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Title: | Optimal charge/discharge scheduling of batteries in microgrids of prosumers |
Authors: | Ruiz Cortés, Mercedes González Romera, Eva Lopes, Rui Amaral Romero Cadaval, Enrique Martins, João Milanés Montero, María Isabel Barrero González, Fermín |
Keywords: | Sistemas de gestión de la batería;Recursos energéticos;Almacen de energia;Algoritmos genéticos;Microrredes;Autoconsumo;Battery management systems;Energy resources;Energy storage;Genetic algorithms;Microgrids;Self-consumption |
Issue Date: | 2019 |
Publisher: | IEEE |
Abstract: | Integration of renewable energy sources, active role of consumers and energy management systems are currently among research priorities in energy systems. This paper proposes an innovative coordinated energy scheduling for a microgrid of neighbor prosumers with different consumption patterns. All prosumers have photovoltaic generation systems, Li-ion batteries as energy storage systems and regular household loads. A genetic algorithm is used to schedule each prosumer’s battery charge/discharge, with the aim of reducing energy exchange losses by minimizing the power in the point of interconnection of the microgrid with the main grid, with several advantages compared to classical optimization objectives, and without worsening battery lifespan degradation. Individual and coordinated strategies are compared and self-consumption and self-sufficiency of the prosumers’ set are evaluated with the aim of showing the advantage of coordination. The paper concludes that coordinated operation can contribute to improve the exploitation of energy resources in the prosumer microgrid, reducing the amount of energy interchanged with the distribution grid by approximately 13%, and, at the same time, avoiding increasing the battery cycling and consequent degradation. |
Description: | Publicado en: IEEE Transactions on Energy Conversion (Volume: 34, Issue: 1, March 2019, pp. 468-477) http://dx.doi.org/10.1109/TEC.2018.2878351 |
URI: | http://hdl.handle.net/10662/9752 |
Appears in Collections: | DIEEA - Artículos |
Files in This Item:
File | Description | Size | Format | |
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10.1109_TEC.2018.2878351_postprint.pdf | 841,89 kB | Adobe PDF | View/Open |
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