Accessibility navigation


Evaluating the effectiveness of storage control in reducing peak demand on low voltage feeders

Yunusov, T. ORCID: https://orcid.org/0000-0003-2318-3009, Haben, S., Lee, T., Ziel, F., Holderbaum, W. and Potter, B. (2017) Evaluating the effectiveness of storage control in reducing peak demand on low voltage feeders. In: CIRED 2017, 12-15 Jun 2017, Glasgow, UK, pp. 1745-1749.

[img]
Preview
Text (Open Access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading.

1MB
[img] Text - Accepted Version
· Restricted to Repository staff only

750kB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Official URL: http://doi.org/10.1049/oap-cired.2017.0626

Abstract/Summary

Uptake of Low Carbon Technologies is likely to lead to increased demand in distribution networks and consequently could impose additional stress on the networks. Battery Energy Storage Systems (BESS) are identified as a feasible alternative to traditional network reinforcement. This paper analyses two BESS scheduling algorithms (Model Predictive Control (MPC) and fixed schedule) supplied with forecasts from five methods for predicting demand on 100 low voltage feeders. Results show that forecasting feeders with higher mean daily demand produces lower mean absolute errors and better peak demand reduction. MPC with simple error improves peak reduction over fixed schedule for feeders with lower mean daily demand.

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:Interdisciplinary centres and themes > Centre for Technologies for Sustainable Built Environments (TSBE)
Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics > Centre for the Mathematics of Human Behaviour (CMOHB)
Interdisciplinary centres and themes > Energy Research
Science > School of the Built Environment > Energy and Environmental Engineering group
ID Code:69539
Additional Information:Volume 2017, Issue 1

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation