Adaptation of High Spatio-Temporal Resolution Weather/Load Forecast in Real-World Distributed Energy-System Operation

Amir Ali Safaei Pirooz, Mohammad J. Sanjari (), Young-Jin Kim, Stuart Moore, Richard Turner, Wayne W. Weaver, Dipti Srinivasan, Josep M. Guerrero and Mohammad Shahidehpour
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Amir Ali Safaei Pirooz: Meteorology and Remote Sensing, National Institute of Water and Atmospheric Research (NIWA), Wellington 6241, New Zealand
Mohammad J. Sanjari: School of Engineering and Built Environment, Griffith University, Gold Coast, QLD 4222, Australia
Young-Jin Kim: Department of Electrical Engineering, Pohang University of Science and Technology, Pohang 37673, Republic of Korea
Stuart Moore: Meteorology and Remote Sensing, National Institute of Water and Atmospheric Research (NIWA), Wellington 6241, New Zealand
Richard Turner: Meteorology and Remote Sensing, National Institute of Water and Atmospheric Research (NIWA), Wellington 6241, New Zealand
Wayne W. Weaver: Mechanical Engineering-Engineering Mechanics Department, Michigan Technological University, Houghton, MI 49931, USA
Dipti Srinivasan: Department of Electrical & Computer Engineering, National University of Singapore, Singapore 119228, Singapore
Josep M. Guerrero: Faculty of Engineering and Science, Aalborg University, 9220 Aalborg, Denmark
Mohammad Shahidehpour: Electrical and Computer Engineering Department, Illinois Institute of Technology, Chicago, IL 60616, USA

Energies, 2023, vol. 16, issue 8, 1-16

Abstract: Despite significant advances in distributed renewable energy systems (DRES), the technology still faces several substantial challenges that prevent the large-scale adoption of these systems into a country’s energy sector. The intermittency of renewables, uncertainties associated with real-time multi-horizon weather and load forecasts, and lack of comprehensive control systems are among the main technical and regulatory challenges for the real-world adoption of DRES. This paper outlines the current state of knowledge in the real-world operation of DRES and also describes pathways and methodologies that enable and facilitate the uptake of DRES in a country’s energy sector.

Keywords: renewable microgrid; high-resolution weather/energy forecasting; grid integration; comprehensive control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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