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| Title | Day-Ahead Optimization Algorithm For Demand Side Management In Microgrids |
|---|---|
| ID_Doc | 17534 |
| Authors | Feizi T.; Von Der Heiden L.; Popova R.; Rojas M.; Gerbaulet J.-M. |
| Year | 2019 |
| Published | SMARTGREENS 2019 - Proceedings of the 8th International Conference on Smart Cities and Green ICT Systems |
| DOI | http://dx.doi.org/10.5220/0007686600510057 |
| Abstract | Germany has the political vision of reducing carbon emissions and becoming environmentally sound. According to this vision, the number of electric vehicles (EVs), charging stations and renewable power generators being installed in low voltage grids would increase. The uncontrolled charging of a large number of EVs can generate additional load peaks and lead to the violation of utilization limits in distribution grids. However, the charging of EVs can be controlled, providing the opportunity to relieve the grid and reduce the peak load. This control strategy is called Demand Side Management (DSM). This paper presents a day-ahead optimization algorithm for DSM in a microgrid. The developed algorithm focuses on minimizing the load peaks of a microgrid. Two scenarios, with and without stationary battery storage, have been developed and tested with various historical load profiles of the Micro Smart Grid (MSG) on the European Energy Forum (EUREF) campus in Berlin. The optimization results have shown that using the algorithm offers the possibility to reduce microgrid load peaks. Copyright © 2019 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved |
| Author Keywords | Demand Side Management; Electric Vehicles; Microgrid; Smart Grid |
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