1. ANN-based grid voltage and frequency forecaster
- Author
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Alessandro Massi Pavan, Nadjwa Chettibi, Adel Mellit, Thomas Feehally, Andrew J. Forsyth, and Rebecca Todd
- Subjects
load forecasting ,power engineering computing ,power grids ,neural nets ,grid quantities ,different time windows ,developed ANNs ,dSPACE-based real-time controller ,forecasters ,ANN-based grid voltage ,frequency forecaster ,forecasting ,battery energy storage system ,low-voltage distribution grid ,optimal management ,artificial neural network-based technique ,Engineering (General). Civil engineering (General) ,TA1-2040 - Abstract
This paper presents a method for the forecasting of the voltage and the frequency at the point of connection between a battery energy storage system installed at The University of Manchester and the local low-voltage distribution grid. The techniques are to be used in a real-time controller for optimal management of the storage system. The forecasters developed in this study use an artificial neural network (ANN)-based technique and can predict the grid quantities with two different time windows: one second and one minute ahead. The developed ANNs have been implemented in a dSPACE-based real-time controller and all forecasters show very good performance, with correlations coefficients >0.85, and mean absolute percentage errors of
- Published
- 2019
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