Open Access

Research on new energy grid-connected load monitoring method based on the network analysis method


Cite

Lund, H., Ostergaard, P. A., Connolly, D., & Mathiesen, B. V. (2017). Smart energy and smart energy systems. Energy, 137, 556-565. Search in Google Scholar

Yang, Y., Bremner, S., Menictas, C., & Kay, M. (2018). Battery energy storage system size determination in renewable energy systems: A review. Renewable and Sustainable Energy Reviews, 91, 109-125. Search in Google Scholar

Brown, T., Schlachtberger, D., Kies, A., Schramm, S., & Greiner, M. (2018). Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system. Energy, 160, 720-739. Search in Google Scholar

Elsheikh, A. H., Sharshir, S. W., Abd Elaziz, M., Kabeel, A. E., Guilan, W., & Haiou, Z. (2019). Modeling of solar energy systems using artificial neural network: A comprehensive review. Solar Energy, 180, 622-639. Search in Google Scholar

Zhang, F., & Wang, K. (2023). Key technologies of smart factory machine vision based on efficient deep network model. 3c Empresa: investigación y pensamiento crítico, 12(1), 15-35. Search in Google Scholar

Kuster, C., Rezgui, Y., & Mourshed, M. (2017). Electrical load forecasting models: A critical systematic review. Sustainable cities and society, 35, 257-270. Search in Google Scholar

Amarasinghe, K., Marino, D. L., & Manic, M. (2017, June). Deep neural networks for energy load forecasting. In 2017 IEEE 26th international symposium on industrial electronics (ISIE) (pp. 1483-1488). IEEE. Search in Google Scholar

Almalaq, A., & Edwards, G. (2017, December). A review of deep learning methods applied on load forecasting. In 2017 16th IEEE international conference on machine learning and applications (ICMLA) (pp. 511-516). IEEE. Search in Google Scholar

Alhussein, M., Aurangzeb, K., & Haider, S. I. (2020). Hybrid CNN-LSTM model for short-term individual household load forecasting. Ieee Access, 8, 180544-180557. Search in Google Scholar

Kong, W., Dong, Z. Y., Hill, D. J., Luo, F., & Xu, Y. (2017). Short-term residential load forecasting based on resident behaviour learning. IEEE Transactions on Power Systems, 33(1), 1087-1088. Search in Google Scholar

Bianchi, F. M., Maiorino, E., Kampffmeyer, M. C., Rizzi, A., & Jenssen, R. (2017). An overview and comparative analysis of recurrent neural networks for short term load forecasting. arXiv preprint arXiv: 1705.04378. Search in Google Scholar

Qiu, T., & Faraji, J. (2021). Techno‐economic optimization of a grid‐connected hybrid energy system considering electric and thermal load prediction. Energy Science & Engineering, 9(9), 1313-1336. Search in Google Scholar

Lingamuthu, R., & Mariappan, R. (2019). Power flow control of grid connected hybrid renewable energy system using hybrid controller with pumped storage. International Journal of Hydrogen Energy, 44(7), 3790-3802. Search in Google Scholar

Sigalo, M. B., Pillai, A. C., Das, S., & Abusara, M. (2021). An energy management system for the control of battery storage in a grid-connected microgrid using mixed integer linear programming. Energies, 14(19), 6212. Search in Google Scholar

Shirzadi, N., Nasiri, F., El‐Bayeh, C., & Eicker, U. (2022). Optimal dispatching of renewable energy‐ based urban microgrids using a deep learning approach for electrical load and wind power forecasting. International Journal of Energy Research, 46(3), 3173-3188. Search in Google Scholar

Asadabadi, M. R., Chang, E., & Saberi, M. (2019). Are MCDM methods useful? A critical review of analytic hierarchy process (AHP) and analytic network process (ANP). Cogent Engineering, 6(1), 1623153. Search in Google Scholar

Fei, L. (2020). D-ANP: a multiple criteria decision making method for supplier selection. Applied Intelligence, 50, 2537-2554. Search in Google Scholar

Gupta, G., & Mishra, R. P. (2018). Identification of critical components using ANP for implementation of reliability centered maintenance. Procedia CIRP, 69, 905-909. Search in Google Scholar

Sanny, L., Simamora, B. H., Polla, J. R., & Atipa, J. L. (2018). Business Strategy Selection Using SWOT Analysis with ANP and Fuzzy TOPSIS for Improving Competitive Advantage. Pertanika Journal of Social Sciences & Humanities, 26(2). Search in Google Scholar

Balaji, M., Dinesh, S. N., Vetrivel, S. V., Kumar, P. M., & Subbiah, R. (2021). Augmenting agility in production flow through ANP. Materials Today: Proceedings, 47, 5308-5312. Search in Google Scholar

eISSN:
2444-8656
Language:
English
Publication timeframe:
Volume Open
Journal Subjects:
Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics