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Investigating the impact of missing data imputation techniques on battery energy management system

Lookup NU author(s): Dr Mehdi Pazhoohesh, Dr Adib Allahham, Dr Ronnie Das, Professor Sara Walker

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Effective control of energy storage system (ESS), supplying an ancillary service to a grid, requires effective and critical calculation of state‐of‐charge (SoC). Charging and discharging values from battery operations are essential in calculating the efficiency and performance of a storage system. This information can also be a key to understand and forecast peak demand performance. Missing data is a real problem in any operations system, and it appears to be more common within powers systems due to sensor and/or network malfunctioning problems. Missing data imputation techniques have evolved in power systems research using smart meter data, but little research has gone into understanding how missing data can be best handled within storage management systems. This paper builds on a year's worth of charging and discharging data collected from a real 6MW/10MWh lithium‐ion storage battery deployed on the distribution network at Leighton Buzzard, UK. Using R Studio version (1.3.959‐1) open‐source software, eight selected imputation techniques were applied in identifying the best suited technique in replacing various missing data amounts and patterns. Findings from the study open up avenues for discussion and debate in identifying an appropriate imputation technique within the storage management context. The study also provides a pioneering lead in understanding the importance of decomposition in evaluating the right imputation technique.


Publication metadata

Author(s): Pazhoohesh M, Allahham A, Das R, Walker S

Publication type: Article

Publication status: Published

Journal: IET Smart Grid

Year: 2021

Volume: 4

Issue: 2

Pages: 162-175

Print publication date: 01/04/2021

Online publication date: 15/02/2021

Acceptance date: 09/01/2021

Date deposited: 21/02/2021

ISSN (electronic): 2515-2947

Publisher: The Institution of Engineering and Technology

URL: https://doi.org/10.1049/stg2.12011

DOI: 10.1049/stg2.12011


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Funding

Funder referenceFunder name
EP/S016627/1EPSRC

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