ANFISPID-based voltage regulation strategy for grid-tied renewable DG system with ESS
Mahmud, Nasif, Zahedi, Ahmad, and Mahmud, Asif (2016) ANFISPID-based voltage regulation strategy for grid-tied renewable DG system with ESS. In: Proceedings of the IEEE Innovative Smart Grid Technologies Conference. pp. 81-86. From: ISGT-Asia 2016: IEEE Innovative Smart Grid Technologies Conference, 28 November - 1 December 2016, Melbourne, VIC, Australia.
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Abstract
In this paper, the voltage regulation problem at point of common coupling (PCC) of low voltage grid-tied renewable distributed generation (DG) system has been addressed. This paper proposes and evaluates the performance of a novel intelligent adaptive neuro-fuzzy inference system (ANFIS) based proportional-integral-derivative (PID) control scheme to regulate the voltage of three phase grid connected renewable DG system under any nonlinear and fluctuating operating conditions. The proposed ANFIS-based PID control scheme dynamically controls the grid interfacing inverter of solar photovoltaic system (DG) to inject/absorb appropriate reactive power to regulate the voltage at PCC in cases of versatile operating conditions like insufficient, no or excess generated PV power comparing to dynamic load demands, sudden short term voltage fluctuations caused by passing clouds or large load start etc. Also, a state-based energy management system has been proposed to control the charge/ discharge of an energy storage system (ESS) to balance the system power generation and load demand. The proposed intelligent control schemes are developed and simulated in MATLAB/ Simulink environment and their dynamic performance is compared with the conventional PID control schemes.
Item ID: | 47351 |
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Item Type: | Conference Item (Research - E1) |
ISBN: | 978-1-5090-4303-3 |
Keywords: | ANFIS, solar photovoltaic, voltage regulation, distribution networks, distributed generation |
Date Deposited: | 15 Feb 2017 07:40 |
FoR Codes: | 40 ENGINEERING > 4007 Control engineering, mechatronics and robotics > 400702 Automation engineering @ 100% |
SEO Codes: | 85 ENERGY > 8505 Renewable Energy > 850504 Solar-Photovoltaic Energy @ 100% |
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