• 대한전기학회
Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
  • COPE
  • kcse
  • 한국과학기술단체총연합회
  • 한국학술지인용색인
  • Scopus
  • crossref
  • orcid

References

1 
F. Bonassi, A. La Bella, L. Fagiano, R. Scattolini, D. Zarrilli and P. Almaleck, “Software-in-the-loop testing of a distributed optimal scheduling strategy for microgrids’ aggregators,” 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), pp. 985-989, 2020. DOI:10.1109/ISGT-Europe47291.2020.9248775DOI
2 
C. S. B. Clausen, B. N. Jørgensen and Z. G. Ma, “A scoping review of in-the-loop paradigms in the energy sector focusing on software-in-the loop,” Energy Informatics, vol. 7, pp. 1-40, 2024. DOI:10.1186/s42162-024-00312-8DOI
3 
S. Sumith Shankar, K. Desai, S. Dutta, R. R. Chetwani, M. Ravindra and K. M. Bharadwaj, “Mission critical software test philosophy a SILS based approach in Indian Mars Orbiter Mission,” 2014 International Conference on Contemporary Computing and Informatics (IC3I), pp. 414-419, 2014. DOI:10.1109/IC3I.2014.7019637DOI
4 
H. T. Nguyen, G. Yang, A. H. Nielsen and P. H. Jensen, “Hardware- and Software-in-the-Loop Simulation for Parameterizing the Model and Control of Synchronous Condensers,” IEEE Transactions on Sustainable Energy, vol. 10, no. 3, pp. 1593-1602, July 2019. DOI:10.1109/TSTE.2019.2913471DOI
5 
C. A. V. Guerrero et al., “A new software-in-the-loop strategy for real-time testing of a coordinated Volt/Var Control,” 2016 IEEE PES PowerAfrica, pp. 6-10, 2016. DOI:10.1109/PowerAfrica.2016.7556559DOI
6 
G. M. Casolino, M. AlizadehTir, A. Andreoli, M. Albanesi and F. Marignetti, “Software-in-the-loop simulation of a test system for automotive electric drives,” IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society, pp. 1882-1887, 2016. DOI:10.1109/IECON.2016.7794145DOI
7 
M. Mütherig, G. Puleo, M. Zdrallek and A. Schönbauer, “Development of a software in the loop environment to control a microgrid,” 7th International Hybrid Power Plants & Systems Workshop (HYB), pp. 103-107, 2023. DOI:10.1049/icp.2023.1439DOI
8 
F. Bin and J. He, “A short-term photovoltaic power prediction model using cyclical encoding and STL decomposition based on LSTM,” 2023 3rd International Conference on Electronic Information Engineering and Computer Communication (EIECC), pp. 260-266, 2023. DOI:10.1109/EIECC60864.2023.10456727DOI
9 
Q. -T. Phan, Y. -K. Wu and Q. -D. Phan, “Short-term Solar Power Forecasting Using XGBoost with Numerical Weather Prediction,” 2021 IEEE International Future Energy Electronics Conference (IFEEC), pp. 1-6, 2021. DOI:10.1109/IFEEC53238.2021.9661874DOI
10 
D. Liu and K. Sun, “Random forest solar power forecast based on classification optimization,” Energy, vol. 187, Art. no. 115940, Nov. 2019. DOI:10.1016/j.energy.2019.115940DOI
11 
Z. Wang and L. Jia, “Short-Term Photovoltaic Power Generation Prediction Based on LightGBM-LSTM Model,” 2020 5th International Conference on Power and Renewable Energy (ICPRE), pp. 543-547, 2020.DOI
12 
M. Lambert and R. Hassani, “Diesel genset optimization in remote microgrids,” Applied Energy, vol. 340, Art. no. 121036, June 2023. DOI:10.1109/ICPRE51194.2020.9233298DOI
13 
K. Rajashekaraiah, C. Iurlaro, S. Bruno and G. De Carne, “Modelling of 3-Phase p-q Theory-Based Dynamic Load for Real-Time Simulation,” IEEE Open Access Journal of Power and Energy, vol. 10, pp. 654-664, 2023. DOI:10.1109/OAJPE.2023.3340299DOI
14 
J. S. Hwang, J. -S. Kim and H. Song, “Handling Load Uncertainty during On-Peak Time via Dual ESS and LSTM with Load Data Augmentation,” Energies, vol. 15, Art. no. 3001, 2022. DOI:10.3390/en15093001DOI