A multiobjective interval programming model for wind-hydrothermal power system dispatching using 2-step optimization algorithm.
Wind-hydrothermal power system dispatching has received intensive attention in recent years because it can help develop various reasonable plans to schedule the power generation efficiency. But future data such as wind power output and power load would not be accurately predicted and the nonlinear n...
| Publicado en: | Scientific World Journal pp. 825216 - 825217 |
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| Autores principales: | , |
| Formato: | Journal Article |
| Publicado: |
Wiley-Blackwell
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103827110&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103827110 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 103827110 NLM24895663 2012606862 10.1155/2014/825216 NLM24895663 PMC4034478 103827110 ppf: 825216 ppct: 1 formats: tig: atl: A multiobjective interval programming model for wind-hydrothermal power system dispatching using 2-step optimization algorithm. aug: au: Ren, Kun Jihong, Qu affil: Institute of Water Resources and Hydro-electric Engineering, Xi'an University of Technology, Xi'an 710048, China ; North China University of Water Resources and Electric Power, Zhengzhou 450011, China. sug: subj: Models, Theoretical Weather Algorithms Energy-Generating Resources ab: Wind-hydrothermal power system dispatching has received intensive attention in recent years because it can help develop various reasonable plans to schedule the power generation efficiency. But future data such as wind power output and power load would not be accurately predicted and the nonlinear nature involved in the complex multiobjective scheduling model; therefore, to achieve accurate solution to such complex problem is a very difficult task. This paper presents an interval programming model with 2-step optimization algorithm to solve multiobjective dispatching. Initially, we represented the future data into interval numbers and simplified the object function to a linear programming problem to search the feasible and preliminary solutions to construct the Pareto set. Then the simulated annealing method was used to search the optimal solution of initial model. Thorough experimental results suggest that the proposed method performed reasonably well in terms of both operating efficiency and precision. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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