Biogeography Based Optimal State Feedback Controller for Frequency Regulation of a Smart Microgrid
In this paper an isolated microgrid comprising both controllable and uncontrollable sources, such as solar, wind, diesel generator, fuel cell, aqua-electrolyser and hydrogen storage is modeled. After discussing the modeling of the power system and different generating units, two kinds of control approaches have been used and the results have been compared to each other. Firstly, PI controllers have been implemented for controllable sources to damp the frequency oscillations. This control approach is a kind of local approach and just uses the data locally. Secondly, Optimal LQR control algorithm is employed for controlling the system using Particle Swarm Optimization. This control is a full state feedback control which uses all the state of the system and tries to minimize the objective function. PSO technique has been applied to come up with the best control matrices such that the frequency oscillation due to a disturbance in a microgrid is minimized. To establish an efficient resource management strategy, a central controller takes the decisions based on the status of the loads and sources. The status is obtained with the help of multi-agent concept (treating each load and source as an agent) through internet using User Datagram Protocol/Internet Protocol (UDP/IP). The decisions are transmitted to the controllable sources to regulate their power output for damping of frequency deviations following a disturbance. The proposed control approach is tested in presence of different frequency changes in the system including cyber attack effects. The proposed control method is improved by optimizing the frequency sending rate and tested in case of cyber intrusions or malfunctions.