Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design
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- Simone Sala & Alfonso Amendola & Sonia Leva & Marco Mussetta & Alessandro Niccolai & Emanuele Ogliari, 2019. "Comparison of Data-Driven Techniques for Nowcasting Applied to an Industrial-Scale Photovoltaic Plant," Energies, MDPI, vol. 12(23), pages 1-19, November.
- Munir Husein & Il-Yop Chung, 2019. "Day-Ahead Solar Irradiance Forecasting for Microgrids Using a Long Short-Term Memory Recurrent Neural Network: A Deep Learning Approach," Energies, MDPI, vol. 12(10), pages 1-21, May.
- Altan Dombaycı, Ömer & Gölcü, Mustafa, 2009. "Daily means ambient temperature prediction using artificial neural network method: A case study of Turkey," Renewable Energy, Elsevier, vol. 34(4), pages 1158-1161.
- Silvano Vergura, 2016. "A Complete and Simplified Datasheet-Based Model of PV Cells in Variable Environmental Conditions for Circuit Simulation," Energies, MDPI, vol. 9(5), pages 1-12, April.
- Moretti, L. & Polimeni, S. & Meraldi, L. & Raboni, P. & Leva, S. & Manzolini, G., 2019. "Assessing the impact of a two-layer predictive dispatch algorithm on design and operation of off-grid hybrid microgrids," Renewable Energy, Elsevier, vol. 143(C), pages 1439-1453.
- Tao Hong & Jason Wilson & Jingrui Xie, 2013. "Long term probabilistic load forecasting and normalization with hourly information," HSC Research Reports HSC/13/13, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
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- Trinadh Pamulapati & Muhammed Cavus & Ishioma Odigwe & Adib Allahham & Sara Walker & Damian Giaouris, 2022. "A Review of Microgrid Energy Management Strategies from the Energy Trilemma Perspective," Energies, MDPI, vol. 16(1), pages 1-34, December.
- Miguel Ángel Pardo & Héctor Fernández & Antonio Jodar-Abellan, 2020. "Converting a Water Pressurized Network in a Small Town into a Solar Power Water System," Energies, MDPI, vol. 13(15), pages 1-26, August.
- Héctor Fernández Rodríguez & Miguel Ángel Pardo, 2023. "A Study of the Relevant Parameters for Converting Water Supply to Small Towns in the Province of Alicante to Systems Powered by Photovoltaic Solar Panels," Sustainability, MDPI, vol. 15(12), pages 1-24, June.
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Keywords
microgrid; energy management; weather effects; weather forecast; electrical load forecast; fuel consumption; energy storage requirements; model predictive control;All these keywords.
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