An Adaptive Power Oscillation Damping Controller for a Hybrid AC/DC Microgrid

Moudud Ahmed,Arash Vahidnia,Lasantha Meegahapola,Manoj Datta

doi:10.1109/access.2020.2985978

Moudud Ahmed, Arash Vahidnia + Show 2 more

Open Access

https://doi.org/10.1109/access.2020.2985978

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Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 17	License type: CC BY 4.0

Affiliation: RMIT University

Abstract

High penetration of dynamic loads, such as induction motors (IMs) could give rise to sustained voltage/frequency and power oscillations in hybrid AC/DC microgrids during disturbances. Majority of the published literature has investigated these stability issues with aggregated models of IMs in hybrid AC/DC microgrids, which do not properly reflect the actual dynamics of parallel operating IMs; hence, power oscillation damping (POD) controllers must be designed explicitly considering various oscillations induced by parallel operating IMs. This paper proposes an adaptive neuro-fuzzy inference system (ANFIS) based POD controller to damp low-frequency oscillations (LFOs) induced by IMs in hybrid AC/DC microgrids. The proposed supplementary POD controller was embedded to the energy storage system (ESS) controller, which provides additional damping power proportional to the frequency deviation. The following two features namely: 1) ability to adjust the gain based on the frequency deviation, and 2) ability to handle more non-linearity in the system dynamics, make the proposed adaptive ANFIS based POD controller more unique compared to conventional POD controllers. The effectiveness of the proposed ANFIS-POD controller is verified using non-linear dynamic simulations considering a range of disturbances in a hybrid AC/DC microgrid and different combinations of parallel operating IMs. Results indicate improved oscillatory stability performance in the hybrid AC/DC microgrid with the proposed ANFIS-POD controller.

Highlights

Advancement of power electronic converter (PEC) interfaced renewable energy sources (RESs), and energy storage systems (ESSs) have paved the way to a new energy system architecture called ‘‘microgrids’’
SIMULATION RESULTS Non-linear dynamic simulations have been performed to evaluate the effectiveness of the proposed Adaptive neuro-fuzzy inference system (ANFIS) based adaptive power oscillation damping (POD) controller of the ESS considering known & unknown set of induction machine (IM) loading configurations and disturbances in the hybrid alternating current (AC)/direct current (DC) microgrid
TRAINING MODE (26.72% LOAD DISTURBANCES AT THE AC SUB-GRID) Aforementioned, three types of IM configurations are considered in this study and the ANFIS based adaptive POD controller was trained for mode-1 IM loading configuration

Summary

INTRODUCTION

Advancement of power electronic converter (PEC) interfaced renewable energy sources (RESs), and energy storage systems (ESSs) have paved the way to a new energy system architecture called ‘‘microgrids’’. The following two attributes, 1) if the gain of the proportional based POD controllers can be adjusted with the IM loading level, 2) if the proportional controller is effective over a wide-range of operating conditions, can make the LFO damping performance even better under various combinations of IMs in microgrids. This research proposes an ANFIS based POD controller, which autonomously adjusts its gain based on IM loading level and provides significantly improved response over a wide-range of operating conditions. The robustness of the proposed controller is verified by applying various disturbances at both sides of the hybrid AC/DC microgrid with various combinations of parallel operating IMs of distinct power ratings, while total IM loading level remains unchanged.

DESCRIPTION OF THE SIMULATION PLATFORM

ENERGY STORAGE SYSTEM WITH ADAPTIVE POD CONTROLLER

ANFIS-POD CONTROLLER TRAINING

CONCLUSION