Journal article
Using time series simulation tool for assessing the effects of variable renewable energy generation on power and energy systems
The increasing share of variable renewable energy (VRE) generation poses challenges to power systems. Possible challenges include adequacy of reserves, planning and operation of power systems, and interconnection expansion studies in future power systems with very different generation patterns compared to today.
To meet these challenges, there is a need to develop models and tools to analyze the variability and uncertainty in VRE generation. To address the varied needs, the tools should be versatile and applicable to different geographical and temporal scales. Time series simulation tools can be used to model both today and future scenarios with varying VRE installations.
Correlations in Renewable Energy Sources (CorRES) is a simulation tool developed at Technical University of Denmark, Department of Wind Energy capable of simulating both wind and solar generation. It uses a unique combination of meteorological time series and stochastic simulations to provide consistent VRE generation and forecast error time series with temporal resolution in the minute scale.
Such simulated VRE time series can be used in addressing the challenges posed by the increasing share of VRE generation. These capabilities will be demonstrated through three case studies: one about the use of large‐scale VRE generation simulations in energy system analysis, and two about the use of the simulations in power system operation, planning, and analysis.
Language: | English |
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Publisher: | Wiley Periodicals, Inc. |
Year: | 2019 |
ISSN: | 2041840x and 20418396 |
Types: | Journal article |
DOI: | 10.1002/wene.329 |
ORCIDs: | Koivisto, Matti Juhani , Das, Kaushik , Sørensen, Poul , Cutululis, Nicolaos Antonio and 0000-0003-0978-7711 |
Energy systems Power system SDG 7 - Affordable and Clean Energy Simulation Solar Time series Uncertainty Variability Wind
energy system power system simulation solar time series uncertainty variability wind