The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction
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School of Systems Engineering, University of Reading, Whiteknights, Reading,Berkshire RG6 6AH, UK
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Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory, Woodstock Road, Oxford OX2 6GG, UK
*
Author to whom correspondence should be addressed.
Energies 2014, 7(6), 3537-3560; https://doi.org/10.3390/en7063537
Received: 27 March 2014
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Revised: 9 May 2014
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Accepted: 15 May 2014
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Published: 30 May 2014
Energy storage is a potential alternative to conventional network reinforcement of the low voltage (LV) distribution network to ensure the grid’s infrastructure remains within its operating constraints. This paper presents a study on the control of such storage devices, owned by distribution network operators. A deterministic model predictive control (MPC) controller and a stochastic receding horizon controller (SRHC) are presented, where the objective is to achieve the greatest peak reduction in demand, for a given storage device specification, taking into account the high level of uncertainty in the prediction of LV demand. The algorithms presented in this paper are compared to a standard set-point controller and bench marked against a control algorithm with a perfect forecast. A specific case study, using storage on the LV network, is presented, and the results of each algorithm are compared. A comprehensive analysis is then carried out simulating a large number of LV networks of varying numbers of households. The results show that the performance of each algorithm is dependent on the number of aggregated households. However, on a typical aggregation, the novel SRHC algorithm presented in this paper is shown to outperform each of the comparable storage control techniques.
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Keywords:
DNO; storage; control; stochastic optimisation; model predictive control; receding horizon; forecast
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MDPI and ACS Style
Rowe, M.; Yunusov, T.; Haben, S.; Holderbaum, W.; Potter, B. The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction. Energies 2014, 7, 3537-3560. https://doi.org/10.3390/en7063537
AMA Style
Rowe M, Yunusov T, Haben S, Holderbaum W, Potter B. The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction. Energies. 2014; 7(6):3537-3560. https://doi.org/10.3390/en7063537
Chicago/Turabian StyleRowe, Matthew, Timur Yunusov, Stephen Haben, William Holderbaum, and Ben Potter. 2014. "The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction" Energies 7, no. 6: 3537-3560. https://doi.org/10.3390/en7063537
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