Optimizing Solar Power Using Array Topology Reconfiguration With Regularized Deep Neural Networks-Reference-Cited by-同舟云学术

Optimizing Solar Power Using Array Topology Reconfiguration With Regularized Deep Neural Networks

Published:2023 Issue: Volume:11 Page:7461-7470
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Narayanaswamy Vivek¹^ORCID,Ayyanar Raja¹^ORCID,Tepedelenlioglu Cihan¹^ORCID,Srinivasan Devarajan²^ORCID,Spanias Andreas¹^ORCID

Affiliation:

1. Sensor, Signal and Information Processing (SenSIP) Center, School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USA

2. POUNDRA LLC, Tempe, AZ, USA

Funder

National Science Foundation (NSF) Cyber Physical Systems

NSF Major Research Instrumentation (MRI) Grant

Sensor, Signal and Information Processing (SenSIP) Center

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

https://ieeexplore.ieee.org/ielam/6287639/10005208/10024141-aam.pdf

Reference43 articles.

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3. Irradiance-Driven Partial Reconfiguration of PV Panels

4. Research on an adaptive solar photovoltaic array using shading degree model-based reconfiguration algorithm;liu;Proc Chin Control Decis Conf,2010

5. Batch normalization: Accelerating deep network training by reducing internal covariate shift;ioffe;Proc ICML,2015

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