Optimal placement and sizing of battery energy storage using the genetic algorithm
dc.contributor.advisor | Anaya-Lara, Olimpo | |
dc.contributor.author | Gavric, Mirko | |
dc.date.accessioned | 2017-03-13T07:49:40Z | |
dc.date.available | 2017-03-13T07:49:40Z | |
dc.date.created | 2016-11-15 | |
dc.date.issued | 2016 | |
dc.identifier | ntnudaim:16400 | |
dc.identifier.uri | http://hdl.handle.net/11250/2433738 | |
dc.description.abstract | Voltage rise and drop are one of the major problems in low voltage distribution networks. Usually they occur due to the large mismatches in demand and supply of power. An increase in the penetration of renewable energy sources (RES) is also a contributor to these problems. With the help of energy storage these problems can be successfully mitigated and the RES hosting capacity of the distribution networks can be increased. The effects of using this strategy can be maximized by optimal placement and sizing of energy storage. There are various tools used for the optimization processes and one of them is the Genetic Algorithm which has proven to be a good tool for this type of problems. | |
dc.language | eng | |
dc.publisher | NTNU | |
dc.subject | Wind Energy, Electric Power Systems | |
dc.title | Optimal placement and sizing of battery energy storage using the genetic algorithm | |
dc.type | Master thesis |
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Institutt for elkraftteknikk [2499]