Issue |
MATEC Web Conf.
Volume 171, 2018
The First International Conference on Energy, Power, Petroleum and Petrochemical Engineering (E3PE 2017)
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|
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Article Number | 02004 | |
Number of page(s) | 6 | |
Section | Chapter 2: Energy Management Systems | |
DOI | https://doi.org/10.1051/matecconf/201817102004 | |
Published online | 04 June 2018 |
Investigation of the impact of Photovoltaic Sizing and Siting Modeling on Micro-grids Energy Management Optimization
1 Electrical Power and Machines Department Faculty of Engineering, Ain Shams University Cairo, Egypt
2 Electrical Power and Machines Department Faculty of Engineering, Ain Shams University Cairo, Egypt
3 Electrical Power and Machines Department Faculty of Engineering, Ain Shams University Cairo, Egypt
* marwa.mahmoud@eng.asu.edu.eg
** walid.elkhattam@eng.asu.edu.eg
*** dr.i.helal@gmail.com
The modeling of micro-grid’s PV units’ and loads’ size and distribution along its network could severely affect the accuracy of power losses calculation and; thus the amount of energy to be imported from the main-grid to balance the load. Also, it will affect the micro-grid’s optimal energy management results. Therefore, a comprehensive analysis is carried out to assess the impact of the PV’s and the load’s sizing and sitting (either lumped or distributed). Four case studies are carried out to illustrate the impact of the modeling on the micro-grid’s losses and the imported energy from the main-grid and their costs. The obtained results are used to implement the proposed energy management two-single objective optimization functions applying Genetic Algorithm. Then, a fifth case study is carried out to optimize the micro-grid energy management process through an optimal chagrining - discharging scheduling of a storage module. The obtained results, recommendations, and evaluations for choosing a proper sizing and siting modeling and the chagrining - discharging scheduling of a storage module under seasonal variations are reported and discussed.
Key words: Energy management optimization / Genetic Algorithm optimization / Micro-grid
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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