F
Frede Blaabjerg
Researcher at Aalborg University
Publications - 396
Citations - 5997
Frede Blaabjerg is an academic researcher from Aalborg University. The author has contributed to research in topics: Inverter & Capacitor. The author has an hindex of 22, co-authored 396 publications receiving 3074 citations. Previous affiliations of Frede Blaabjerg include University of Biskra & Central South University.
Papers
More filters
Journal ArticleDOI
High-Efficiency High Step-Up DC–DC Converter With Dual Coupled Inductors for Grid-Connected Photovoltaic Systems
TL;DR: In this paper, the authors proposed a non-isolated high step-up dc-dc converter with dual coupled inductors suitable for distributed generation applications, which inherits shared input current with low ripple, which also requires small capacitive filter at its input.
Journal ArticleDOI
Grid-Synchronization Stability of Converter-Based Resources - An Overview
TL;DR: This paper presents an overview of the synchronization stability of converter-based resources under a wide range of grid conditions, and the small-signal and transient stability of these two operating modes are discussed.
Journal ArticleDOI
Optimal planning of electric vehicle charging station at the distribution system using hybrid optimization algorithm
Abhishek Awasthi,Karthikeyan Venkitusamy,Sanjeevikumar Padmanaban,Rajasekar Selvamuthukumaran,Frede Blaabjerg,Asheesh K. Singh +5 more
TL;DR: Through simulation studies on a real time system of Allahabad city, the superior performance of the aforementioned technique with respect to genetic algorithm and particle swarm optimization in terms of improvement in voltage profile and quality is found.
Journal ArticleDOI
An Experimental Estimation of Hybrid ANFIS–PSO-Based MPPT for PV Grid Integration Under Fluctuating Sun Irradiance
Neeraj Priyadarshi,Sanjeevikumar Padmanaban,Jens Bo Holm-Nielsen,Frede Blaabjerg,Mahajan Sagar Bhaskar +4 more
TL;DR: An adaptive neuro-fuzzy inference system–particle swarm optimization (ANFIS–PSO)-based hybrid MPPT method to acquire rapid and maximal PV power with zero oscillation tracking is introduced.
Journal ArticleDOI
Reinforcement Learning and Its Applications in Modern Power and Energy Systems: A Review
TL;DR: This paper provides a comprehensive literature review of RL in terms of basic ideas, various types of algorithms, and their applications in power and energy systems.