans, W.\nD-haeseleer, 2005. Distributed Generation: definition, benefits and\nissues. Energy Policy, 33: 787-798.","P.P. Barker, R.W. de Mello, 2000. Determining the impact of\ndistributed generation on power systems Part 1 - Radial distribution\nsystems. IEEE PES Summer Meeting, 3: 1645-1656.","N. Hadjsaid, J.F. Canard, F. Dumas, 1999. Dispersed generation impact\non distribution networks. IEEE Computer Application in Power\nSystem, 12: 22-28.","S. Rau, Y.H. Wan, 1994. Optimum location of resources in distributed\nplanning. IEEE Transactions in Power System, 9: 2014-2020.","K.H. Kim, Y.J. Lee, S.B. Rhee, S.K. Lee, S.-K. You, 2002. Dispersed\ngenerator placement using fuzzy-GA in distribution systems. IEEE PES\nSummer Meeting, 3: 1148-1153.","J.O. Kim, S.W. Nam, S.K. Park, C. Singh, 1998. Dispersed generation\nplanning using improved Hereford Ranch algorithm. Electrical Power\nSystem Research, 47: 47-55.","K. Nara, Y. Hayashi, K. Ikeda, T. Ashizawa, 2001. Application of tabu\nsearch to optimal placement of distributed generators. IEEE PES\nWinter Meeting, 2: 918-923.","H.L. Willis, 2000. Analytical methods and rules of thumb for\nmodelling DG distribution interaction. IEEE PES Summer Meeting, 3:\n1643-1644.\n[10] T. Griffin, K. Tomsovic, D. Secrest, A. Law, 2000. Placement of\ndispersed generation systems for reduced losses. 33rd Annual Hawaii\nInternational Conference on Systems Sciences, Maui, 1-9.\n[11] C. Wang, M.H. Nehrir, 2004. Analytical approaches for optimal\nplacement of DG sources in power systems. IEEE Transactions in\nPower System, 19(4): 2068-2076.\n[12] T. Gözel, M.H. Hocaoglu, U. Eminoglu, A. Balikci, 2005. Optimal\nplacement and sizing of distributed generation on radial feeder with\ndifferent static load models. International Conference on Future Power\nSystems, Amsterdam, November 16-18.\n[13] N. Acharya, P. Mahat, N. Mithulananthan, 2006. An analytical\napproach for DG allocation in primary distribution network.\nInternational Journal of Electrical Power & Energy System, 28(10):\n669-678.\n[14] J.-H. Teng, C.-Y. Chang, 2002. A network-topology-based capacitor\ncontrol algorithm for distribution systems. IEEE Transmission and\nDistribution Conference, 2: 1158-1163.\n[15] H.N. Ng, M.M.A. Salama, A.Y. Chikhani, 2000. Classification of\ncapacitor allocation techniques. IEEE Transactions on Power Delivery,\n15: 387-392.\n[16] Shirmohammadi.D, Carol.S, Cheng, 1995. A Three phase power flow\nmethod for real time distribution system analysis. IEEE Transactions in\nPower System, 10(2): 671-679.\n[17] Sarika Kushalini, Noel schulz, 2006. Unbalanced distribution power\nflow with distributed generation. IEEE PES Transmission and\nDistribution Conference and Exhibition, 301-306.\n[18] Chen T. H, Chen M. S, Hwang K. J, Kotas. P, Chebli E. A, 1991.\nThree phase Co-generator and transformer models for distribution\nanalysis\" IEEE Transactions Power Delivery, 6(4): 1671-1681.\n[19] Radial Distribution test feeders - web:\nhttp://www.ewh.ieee.org/soc/pes/dsacom/testfeeders.html"]}