The real-time optimisation of DNO owned storage devices on the LV network for peak reduction

Rowe, M., Yunusov, T. ORCID: https://orcid.org/0000-0003-2318-3009, Haben, S., Holderbaum, W. ORCID: https://orcid.org/0000-0002-1677-9624 and Potter, B. (2014) The real-time optimisation of DNO owned storage devices on the LV network for peak reduction. Energies, 7 (6). pp. 3537-3560. ISSN 1996-1073 doi: 10.3390/en7063537

Abstract/Summary

Energy storage is a potential alternative to conventional network reinforcementof the low voltage (LV) distribution network to ensure the grid’s infrastructure remainswithin its operating constraints. This paper presents a study on the control of such storagedevices, owned by distribution network operators. A deterministic model predictive control (MPC) controller and a stochastic receding horizon controller (SRHC) are presented, wherethe objective is to achieve the greatest peak reduction in demand, for a given storagedevice 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-pointcontroller and bench marked against a control algorithm with a perfect forecast. A specificcase study, using storage on the LV network, is presented, and the results of each algorithmare 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.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/36756
Item Type	Article
Refereed	Yes
Divisions	Science > School of the Built Environment > Construction Management and Engineering Life Sciences > School of Biological Sciences > Department of Bio-Engineering Interdisciplinary centres and themes > Energy Research Science > School of the Built Environment > Energy and Environmental Engineering group
Publisher	MDPI Publishing, Basel
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