Optimal Planning of Renewable-Based Microgrid Using Bald Eagle Search Algorithm
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-3951-8_51
Reference18 articles.
1. Hirsch A, Parag Y, Guerrero J (2018) Microgrids: a review of technologies, key drivers, and outstanding issues. Renew Sustain Energy Rev 90:402–411. https://doi.org/10.1016/j.rser.2018.03.040
2. Pourbehzadi M, Niknam T, Aghaei J, Mokryani G, Shafie-khah M, Catalão JPS (2019) Optimal operation of hybrid AC/DC microgrids under uncertainty of renewable energy resources: a comprehensive review. Int J Electr Power Energy Syst 109:139–159. https://doi.org/10.1016/j.ijepes.2019.01.025
3. Yeh W, He M, Huang C, Tan S, Zhang X, Huang Y, Li L (2020) New genetic algorithm for economic dispatch of stand-alone three-modular microgrid in DongAo Island. Appl Energy 263:114508. https://doi.org/10.1016/j.apenergy.2020.114508
4. Chen H, Zhang R, Li G, Bai L, Li F (2016) Economic dispatch of wind integrated power systems with energy storage considering composite operating costs. IET Gener Transm Distrib 10:1294–1303. https://doi.org/10.1049/iet-gtd.2015.0410
5. Islam MM, Nagrial M, Rizk J, Hellany A (2021) Dual stage microgrid energy resource optimization strategy considering renewable and battery storage systems. Int J Energy Res 7185. https://doi.org/10.1002/er.7185
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