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dc.contributor.authorMišák, Stanislav
dc.contributor.authorStuchlý, Jindřich
dc.contributor.authorVantuch, Tomáš
dc.contributor.authorBuriánek, Tomáš
dc.contributor.authorSeidl, David
dc.contributor.authorProkop, Lukáš
dc.date.accessioned2017-05-26T09:44:14Z
dc.date.available2017-05-26T09:44:14Z
dc.date.issued2017
dc.identifier.citationElectric Power Systems Research. 2017, vol. 147, p. 165-173.cs
dc.identifier.issn0378-7796
dc.identifier.issn1873-2046
dc.identifier.urihttp://hdl.handle.net/10084/117084
dc.description.abstractThe development of autonomous energy systems has been accompanied by a number of challenges related to the specific characteristics of these systems, such as power flow control, development of protection systems respecting the dynamic changes in short-circuit power and the issue of compliance with power quality parameters. To keep the power quality parameters of electrical energy in Off-Grid systems within the limit is highly complicated with regards to the supply of electrical energy from renewable sources of a stochastic nature, which are used as dominant sources of electric or heat energy. Variations in short-circuit power may significantly affect the system stability and may have a negative impact on the operation in case of sensitive appliances. We developed tools and methods to keep the power quality parameters in Off-Grid systems within the limits using an intelligent approach based on an artificial intelligence technique. Our computational model is able to predict disturbances in power quality and perform a set of proper reactions to avoid such disturbances with over 60% success rate in time horizon of 15 min ahead. As a result, it is subsequently possible to optimize the operation of Off-Grid systems and thus contribute to improvements in the power quality parameters in Off-Grid systems.cs
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofseriesElectric Power Systems Researchcs
dc.relation.urihttps://doi.org/10.1016/j.epsr.2017.02.021cs
dc.rights© 2017 Elsevier B.V. All rights reserved.cs
dc.subjectOff-Grid systemcs
dc.subjectpower qualitycs
dc.subjectrenewable energy sourcescs
dc.subjectartificial intelligencecs
dc.titleA holistic approach to power quality parameter optimization in AC coupling Off-Grid systemscs
dc.typearticlecs
dc.identifier.doi10.1016/j.epsr.2017.02.021
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume147cs
dc.description.lastpage173cs
dc.description.firstpage165cs
dc.identifier.wos000400226500018


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