FPGA control system technology for integrating the PV/wave/FC hybrid system using ANN optimized by MFO techniques
Bibliographic Data
| ID | 21234898 |
|---|---|
| Authors | M Talaat (0000-0001-5976-7810, Zagazig University, corresponding author), Adel Alblawi (0000-0002-0674-9421, Shaqra University), M Tayseer (0000-0001-8234-7929, Zagazig University), M H Elkholy (Zagazig University) |
| Year | 2022 |
| Volume | 80 |
| Pages | 103825 |
| Publication date | 2022-05-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sustainable Cities and Society (JOURNAL) |
| Journal identifiers | ISSN: 2210-6707 • E-ISSN: 2210-6715 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.scs.2022.103825 |
| OpenAlex | W4220780979 |
| Language | EN |
| Citations received | 1 |
| References cited | 36 |
Electrical engineering · Embedded system · Field-programmable gate array · Hybrid system · Microcontroller · Renewable energy · Computer Science · Energy Harvesting in Wireless Networks · Engineering · Microgrid Control and Optimization · Photovoltaic System Optimization Techniques
Techno-economic analysis of off-grid PV/wind/fuel cell hybrid system combinations with a comparison of regularly and seasonally occupied households
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Implementation of solar energy in smart cities using an integration of artificial neural network, photovoltaic system and classical Delphi methods
| Citations per year | 0.25 |
|---|---|
| Citation span | 2022 - 2022 (1) |
| Highly cited | No |