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A Comprehensive Review of the Current Status of Smart Grid Technologies for Renewable Energies Integration and Future Trends: The Role of Machine Learning and Energy Storage Systems. (2024). Kiasari, Mahmoud ; Ghaffari, Mahdi ; Aly, Hamed H.
In: Energies.
RePEc:gam:jeners:v:17:y:2024:i:16:p:4128-:d:1459360.

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  19. Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead. (2023). Leonowicz, Zbigniew ; Shahzad, Sulman ; Akhtar, Saima ; Gono, Radomir ; Jasiski, Micha ; Kilic, Heybet ; Ullah, Hafiz Sami ; Zaheer, Asad.
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  23. Short-term electricity load forecasting—A systematic approach from system level to secondary substations. (2023). Madeira, Sara C ; Pinheiro, Marco G ; Francisco, Alexandre P.
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  24. A Hybrid Algorithm for Short-Term Wind Power Prediction. (2022). Xiong, Zhenhua ; Zhuo, Yixin ; Chen, Yan ; Huang, Kui ; Ban, Guihua.
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  25. Sustainable power systems operations under renewable energy induced disjunctive uncertainties via machine learning-based robust optimization. (2022). Zhao, Ning ; You, Fengqi.
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  28. Evaluation of opaque deep-learning solar power forecast models towards power-grid applications. (2022). Wei, Zhinong ; Cheng, Lilin ; Zang, Haixiang ; Sun, Guoqiang ; Zhang, Fengchun.
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  34. Multi-Input Nonlinear Programming Based Deterministic Optimization Framework for Evaluating Microgrids with Optimal Renewable-Storage Energy Mix. (2021). Alhumaid, Yousef ; Khalid, Muhammad ; Khan, Khalid ; Alismail, Fahad.
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  35. Improving Wind Power Forecasts: Combination through Multivariate Dimension Reduction Techniques. (2021). Poncela, Pilar ; Poncela-Blanco, Marta.
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  36. Prediction of Solar Power Using Near-Real Time Satellite Data. (2021). Kay, Merlinde ; Prasad, Abhnil Amtesh.
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  37. A Comparative Study of Machine Learning-Based Methods for Global Horizontal Irradiance Forecasting. (2021). Thil, Stephane ; Grieu, Stephane ; Gbemou, Shab ; Eynard, Julien ; Guillot, Emmanuel.
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  38. Applications for solar irradiance nowcasting in the control of microgrids: A review. (2021). Blum, Niklas ; Moghbel, Moayed ; Shoeb, Md Asaduzzaman ; Calais, Martina ; Shafiullah, G M ; Nouri, Bijan ; Samu, Remember.
    In: Renewable and Sustainable Energy Reviews.
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  39. Optimal energy bidding for renewable plants: A practical application to an actual wind farm in Spain. (2021). Payan, Manuel Burgos ; Endemao-Ventura, Lazaro ; Roldan, Juan Manuel ; Riquelme, Jesus Manuel ; Gonzalez, Javier Serrano.
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    RePEc:eee:renene:v:175:y:2021:i:c:p:1111-1126.

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  40. Ultra-short-term combined prediction approach based on kernel function switch mechanism. (2021). Zhao, Yongning ; Qu, Ying ; Zhong, Wuzhi ; Lu, Peng ; Ye, Lin ; Zhai, Bingxu ; Tang, Yong.
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  41. Short-term wind power forecasting using the hybrid model of improved variational mode decomposition and Correntropy Long Short -term memory neural network. (2021). Tian, Xuan ; Ma, Wentao ; Fang, Shuai ; Wang, Peng ; Duan, Jiandong ; Liu, Haofan ; Cheng, Yulin ; Chang, Ying.
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  42. A review of wind speed and wind power forecasting with deep neural networks. (2021). Wang, Yun ; Zou, Runmin ; Liu, Qianyi ; Zhang, Lingjun.
    In: Applied Energy.
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  43. A Characterization of Metrics for Comparing Satellite-Based and Ground-Measured Global Horizontal Irradiance Data: A Principal Component Analysis Application. (2020). Bueso, Maria C ; Paredes-Parra, Jose Miguel ; Mateo-Aroca, Antonio ; Molina-Garcia, Angel.
    In: Sustainability.
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  44. Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications. (2020). Dong, Z Y ; Begum, R A ; Ker, Pin Jern ; Faisal, M ; Hannan, M A ; Zhang, C.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:131:y:2020:i:c:s1364032120303130.

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  45. A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization. (2020). Mishra, Y ; Sreeram, V ; Ahmed, R ; Arif, M D.
    In: Renewable and Sustainable Energy Reviews.
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  46. Assessment of critical parameters for artificial neural networks based short-term wind generation forecasting. (2020). Sewdien, V N ; Preece, R ; van der Meijden, M ; Rueda, J L ; Rakhshani, E.
    In: Renewable Energy.
    RePEc:eee:renene:v:161:y:2020:i:c:p:878-892.

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  47. Impact of 15-day energy forecasts on the hydro-thermal scheduling of a future Nordic power system. (2020). Rasku, Topi ; Kiviluoma, Juha ; Miettinen, Jari ; Rinne, Erkka.
    In: Energy.
    RePEc:eee:energy:v:192:y:2020:i:c:s0360544219323631.

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  48. Deep Learning Models for Long-Term Solar Radiation Forecasting Considering Microgrid Installation: A Comparative Study. (2019). Hong, Sugwon ; Lee, Seung-Jae ; Aslam, Muhammad ; Kim, Hyung-Seung.
    In: Energies.
    RePEc:gam:jeners:v:13:y:2019:i:1:p:147-:d:302641.

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  49. Day Ahead Hourly Global Horizontal Irradiance Forecasting—Application to South African Data. (2019). Sigauke, Caston ; Mulaudzi, Sophie ; Mpfumali, Phathutshedzo ; Bere, Alphonce.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:18:p:3569-:d:268391.

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  50. Wind power forecast based on improved Long Short Term Memory network. (2019). Gao, Zhiyu ; Zhang, Rongchang ; Jing, Huitian.
    In: Energy.
    RePEc:eee:energy:v:189:y:2019:i:c:s0360544219319954.

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