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Parameter Improved Particle Swarm Optimization Based Direct-Current Vector Control Strategy for Solar PV SystemNAMMALVAR, P. , RAMKUMAR, S.
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solar energy, particle swarm optimization, optimal control, power conditioning, microgrids
power(22), control(10), systems(7), energy(7), grid(6), current(6), voltage(5), system(5), generation(5), connected(5)
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About this article
Date of Publication: 2018-02-28
Volume 18, Issue 1, Year 2018, On page(s): 105 - 112
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.01013
SCOPUS ID: 85043243615
This paper projects Parameter Improved Particle Swarm Optimization (PIPSO) based direct current vector control technology for the integration of photovoltaic array in an AC micro-grid to enhance the system performance and stability. A photovoltaic system incorporated with AC micro-grid is taken as the pursuit of research study. The test system features two power converters namely, PV side converter which consists of DC-DC boost converter with Perturbation and Observe (P&O) MPPT control to reap most extreme power from the PV array, and grid side converter which consists of Grid Side-Voltage Source Converter (GS-VSC) with proposed direct current vector control strategy. The gain of the proposed controller is chosen from a set of three values obtained using apriori test and tuned through the PIPSO algorithm so that the Integral of Time multiplied Absolute Error (ITAE) between the actual and the desired DC link capacitor voltage reaches a minimum and allows the system to extract maximum power from PV system, whereas the existing d-q control strategy is found to perform slowly to control the DC link voltage under varying solar insolation and load fluctuations. From simulation results, it is evident that the proposed optimal control technique provides robust control and improved efficiency.
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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