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In this paper, parallel ant-lion optimizer (ALO) and artificial neural network (ANN) for the micro-grid (MG) connected system with AC load is proposed. The proposed algorithm is the combined performance of ALO type I and II algorithms. The aim of the proposed algorithm is to increase the power transfer capability between the source and load sides and to offer several benefits like enhanced predicting capability, degradation in complexity, and randomization. ALO type I is utilized for active power controller parameter optimization with enhanced searching behaviour like crossover and mutation. Using the ALO type II, the reactive power controller parameters’ optimization is performed with online predictor ANN. The exact control signals of the power controller are determined based on the system power deviations using the parallel operation of the algorithms. With the performance of the proposed controller, the power exchange is enhanced and ensured between the sources to load. The implementation is done by the MATLAB/Simulink platform. The performance of the proposed method is analysed using comparison analysis with the existing techniques.

PALONN: Parallel Ant Lion Optimizer and Artificial Neural Network for Power Flow Control of the Micro Grid-Connected System