Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/101946
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dc.contributor.authorGayibov, Tulkin-
dc.contributor.authorLatipov, Sherkhon-
dc.contributor.authorPulatov, Bekhzod-
dc.date.accessioned2023-04-18T11:16:52Z-
dc.date.available2023-04-18T11:16:52Z-
dc.date.issued2023-
dc.identifier.urihttps://opendata.uni-halle.de//handle/1981185920/103899-
dc.identifier.urihttp://dx.doi.org/10.25673/101946-
dc.description.abstractOne of the main tasks to be solved during planning the short-term modes of power systems is the optimization of compositions of operating units in power plants. In general case, it is a complex problem of nonlinear mathematical programming. Its solution, in essence, comes down to determining for each time interval of the planning period the composition of units to be put into operation or to be stopped. Currently, there are many methods and algorithms for solving of this problem. On the powers obtained at this stage and generalized energy characteristics, the optimal compositions of operating units in power plants are determined. The effectiveness of proposed algorithm is researched on the examples of power systems mode optimization with determination the composition of operating units in power plants. The high accuracy of results of optimization and the reliability of convergence of iterative process is ensured due to direct use in calculations the real, obtained in tabular form, energy characteristics of power plants with effective consideration of functional constraints by penalty functions, as well as due to the ability of genetic algorithm to solve multi-extremal problems without any simplifications.-
dc.format.extent1 Online-Ressource (8 Seiten)-
dc.language.isoeng-
dc.rights.urihttps://creativecommons.org/licenses/by-sa/4.0/-
dc.subject.ddc004-
dc.titleOptimization of the Composition of Operating Units in Power Plants by Genetic Algorithm-
local.versionTypepublishedVersion-
local.publisher.universityOrInstitutionHochschule Anhalt-
local.openaccesstrue-
dc.identifier.ppn1842686607-
local.bibliographicCitation.year2023-
cbs.sru.importDate2023-04-18T11:15:04Z-
local.bibliographicCitationEnthalten in Proceedings of the 11th International Conference on Applied Innovations in IT - Koethen, Germany : Edition Hochschule Anhalt, 2023-
local.accessrights.dnbfree-
Appears in Collections:International Conference on Applied Innovations in IT (ICAIIT)

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