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| WR82 |
| WHX124 |
| WHX132 |
| WHX150 |
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| SS-2184 |
| SS-800 |
| 81X,81XH |
| M315 |
| M450 |
| M630 |
| M900 |
| 9835M |
| 110M |
| 111M |
| 150M |
| 5907D |
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Power Transmission Planning
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Since the late 1980¨s, the electric utility industry has beenfacing the pressure of deregulation and restructuring. Twoof the major changes were that the owners of the power transmission could participate in the market to makedecisions on behalf of themselves, and that the oldboundary lines have been removed to offer consumers morealternatives, for example, in the U.S., consumers wereallowed to purchase electricity from power stations locatedin other states.
As deregulation and restructuring have become inevitabletrends in the modern utility industries, there is a need formore efficient methods or systems to facilitate a searching method to find new partners, as well as a system to identify the contribution from eachparticipant.
Deregulation and restructuring have been adopted inseveral states, for example, California, and countries, forexample, Australia; market structure of such states orcountries have been changed significantly. In most cases, amore decentralized system or negotiation infrastructure hasreplaced the original system. Since this issue was veryimportant, Wu et al. [18] have developed a decentralizedalgorithm to optimize multilateral trading among theparticipants. For transmission planning, Bushnell and Stoft[2], and Chao et al. [3] have shown that investmentincentives and market mechanisms have been important toguarantee a fair and just outcome.
Planning for transmission expansion involves decisionsfrom the players over several scenarios, which include thenetwork topology, suppliers, customers, and/or owners oftransmission lines. It is common that when adding a new power transmission, costs should be shared by all the playerswho will have a benefit. The decision making process aboutwhether to add one more line or not and how to allocatecosts is still an open research area.
This problem is very similar to the logistics planningproblem in which the numbers and locations of themanufacturing plants or warehouses and retail stores arefixed. Therefore, to design a new logistics system, whichincludes decision of the routing and number of trucks, hasbecome the core of the problem. In other words, the goalof solving such a problem is to satisfy the demands of anew set of consumers with the lowest costs to both ownersof the transmission gear and owners of power units. Tosolve such problems, a solution needs to guarantee that theother operational constraints, such as, capacity of power transmission, can be satisfied.
Several techniques have been used to assist the planningof transmission expansion. For example, techniques basedon mathematical programming, such as Branch-and-Bound[4, 5, 12], techniques based on sensitivity analysis [1, 13],and techniques that use a hybrid of neural networks andgenetic algorithms [19]. Normally, planning for expansionis a combinatorial problem, and that makes it very difficultto find reasonable solutions within short computationaltime if the number of nodes or number of participants islarge.
Using game theory to assist in the formation of coalitionsis one approach to solve the power transmission expansion problem. In particular, Gately used the Shapley value to setup regional cooperation for investment in expansion andcost allocation [6]. Gately¨s approach was a centralizedone, where a central planner is needed to be in charge ofcost allocation.
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