Integrated resource planning in sustainable energy-based distributed microgrids

This work is devoted to assess the optimal allocation of suitable integrated resources planning for ecofriendly sustainable energy-based hybrid microgrids with distributed generation. The issues due to intermittency of renewable resources and low inertia of these microgrids are alleviated by coordination of suitable demandresponse support (DRS) and virtual-inertia support (VIS) systems. Primarily, 3-distributed unequal microgrids are planned with locally available Solar/Wind/Bioenergy resources including combined storage-based VIS and Electric-Vehicle charging station-based DRS units for supply and demand-side management respectively. The planned system is modelled in MATLAB considering real-time recorded Solar/Wind data with 12-months loading and simulated in different scenarios of source and load variations. The controllers are tuned using a new Quasi-oppositional chaotic Selfish-herd optimization (QCSHO) algorithm, for optimal frequency and voltage regulation in the distributed microgrids, after confirming it's superiority over other contemporary algorithms by comparing the system responses. Then the coordination of frequency, voltage and tie-line loadings are investigated for the projected microgrids without retuning the controllers in 5-extreme scenarios of source and load variations. Lastly, the responses are evaluated for 22-diverse possible allocations of DRS and VIS units in different microgrids. Also the most suitable allocation of integrated resources are recorded after comparing their overall responses.