Traceability of Power Quality Pollution in Smelting Industry Event Traceability Based on Steady State Characteristic Index

The paper focuses on the experimental results of a series of tests performed on a hybrid electrical source. The hybrid generator is made up of a fuel cell primary source equipped with an ultracapacitor storage device. The paper presents an examination of the steady-state and transient performance of the hybrid fuel cell-ultracapacitor source in terms of power quality. The aim is to investigate on fuel cell-ultracapacitor source’s behavior to feed pulsing loads.

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Performance enhancement of grid-interfaced inverter using intelligent controller

Measurement and Control ◽

10.1177/0020294019879171 ◽

2020 ◽

Vol 53 (3-4) ◽

pp. 551-563 ◽

Cited By ~ 1

Author(s):

Sushma Kakkar ◽

Rajesh Kumar Ahuja ◽

Tanmoy Maity

Keyword(s):

Steady State ◽

Power Quality ◽

Reactive Power ◽

Performance Enhancement ◽

Parametric Uncertainties ◽

Inference Control ◽

Integral Control ◽

Proportional Integral ◽

Active And Reactive Power ◽

Proportional Integral Control

The high-performance grid-interfaced inverters are in demand as they are rapidly used in renewable energy systems. The main objective of grid-interfaced inverters is to inject high-quality active and reactive power with sinusoidal current. Many control schemes have been proposed earlier in the literature, but the operation under parametric uncertainties has not been given much attention. In this article, an adaptive network–based fuzzy inference control algorithm for a three-phase grid-interfaced inverter under parametric uncertainties is proposed. The main purpose of the proposed technique is to enhance the response time, decrease the steady-state oscillation in the injected active and reactive power and enhance the power quality even with parametric uncertainties. For assessment and evaluation reason, the conventional proportional–integral control is compared with the proposed controller. For a fair comparison, the gain setting for the proportional–integral control is obtained by Particle swarm optimization algorithm. The suggested system is developed and simulated in MATLAB/Simulink. Simulation results demonstrate that both the controllers work well to regulate the powers to required values, even with parametric variations. However, the proposed control demonstrates superiority in comparison to conventional proportional–integral control in terms of speedy response, decreased steady-state fluctuations, better power quality and increased robustness. The rise time and fluctuations in the per-unit active and reactive power are much less with the proposed control. Total harmonic distortion of the injected current and grid current are significantly better than the conventional proportional–integral control.

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Steady-State Power Quality Synthetic Evaluation Based on the Triangular Fuzzy BW Method and Interval VIKOR Method

Applied Sciences ◽

10.3390/app10082839 ◽

2020 ◽

Vol 10 (8) ◽

pp. 2839

Author(s):

Jidong Wang ◽

Naixing Ye ◽

Leijiao Ge

Keyword(s):

Steady State ◽

Power Systems ◽

Power Quality ◽

Fossil Fuels ◽

Evaluation Method ◽

State Power ◽

Triangular Fuzzy Number ◽

National Standards ◽

Vikor Method ◽

Synthetic Evaluation

With the increasing consumption of fossil fuels, renewable sources power generation has attracted more and more attention. However, with the integration of renewable energy and a large number of non-linear loads in power systems, several power quality problems are attracting the attention of researchers. At present, only national standards for an individual power quality index have been set in China. When evaluating power quality in practice, the individual standard cannot reflect a comprehensive level of power quality. In this paper, a synthetic evaluation method for steady-state power quality is proposed. Firstly, the traditional BW (best-worst) method is improved based on the triangular fuzzy number, to obtain the interval weight of each evaluation index. Then, the interval VIKOR method is used to evaluate the steady-state power quality monitoring data, and the final evaluation results are obtained. The validity of the proposed method is verified by the experimental data from the dynamic simulation laboratory of Tianjin University.

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