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Showing 2 results for Distribution System

K. Eshghi and S. Pasalar,
Volume 20, Issue 2 (4-2001)
Abstract

Multicommodity distribution problem is one of the most interesting and useful models in mathematical programming due to its major role in distribution networks. The purpose of this paper is to describe and solve a special class of multicommodity distribution problems in which shipment of a commodity from a plant to a customer would go through different distribution centers. The problem is to determine which distribution centers to use so that all customer demands are satisfied, production capacities are not exceeded, and the total distribution cost is minimized.The proposed problem is formulated as a mixed integer linear program and a solution technique based on tabu search is developed, implemented and successfully applied to the test problems. Keywords: Commodity Distribution Systems, Tabu Search, Mathematical Programming
M. E. Hamedani Golshan, S. A. Arefifar, and Gh. Moslehi,
Volume 25, Issue 1 (7-2006)
Abstract

Introducing distributed generation into a power system can lead to numerous benefits including technical, economic, environmental, etc. To attain these benefits, distributed generators with proper rating should be installed at suitable locations. Given the similar effects of distributed generators and capacitor banks on operation indices of a distribution system, simultaneous assignment of best locations and sizes to both will not only lead to greatest benefits from distributed generators but also to lower reactive power capacity requirements. In this paper, a new combined planning problem involving distributed generation and Volt/VAr control means planning is formulated and solved in which the quantity of distributed generators and reactive power sources are simultaneously assigned to buses in a distribution system. Also tap positions of voltage regulators are computed such that with a given distributed generation under peak load conditions, power losses and the reactive power capacity required are minimized. Like many other problems in power network planning, the problem formulated here is a nonlinear combinatorial one. Hence, we employ the tabu search algorithm to solve the optimization problem. The results from applying the algorithm to distribution networks with 6, 19, and 33 buses are presented and compared with those obtained from employing the second order method.

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