Optimal Voltage–Frequency Regulation in Distributed Sustainable Energy-Based Hybrid Microgrids with Integrated Resource Planning

This work is the earliest attempt to propose an integrated resource planning for distributed hybrid microgrids considering virtual-inertia support (VIS) and demand-response (DRS) systems. Initially, three-distributed sustainable energy-based unequal are envisioned with availability of solar/wind/bioenergy resources. In order overcome effects intermittency in renewable resources low inertia, each microgrid incorporated DRS VIS units demand- supply-side management, respectively. The proposed system simulated MATLAB real-time recorded solar/wind data realistic loading 12 months. A novel quasi-oppositional chaotic selfish-herd optimization (QCSHO) algorithm by hybridizing quasi-opposition-based learning linear search techniques into optimization, optimal regulation voltage frequency microgrids. Then, responses compared 7 algorithms 5 error functions tune PID controllers’ gains, which confirmed superiority QCSHO over others. study proceeds investigate voltage, frequency, tie-line power coordination extreme scenarios source load variations without retuning controllers. Finally, analyzed 10 different possible allocation find most suitable combinations, results recorded.