Sigma Delta Modulation Controller and Associated Cybersecurity Issues with Battery Energy Storage Integrated with PV-Based Microgrid

Syeda Afra Saiara and Mohd. Hasan Ali ()
Additional contact information
Syeda Afra Saiara: Department of Electrical & Computer Engineering, The University of Memphis, Memphis, TN 38111, USA
Mohd. Hasan Ali: Department of Electrical & Computer Engineering, The University of Memphis, Memphis, TN 38111, USA

Energies, 2024, vol. 17, issue 24, 1-35

Abstract: Battery energy storage systems (BESSs) play a crucial role in integrating renewable energy sources into microgrids. However, robust BESS controllers are needed to carry out this function properly. Existing controllers suffer from overshoots and slow convergence issues. Moreover, as electrical grid networks become increasingly connected, the risk of cyberattacks grows, and traditional physics-based anomaly detection methods face challenges such as reliance on predefined models, high computational demands, and limited scalability for complex, large-scale data. To address the limitations of the existing approaches, this paper first proposes a novel sigma-delta modulation (SDM) controller for BESSs in solar photovoltaic (PV)-connected microgrids. The performance of SDM has been compared with those of the proportional–integral (PI) controller and fuzzy logic controller (FLC). Also, this paper proposes an improved ensemble-based method to detect the false data injection (FDI) and denial-of-service (DoS) attacks on the BESS controller. The performance of the proposed detection method has been compared with that of the traditional ensemble-based method. Four PV-connected microgrid systems, namely the solar DC microgrid, grid-connected solar AC microgrid, hybrid AC microgrid with two BESSs, and hybrid AC microgrid with a single BESS, have been considered to show the effectiveness of the proposed control and detection methods. The MATLAB/Simulink-based results show the effectiveness and better performance of the proposed controller and detection methods. Numerical results demonstrate the improved performance of the proposed SDM controller, with a 35% reduction in AC bus voltage error compared to the conventional PI controller and FLC. Similarly, the proposed SAMME AdaBoost detection method achieves superior accuracy with an F1 score of 95%, outperforming the existing ensemble approaches.

Keywords: battery energy storage system; sigma-delta modulation controller; cyberattacks (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/17/24/6463/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/24/6463/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:17:y:2024:i:24:p:6463-:d:1549935

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().