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RSS FeedsEnergies, Vol. 11, Pages 2514: Data-Driven Risk Analysis for Probabilistic Three-Phase Grid-Supportive Demand Side Management (Energies)

 
 

27 september 2018 01:00:08

 
Energies, Vol. 11, Pages 2514: Data-Driven Risk Analysis for Probabilistic Three-Phase Grid-Supportive Demand Side Management (Energies)
 




Along with the emerging development of demand side management applications, it is still a challenge to exploit flexibility realistically to resolve or prevent specific geographical network issues due to limited situational awareness of the (unbalanced low-voltage) network as well as complex time dependent constraints. To overcome these problems, this paper presents a time-horizon three-phase grid-supportive demand side management methodology for low voltage networks by using a universal interface that is established between the demand side management application and the monitoring and network analysis tools of the network operator. Using time-horizon predictions of the system states that the probability of operational limit violations is identified. Since this analysis is computationally intensive, a data driven approach is adopted by using machine learning. Time-horizon flexibility is procured, which effectively prevents operation limit violation from occurring independent of the objective that the demand side management application has. A practical example featuring fair power sharing demonstrates the effectiveness of the presented method for resolving over-voltages and under-voltages. This is followed by conclusions and recommendations for future work.


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11 viewsCategory: Biophysics, Biotechnology, Physics
 
Energies, Vol. 11, Pages 2515: Voltage Harmonic Suppression by Means of Grid-Connected Converters Using only Local Measurements (Energies)
Energies, Vol. 11, Pages 2513: CFD Steady Model Applied to a Biomass Boiler Operating in Air Enrichment Conditions (Energies)
 
 
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