Hybrid BIMASGO approach based optimal scheduling of renewable microgrid with multi-period islanding constraints

In this manuscript, a hybrid system for the optimal microgrid programming with multi-period island constraints was proposed. The proposed hybrid method is the combined execution of the Buyer Inspired Metaheuristic Optimization Algorithm (BIMA) and Shell Game Optimization (SGO); hence it is named as BIMASGO approach. The BIMASGO approach was utilized for optimal microgrid programming and also considerably diminishes the computational load. The main objective of the proposed work is to diminish the cost of operating the microgrid, including the cost of operating the dispatchable units, the cost of transferring power from the main network, and the cost of inconvenience incurred by consumers. The cost of power transfer from the main grid should be positive or negative based on the direction of flow in the transmission line connecting the microgrid to the main grid. A negative cost represents an export of energy to the main grid, appears as an economic benefit for the microgrid. The cost of inconvenience represents the penalty in scheduling adjustable loads outside of consumer-specified time intervals. The constant penalty factor is utilized to prioritize loads with respect to sensitivity when operating at specified time intervals, where a higher value for the penalty factor denotes less flexible load based on time interval settings of the operation. The value of the penalty factor is chosen reasonably higher than the generation cost of the units and the market price. In the proposed system, the BIMASGO approach develops the evaluation procedure to establish the exact schedule of the microgrid combinations depends on the load side of the power range. In the proposed technique, the objective function is defined by the data of the system subject to equality and inequality restrictions. During the programming process, several actual constraints associated with adjustable charges, battery charge/discharge limitations, and the on/off time of dispatchable Distributed Energy Resources (DERs) were considered. The proposed method was implemented in the MATLAB / Simulink site. It was analysed and compared with different existing methods. The calculation time of BIMASGO and the existing methods were also discussed. The calculation time of the proposed method was 4.1 seconds.