A peak reduction scheduling algorithm for storage devices on the low voltage network

Rowe, M., Yunusov, T. ORCID: https://orcid.org/0000-0003-2318-3009, Haben, S., Singleton, C., Holderbaum, W. ORCID: https://orcid.org/0000-0002-1677-9624 and Potter, B. (2014) A peak reduction scheduling algorithm for storage devices on the low voltage network. IEEE Transactions on Smart Grid, 5 (4). pp. 2115-2124. ISSN 1949-3053 doi: 10.1109/TSG.2014.2323115

Abstract/Summary

Reinforcing the Low Voltage (LV) distribution network will become essential to ensure it remains within its operating constraints as demand on the network increases. The deployment of energy storage in the distribution network provides an alternative to conventional reinforcement. This paper presents a control methodology for energy storage to reduce peak demand in a distribution network based on day-ahead demand forecasts and historical demand data. The control methodology pre-processes the forecast data prior to a planning phase to build in resilience to the inevitable errors between the forecasted and actual demand. The algorithm uses no real time adjustment so has an economical advantage over traditional storage control algorithms. Results show that peak demand on a single phase of a feeder can be reduced even when there are differences between the forecasted and the actual demand. In particular, results are presented that demonstrate when the algorithm is applied to a large number of single phase demand aggregations that it is possible to identify which of these aggregations are the most suitable candidates for the control methodology.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/36953
Identification Number/DOI	10.1109/TSG.2014.2323115
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
Uncontrolled Keywords	DNO; LV network; energy storage; forecast; load uncertainty; smart grid
Publisher	IEEE
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