A New Decentralized Robust Secondary Control for Smart Islanded Microgrids

Abstract

Dealing with the islanded operation of a microgrid (MG), the micro sources must cooperate autonomously to regulate the voltage and frequency of the local power grid. Droop controller-based primary control is a method typically used to self-regulate voltage and frequency. The first problem of the droop method is that in a steady state, the microgrid’s frequency and voltage deviate from their nominal values. The second concerns the power-sharing issue related to mismatched power line impedances between Distribution Generators (DGs) and MGs. A Secondary Control Unit (SCU) must be used as a high-level controller for droop-based primary control to address the first problem. This paper proposed a decentralized SCU scheme to deal with this issue using optimized PI controllers based on a Genetic Algorithm (GA) and Artificial Neural Networks (ANNs). The GA provides the appropriate adjustment parameters for all adopted PI controllers in the primary control-based voltage and current control loops and SCU-based voltage and frequency loops. ANNs are additionally activated in SCUs to provide precise online control parameter modification. In the proposed control structure, a virtual impedance method is adopted in the primary control scheme to address the power-sharing problem of parallel DGs. Further, in this paper, one of the main objectives includes electricity transmission over long distances using Low-Voltage DC Transmission (LVDCT) systems to reduce power losses and eradicate reactive power problems. Voltage Source Inverters (VSIs) are adopted to convert the DC electrical energy into AC near the consumer loads. The simulation results illustrated the feasibility of the proposed solutions in restoring voltage and frequency deviations, reducing line losses, as well as achieving active and reactive power sharing among the DGs connected to the MG.

Finite Control Set MPC for Voltage and Frequency Stabilization in Islanded AC Microgrids with Line Impedance Consideration and Enhanced Power Sharing Control

“…The accurate tuning of proportional-integral (PI) gains is a critical and challenging task, particularly with respect to guaranteeing improved system performance and power quality during the operation of DG units and load changes. To address this issue, an improved SC mechanism is proposed [32]. This control strategy employs an optimized PI controller based on a combination of genetic algorithms (GA) and artificial neural networks (ANNs).…”

A Novel Cooperative Control Technique for Hybrid AC/DC Smart Microgrid Converters

“…Regarding of the control techniques of the inverters, Dead Beat (DB), hysteresis, Proportional Integral (PI), and PR controllers are the main control techniques for incorporating DG equipped with inverters into the power grid [21][22][23][24][25][26][27]. Reference [21] proposed a hysteresis control for grid connected inverter in MG.…”

“…Although it is quite complex and highly reliant on system parameters, it is nonetheless very effective [22]. Among the numerous benefits of the PI controller are improved wave shaping, immediate control, and a constant switching frequency of the power inverter during its application in several grid-connected MGs [25][26][27]. However, the PI also has a downside of steady-state error.…”

Consensus-Based Intelligent Distributed Secondary Control for Multiagent Islanded Microgrid

“…Since the frequency is a global system quantity, P-f droop allows for real power to be shared among DGs based on their individual power ratings. Reactive power sharing is disrupted by the Q-V method because: (1) voltage parameter is local, unlike frequency [1]; (2) the network's reactive power requirement depends on loads, network confguration, and transmission line parameters [1]; and (3) the resistive nature of the transmission lines in the network makes the active power and reactive power mutually dependent [2]. Improper sharing of the reactive power among DGs can result in voltage and frequency deviations, unanticipated load curtailment, degraded power quality, and protection failures of DGs, all of which impact the MG stability.…”