dc.contributor.author | Mišák, Stanislav | |
dc.contributor.author | Stuchlý, Jindřich | |
dc.contributor.author | Vantuch, Tomáš | |
dc.contributor.author | Buriánek, Tomáš | |
dc.contributor.author | Seidl, David | |
dc.contributor.author | Prokop, Lukáš | |
dc.date.accessioned | 2017-05-26T09:44:14Z | |
dc.date.available | 2017-05-26T09:44:14Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Electric Power Systems Research. 2017, vol. 147, p. 165-173. | cs |
dc.identifier.issn | 0378-7796 | |
dc.identifier.issn | 1873-2046 | |
dc.identifier.uri | http://hdl.handle.net/10084/117084 | |
dc.description.abstract | The 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.iso | en | cs |
dc.publisher | Elsevier | cs |
dc.relation.ispartofseries | Electric Power Systems Research | cs |
dc.relation.uri | https://doi.org/10.1016/j.epsr.2017.02.021 | cs |
dc.rights | © 2017 Elsevier B.V. All rights reserved. | cs |
dc.subject | Off-Grid system | cs |
dc.subject | power quality | cs |
dc.subject | renewable energy sources | cs |
dc.subject | artificial intelligence | cs |
dc.title | A holistic approach to power quality parameter optimization in AC coupling Off-Grid systems | cs |
dc.type | article | cs |
dc.identifier.doi | 10.1016/j.epsr.2017.02.021 | |
dc.type.status | Peer-reviewed | cs |
dc.description.source | Web of Science | cs |
dc.description.volume | 147 | cs |
dc.description.lastpage | 173 | cs |
dc.description.firstpage | 165 | cs |
dc.identifier.wos | 000400226500018 | |