Development and performance analysis of cubic Bezier functional expansion‐based adaptive filter for grid‐interfaced PV system. (4th March 2021)

• Record Type: Journal Article
• Authors: Arora, Ankita; Singh, Alka
• Is Part Of: International transactions on electrical energy systems. Volume 31:Number 10(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-03-04
• Subjects: adaptive filter -- least mean square algorithm -- photo‐voltaic -- power quality -- shunt compensation; Electric power -- Periodicals; Electric power systems -- Periodicals; Electrical engineering -- Periodicals; 621.3
• DOI: 10.1002/2050-7038.12840
• Languages: English
• ISSNs: 2050-7038

Abstract

Summary: A non‐linear cubic Bezier‐functional expansion‐based adaptive filter (CB‐FEBAF) has been designed for achieving shunt compensation in this article. The algorithm is developed for mitigating current‐based power quality problems such as harmonics in supply current, reactive VAR compensation, active power compensation, power factor improvement, load balancing, and so on. The CB‐FEBAF is developed using Bezier curve expansion of the input signal. The functional expansion‐based real time and online training converges fast and shows fast response over offline techniques such as neural network and neuro‐fuzzy‐based algorithms. The designed CB‐FEBAF controller is trained online using gradient descent least mean square algorithm to extract the fundamental component of the load current. Moreover, the feedforward active power term corresponding to PV power contribution has been added to the developed controller. This helps to overcome the challenges in the integration of renewable energy‐based distribution systems. The proposed controller is compared with non‐adaptive synchronous reference frame theory, backpropagation neural network, and legendre‐based functional neural network. Hardware results prove the multifunctional capabilities of the developed approach. Abstract : No steady state and dynamic oscillations are observed in fundamental component of load current extracted using CB‐FEBAF Filter. The settling time using CB‐FEBAF and SRFT filter is 0.03 second, which is the fastest but SRFT exhibits continuous sustained oscillations. The computational complexity of CB‐FEBAF algorithm is less and the sampling time taken for running the algorithm experimentally is 35 μs, which is the least of all the three. The THD of grid current using CB‐FEBAF filter is 1.34%, which is the lowest. Hence, the performance of the proposed algorithm is far superior. Comparison of proposed algorithm with different control algorithms.