An AC security constrained unit commitment (AC-SCUC) in the presence of the renewable energy sources (RESs) and parallel flexible AC transmission system (FACTS) devices is conventionally modeled as a deterministic optimization problem to minimize the operation cost of conventional generation units (CGUs) subject to AC optimal power flow (AC-OPF) equations, operation constraints of RESs, parallel FACTS devices, and CGUs. To cope with the uncertainties of load and RES generation, robust and stochastic optimization and linearized formulation have been used to achieve a sub-optimal solution. To achieve the optimal solution, this paper proposed an evolutionary algorithm-based adaptive robust optimization (EA-ARO) approach to solve the non-linear and non-convex optimization problem. A hybrid solver of grey wolf optimization (GWO) and teaching learning-based optimization (TLBO) obtained the robust and reliable optimal solution for the proposed AC-SCUC in the worst-case scenario. Finally, the proposed method was simulated on standard IEEE test systems to demonstrate its capabilities, and the results showed the proposed hybrid solver obtained robust optimal solutions with reduced computation time and standard deviation. Moreover, the numerical results proved the proposed strategy's capabilities of improving the economics of generation units, such as lower operational cost, and technical performance of the transmission networks, such as improved voltage profile and reduced energy losses.INDEX TERMS AC security constrained unit commitment, Evolutionary algorithm-based adaptive robust optimization, Renewable energy sources, Parallel FACTS devices.

This paper tries to address the optimal operation of networked microgrid from the reliability perspective in a correlated atmosphere for the wind generators. The suggested approach performs based on unscented transformation in the form of a nonlinear projection and the heuristic method as the optimizer. The proposed structure is arranged as a complex constraint optimization problem with several targets seeing the varied objectives such as energy not supplied, system interruption frequency, system interruption duration and energy losses. Owing to the interrelated natural surroundings of multi-microgrids, it is a necessity for the microgrids to let the each other access the operation info and with the central unit. In this situation, it is quite wise to provide a secured construction made of the blockchain for the assurance of the reliability and adequate security of data sharing in the microgrids. With the aim of validation of the proposed model, an IEEE standard system is considered and divided into four interrelated microgrids with one side connection to the main grid. The simulation results show the high capability of the proposed framework for enhancing the operation and reliability indices. Moreover, it is seen that almost 0.6% and 0.77% additional cost is imposed to the system in the deterministic framework in the first and second scenarios, respectively.