A novel virtual inertia emulation technique for the single phase electric vehicle charging topology. (July 2022)

• Record Type: Journal Article
• Authors: Bhowmik, Pritam; Satpathy, Priya Ranjan; Thanikanti, Sudhakar Babu; Jana, Narendranath
• Is Part Of: Computers & electrical engineering. Volume 101(2022)
• Publication Date: 2022-07
• Subjects: Power converter -- Vehicles -- Power system dynamic stability -- Transient response; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2022.108114
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: The paper proposes a single phase virtual inertia emulation technique. The emulation technique is based on the concept of virtual two phase space vector mechanism. The gain tuning is achieved through the Self-tuned PIC. Prototyped in ARM Cortex A-72 based architecture. Abstract: The fast frequency stability limit is generally low in a short distribution system with a high penetration of renewables. The study proposes a single-phase virtual inertia emulation technique for residential slow charging systems to improve transient performance in islanded networks serving as an additional vehicle to the grid scheme. The proposed emulation technique is based on the novel notion of using a virtual two-phase space vector to ride over the frequency excursion propensity in a single-phase architecture. For the computation of the instantaneous active power reference to correctly alter network behavior through the control loop, the Self-Tuned Fractional Order Proportional Integral (ST-FOPI) controller has been proposed. The suggested ST-FOPI-based virtual inertia emulation technique's performance was tested on an ARM Cortex-A72 processor-driven hardware platform. The real-time performance gain is remarkable when compared to the typical emulation technique. Graphical abstract: Image, graphical abstract