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Showing 2 results for Wu

A. Azghandi, S. M. Barakati, B. Wu,
Volume 14, Issue 4 (December 2018)

A voltage source inverter (VSI) is widely used as an interface for distributed generation (DG) systems. However, high-power applications with increasing voltage levels require an extra power converter to reduce costs and complications. Thus, a current source inverter (CSI) is used. This study presents a precise phasor modeling and control details for a VSI-based system for DG and compares it with a CSI-based system. First, the dynamic characteristics of the system based on amplitude-phase transformation are investigated via small signal analysis in the synchronous reference frame. Moreover, the performance of the grid-connected system is determined by adopting the closed-loop control method based on the obtained dynamic model. The control strategies employ an outer active-power loop cascaded with an inner reactive-power loop, which the inner loop is a single-input single-output system without coupling terms. The sensitivity analysis of the linearized model indicates the dynamic features of the system. The simulation results for the different conditions confirm proposed model and design of the controller.

I. K. Okakwu, O. E. Olabode, D. O. Akinyele, T. O. Ajewole,
Volume 19, Issue 2 (June 2023)

This paper evaluates the wind potential of some specified locations in Nigeria, and then examines the response of wind energy conversion systems (WECSs) to this potential. The study employs eight probability distribution (PD) functions such as Weibull (Wbl), Rayleigh (Ryh), Lognormal (Lgl), Gamma (Gma), Inverse Gaussian (IG), Normal (Nl), Maxwell (Mwl) and Gumbel (Gbl) distributions to fit the wind data for nine locations in Nigeria viz. Kano, Maiduguri, Jos, Abuja, Akure, Abeokuta, Uyo, Warri and Ikeja. The paper then uses the maximum likelihood (ML) method to obtain the parameters of the distributions and then evaluates the goodness of fit for the PD models to characterize the locations’ wind speeds using the minimum Root Mean Square Error (RMSE). The paper analyses the techno-economic aspect of the WECSs based on the daily average wind speed; it evaluates the performance of ten 25 kW pitch-controlled wind turbines (WT1 – WT10) with dissimilar characteristics for each location, including the cost/kWh of energy (COE) and the sensitivity analyses of the WECSs. Results reveal that Ryh distribution shows the best fit for Kano, Jos, Abeokuta, Uyo, Warri and Ikeja, while the Lgl distribution shows the best fit for Maiduguri, Abuja and Akure due to their minimum RMSE. WT7 achieves the least COE ranging from $0.0328 in Jos to $4.4922 in Uyo and WT5 has the highest COE ranging from $0.1380 in Ikeja to $53.371 in Uyo. The paper also details the sensitivity analysis for the technical and economic aspects.

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