LMSTDE Control for Hybrid Charging Station With Ancillary Services Powered by Variable Speed Wind and PV Array Based Renewable Energy Resources
A hybrid wind/photovoltaic array based grid-tied charging station (CS) is presented in this article. The vector control scheme is used to control the turbine side converter. The grid side converter is controlled through an improved variable step-size (VSS) least mean square time difference estimation algorithm. In the presence of correlated Gaussian noise and a low signal-to-noise ratio, this technique performs good as compared to the conventional techniques. It consists of a VSS with an arctangent function of the correlated value of mean square error. Moreover, it involves a fourth-order cumulant, which improves the performance of the CS. The performance of MGCS is further improved due to its updated weights as it provides the facility of VSS. Moreover, cascaded control is incorporated to control the charging/discharging (C/D) operation of the electric vehicle battery and dc-link voltage regulation. This CS is capable to perform under dynamic conditions, such as variable wind speed, the presence or absence of wind and PV generation, load sudden change, reduced and absence of insolation, and change in C/D. These controls overall enhance the performance and reduce harmonic in the grid current which improves the power quality. The MGCS is validated by using OPAL-RT (OP5600) based experimental laboratory setup.
Authors
- Mukesh Kumar Kirar (ORCID: https://orcid.org/0000-0002-8486-2550)
- Dulichand Jaraniya (ORCID: https://orcid.org/0000-0001-9705-1549)
- Shailendra Kumar (ORCID: https://orcid.org/0000-0002-0132-0538)
Institutions
- Indian Institute of Technology Bhilai (IN)
- Maulana Azad National Institute of Technology (IN)
Publication Details
- Journal
- IEEE Transactions on Industrial Informatics
- Published
- 2024-09-27
- DOI
- https://doi.org/10.1109/tii.2024.3453895
- Citations
- 4
- Primary Topic
- Frequency Control in Power Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.83
Funders
- Science and Engineering Research Board