The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction

Abstract

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.

Publication DOI: https://doi.org/10.3390/en7063537
Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
Additional Information: This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
Full Text Link:
Related URLs: http://www.mdpi ... 6-1073/7/6/3537 (Publisher URL)
PURE Output Type: Article
Published Date: 2014-05-30
Accepted Date: 2014-05-15
Authors: Rowe, Matthew
Yunusov, Timur
Haben, Stephen
Holderbaum, William (ORCID Profile 0000-0002-1677-9624)
Potter, Ben

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