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Optimal allocation of the electrical structure design using the bats approach

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PL
Optymalne ulokowanie elementów struktury dystrybucji z wykorzystaniem Bat
Języki publikacji
EN
Abstrakty
EN
In this paper we describe and use a meta-heuristic optimization method is the algorithm of bats to be able to solve the problem of optimizing redundancy. This problem is known because we will strive to reduce the investment cost of the serial-parallel power system configuration through the algorithm, not to mention to maximize reliability and this is one of the constraints. Redundant components are included to achieve the desired level of availability, and service continuity. The maintainability of the system is based on a multi-state availability function. The elements of the power system are characterized by their performance, reliability, and availability and cost. These elements are chosen from a list of products available on the market. The meta-heuristic proposed seeks the best solution for a better configuration for our structure, which composes the system to be able to minimize the cost with the desired maximum reliability. To estimate the availability of the serial-parallel power system, a fast method based on the universal moment generation (UMGF) function is suggested. The algorithm approach of bats is used as an optimization technique. One gives an example of a power supply system for present simulation
PL
Opisano I zastosowano meta heurystyczną metodę optymalizacji problemu redundancji. Optymalizacja ma na celu redukcję kosztów szeregowo-równoległego systemu dystrybucyjnego. Elementy systemu były opisywane przez ich właściwości, niezawodność i dostępność.
Rocznik
Strony
98--102
Opis fizyczny
Bibliogr. 16 poz., rys., tab.
Twórcy
  • Université Djillali liabes sidi bel abbes-Algeria
  • Université Djillali liabes sidi bel abbes-Algeria
  • Université Djillali liabes sidi bel abbes-Algeria
  • Université Djillali liabes sidi bel abbes-Algeria
Bibliografia
  • [1] Ushakov, Levitin and Lisnianski, Multi-state system reliability: from theory to practice. Proc. of 3 Int. Conf. on mathematical methods in reliability, MMR 2002, Trondheim, Norway, pp. 635- 638.
  • [2] Levitin and Lisnianski, A new approach to solving problems of multi-state system reliability optimization. Quality and Reliability Engineering International, vol. 47, No. 2, 2001, pp. 93-104.
  • [3] Tillman, Hwang and Kuo, Tillman, F. A., C. L. Hwang, and W. Kuo, “Optimization Techniques for System Reliability with Redundancy – A review,” IEEE Transactions on Reliability, Vol. R-26, no. 3, 1997, 148-155.
  • [4] Kuo and Prasad, An Annotated Overview of System- reliability Optimization. IEEE Transactions on Reliability, Vol. 49, no. 2, 2000, 176-187.
  • [5] Ushakov, Optimal standby problems and a universal generating function. Sov. J. Computing System Science, Vol. 25, N 4, 1987, pp 79-82.
  • [6] Lisnianski, Levitin, Ben-Haim and Elmakis, Power system structure optimization subject to reliability constraints. Electric Power Systems Research, vol. 39, No. 2, 1986, pp.145-152.
  • [7] Levitin, Lisnianski, Ben-Haim and Elmakis, Structure optimization of power system with different redundant components. Electric Power Systems Research, vol. 43, No. 1, 1997, pp.19-27.
  • [8] Dorigo, Maniezzo and Colorni, The Ant System: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man and Cybernetics- Part B, Vol. 26, No.1, 1996, pp. 1-13.
  • [9] Dorigo and Gambardella, Bat algorithmSystem: A cooperative Learning Approach to the Traveling Salesman roblem”, IEEE Transactions on Evolutionary computation, Vol. 1, No.1, 1997, pp. 53-66.
  • [10] Maniezzo and Colorni, The Ant System Applied to the Quadratic Assignment Problem. IEEE Transactions on Knowledge and data Engineering, Vol. 11, no. 5, 1997, pp 769- 778.
  • [11] Liang and Smith, An Bat algorithmApproach to Redundancy Allocation. Submitted to IEEE Transactions on eliability.2001.
  • [12] Bullnheimer, Hartl and Strauss, Applying the Ant System to the vehicle Routing problem. 2nd Metaheuristics International Conference (MIC-97), Sophia-Antipolis, France, 1997, pp. 21- 24.
  • [13] Ushakov, Universal generating function. Sov. J. Computing System Science, Vol. 24, N 5, 1996, pp 118-129.
  • [14] Ross, Introduction to probability models. Academic ress.1993.
  • [15] Dallery and Gershwin, Manufacturing Flow Line Systems: A Review of Models and Analytical Results. Queueing stems theory and Applications, Special Issue on Queueing Models of Manufacturing Systems, Vol. 12, No. 1- 2, 1992, pp. 3-94.
  • [16] J.C. Dodu, P. Martin, A. Merlin, J. Pouget, “An optimal formulation and solution of short-range operating problems for a power system with flow constraints,” IEEE Proc; 60(1):54– 63, 1972
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2865a85b-a1ea-4ab0-b586-995b6b6c647f
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