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contributor authorGiovanni Cerri
contributor authorMarco Gazzino
contributor authorFrancesca Alessandra Iacobone
contributor authorAmbra Giovannelli
date accessioned2017-05-09T00:32:28Z
date available2017-05-09T00:32:28Z
date copyrightNovember, 2009
date issued2009
identifier issn1528-8919
identifier otherJETPEZ-27086#061801_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/140384
description abstractThe problem of planning the production of a pool of power plants has been deeply investigated. Maintenance management and load allocation problems have been assumed as crucial aspects for achieving maximum plant profitability. A production-planning approach has been developed, and genetic algorithm techniques have been adopted to implement the developed approach. Life consumption of gas turbines’ hot-section components has been considered as a key element required in simulating plants’ behaviors. As a result, a deterioration model has been developed and included into the planning algorithm. The developed approach takes market scenarios, as well as actual statuses and performances of plant components into account. The plants’ physical models are developed on a modular approach basis and provide the operating parameters required by the planning algorithm. Neural network techniques have been applied to speed up the simulation. Economic implications related to maintenance strategies, including postponement or anticipation of maintenance interventions, are investigated and the results obtained by the numerical simulation are presented and widely discussed.
publisherThe American Society of Mechanical Engineers (ASME)
titleOptimum Planning of Electricity Production
typeJournal Paper
journal volume131
journal issue6
journal titleJournal of Engineering for Gas Turbines and Power
identifier doi10.1115/1.3098429
journal fristpage61801
identifier eissn0742-4795
keywordsIndustrial plants
keywordsStress
keywordsProduction planning
keywordsAlgorithms AND Maintenance
treeJournal of Engineering for Gas Turbines and Power:;2009:;volume( 131 ):;issue: 006
contenttypeFulltext


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