Smart City Gnosys
Smart city article details
| Title | Renewable Energy Based Hybrid Power Quality Compensator Based On Deep Learning Network For Smart Cities |
|---|---|
| ID_Doc | 45054 |
| Authors | John G.K.; Sindhu M.R.; Nambiar T.N.P. |
| Year | 2023 |
| Published | Artificial Intelligence and Machine Learning in Smart City Planning |
| DOI | http://dx.doi.org/10.1016/B978-0-323-99503-0.00017-X |
| Abstract | Distributed generation, electric vehicle charging stations, critical and sensitive loads with varying supply quality requirements are integral parts of smart cities. The system is complicated in nature, due to the uncertain power generation and power demand, which necessitates smart and intelligent compensation strategies to alleviate power quality issues. Critical and sensitive equipment is used in hospitals, data centers, automation industries, banking services, etc., to optimize electrical power usage and perform system needs with optimum reliability. To provide these systems with stable, secure, and high-quality power, a hybrid power quality compensator is proposed which improves power quality at the point of common coupling with suitable mode of compensation. Renewable energy-based hybrid power quality compensator (ReHPQC)-based on deep learning networks is presented in this paper. The case study conducted on CIGRE low-voltage microgrid with multifeeders demonstrates the importance of this system for smart microgrid. © 2023 Elsevier Inc. All rights reserved. |
| Author Keywords | Energy management; Energy resource; Energy storage; Energy systems; Engineering; Power engineering |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
35884  | 0.871 | Rahul R.; Choudhary B. | Machine Learning And Deep Learning Based Hybrid Approach For Power Quality Disturbances Analysis | Proceedings of 3rd IEEE International Conference on Computational Intelligence and Knowledge Economy, ICCIKE 2023 (2023) |
| 42556 | 0.862 | Miron A.; Cziker A.C.; Ungureanu S.; Beleiu H.G.; Darab C.P. | Power Quality Prediction At Consumers Using A Hybrid Knowledge-Based Approach | Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023 (2023) |
| 42563 | 0.861 | Rahul; Gangadharappa M.; Kharola A. | Power Signal Disturbances Analysis Based On Transfer Learning In Deep Architecture | Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022 (2023) |
| 8065 | 0.851 | Baig M.A.A.; Ratyal N.I.; Amin A.; Jamil U.; Liaquat S.; Khalid H.M.; Zia M.F. | An Ensemble Deep Cnn Approach For Power Quality Disturbance Classification: A Technological Route Towards Smart Cities Using Image-Based Transfer | Future Internet, 16, 12 (2024) |