A new hybrid firefly optimized P-Q and V-f controller coordination for PV-DG-based microgrid stabilization

Abstract

Summary In this paper, optimized controller design for multiple distributed generators (DGs) based microgrid network is discussed, where IEEE 1547 standards are followed for primary photovoltaic DG. According to standards, the primary photovoltaic/auxiliary battery energy storage system is integrated through voltage source converter's feedback controller, with operational modes: active reactive (P − Q) power control for grid synchronized operation and voltage frequency (V‐f) droop control for islanded microgrid. To overcome the inadequacy of conventional controller tuning in a multiple DGs‐based weak microgrid architecture, a new mutation based improved firefly algorithm is proposed in this paper. The worst stability operation is considered for voltage source converter's P‐Q and V‐f coordination during insufficiency in battery energy storage system management. The effectiveness of the proposed technique is validated on MATLAB Editor/ Simulink platform. Further, a hardware‐in‐loop test bench validation is achieved by TMS320 C6713 based DSP Starter Kit and embedded MATLAB coder.

Islanding and power quality disturbance monitoring in microgrid using adaptive cross variational mode decomposition and reduced kernel ridge regression

“…The performance of the proposed adaptive XVMD is further validated through a TMS 320C6713 Starter Kit (DSK) for real time implementation . This DSK kit is a 32‐bit floating digital signal processor with MATLAB coder embedded to it.…”

“…The features are generated from the selected band limited IMF estimated from adaptive VMD and XVMD for different PQ disturbances along with faults and islanding problems . The XVMD based techniques needs simple features to classify the disturbances in less time as compared to the VMD based methods.…”

Bumpless Optimal Control over Multi-Objective Microgrids with Mode-Dependent Controllers

“…When the transition happens, it will cause severely unbalanced harmonic currents and voltage deviations. To enhance the integration of large-scale renewable energy sources, control strategies need to consider both the operation modes and transition behavior to guarantee the continuous stability of microgrids in different status, especially the transient jumps when mode changes occur [3]. Therefore, how to reduce the jumps of the system variables and improve power quality in mode transient behaviors is quite essential and is a very significant research topic [4,5].…”

Distributed energy storage system‐based nonlinear control strategy for hybrid microgrid power management included wind/PV units in grid‐connected operation

“…In addition, a generic-based controller with flexible power flow capability has been proposed for hybrid microgrid in Eajal et al, 39 paying attention to the droop controllability of the distributed resources and bidirectional power flow in the interlinking converters. Several combined adaptive fault-tolerant control algorithms in Vargas-Martinez et al, 43 a hierarchical control included adaptive droop method and a new hybrid firefly optimized P-Q and V-f controller coordination in Satapathy et al 44 and a fuzzy control based on energy management system in Islam et al, 45 have been proposed to control various structures of a microgrid system. Designing the robustness, partial feedback linearization in Mahmud et al 41 and a feed-forward control strategy with internal model robust feedback control in Wang et al 42 has verified the importance of considering the nonlinearity features of microgrid dynamic models.…”

“…Designing the robustness, partial feedback linearization in Mahmud et al 41 and a feed-forward control strategy with internal model robust feedback control in Wang et al 42 has verified the importance of considering the nonlinearity features of microgrid dynamic models. Several combined adaptive fault-tolerant control algorithms in Vargas-Martinez et al, 43 a hierarchical control included adaptive droop method and a new hybrid firefly optimized P-Q and V-f controller coordination in Satapathy et al 44 and a fuzzy control based on energy management system in Islam et al, 45 have been proposed to control various structures of a microgrid system.…”