NDLI: Neural network-based quickprop control algorithm for grid connected solar PV-DSTATCOM system

Content Provider	IET Digital Library
Author	Shukl, Pavitra Singh, Bhim
Abstract	For the optimal operation of grid interfaced solar photovoltaic (PV) system, a neural network-based Quickprop control algorithm is presented in this study. The solar PV array supplies maximum power by utilising an incremental conductance-based maximum power point tracking technique to the grid and the load. When the solar power is not present, during cloudy days or at night, the distribution static compensator (DSTATCOM) operation is performed by harmonics mitigation and reactive power compensation of the loads connected at the point of intersection. The proposed system improves power quality when solar PV power is present, along with active power transfer from solar PV array to grid/load. Thus, a smooth transition is provided between these modes with neural network-based Quickprop control algorithm. Moreover, the neural network-based control technique offers enhanced accuracy due to the combinational neural structure in the estimation process. A laboratory prototype is developed for validation and experimental results corroborate reliable operation for modes of operation as DSTATCOM and grid interfaced PV system at varying load and solar insolation condition.
Starting Page	2522
Ending Page	2530
Page Count	9
ISSN	17521416
Volume Number	13
e-ISSN	17521424
Issue Number	Issue 14, Oct (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rpg/13/14
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.0070
Journal	IET Renewable Power Generation
Publisher Date	2019-07-25
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Active Power Transfer Control of Electric Power System Distribution Static Compensator Operation Grid Interfaced Solar Photovoltaic System Harmonics Incremental Conductance-based Maximum Power Point Tracking Technique Maximum Power Point Trackers Neural Network-based Control Technique Neural Network-based Quickprop Control Algorithm Neurocontrol Neurocontrollers Photovoltaic Power System Power Generation Control Power Grid Power Quality Power Supply Quality Reactive Power Compensation Solar Power Solar Power Stations Solar PV Array Solar PV Power Solar PV-DSTATCOM System Static VAr Compensators
Content Type	Text
Resource Type	Article
Subject	Renewable Energy, Sustainability and the Environment

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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