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contributor authorMa, Yinghao
contributor authorXie, Kaigui
contributor authorDong, Jizhe
contributor authorTai, Heng–Ming
contributor authorHu, Bo
date accessioned2019-02-28T10:55:50Z
date available2019-02-28T10:55:50Z
date copyright8/22/2017 12:00:00 AM
date issued2018
identifier issn0195-0738
identifier otherjert_140_01_014501.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4250904
description abstractBundled wind–thermal generation system (BWTGS) is an effective way to utilize remote large–scale wind power. The optimal generation maintenance schedule (GMS) for BWTGS is not only helpful to improve the system reliability level but also useful to enhance the system economic efficiency and extend the lifetime of components. This paper presents a model to optimize the GMS for BWTGS. The probabilistic production simulation technique is employed to calculate the system costs, and a sequential probabilistic method is utilized to capture the sequential and stochastic nature of wind power. A hybrid optimization algorithm (HOA) based on the simulated annealing (SA) and multipopulation parallel genetic algorithm (GA) is developed to solve the proposed model. Case studies demonstrate the effectiveness of this proposed model. Effects of the reliability deterioration of thermal generating units (TGUs) and the pattern of BWTGS transmission power are also investigated.
publisherThe American Society of Mechanical Engineers (ASME)
titleOptimal Generation Maintenance Schedule for Bundled Wind–Thermal Generation System
typeJournal Paper
journal volume140
journal issue1
journal titleJournal of Energy Resources Technology
identifier doi10.1115/1.4037536
journal fristpage14501
journal lastpage014501-7
treeJournal of Energy Resources Technology:;2018:;volume 140:;issue 001
contenttypeFulltext


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