Adaptive model-based receding horizon control of interconnected renewable-based power micro-grids for effective control and optimal power exchanges

This paper proposes an Adaptive Model-based Receding Horizon Control Scheme (AMRHCS), which allows taking into consideration the uncertainty power production of renewable energy resources, demand response, the variance of real-time electricity price, load demand and as well as respecting the special constraints for optimal performance and economic benefits of the micro-grids. The essence of this study is to propose a control scheme for the interconnected power microgrids so as to minimize the operating costs of the individual micro-grid, the power purchased by each micro-grid, the pollutant gas emissions, energy procured from the host grid and from the other micro-grids. Therefore, in order for these objectives to be achieved, an adaptive MPC controller is utilized to locate the best patterns for power exchange and state of energy storage system among micro-grids. More so, to investigate the optimal control action of the interconnected power micro-grids under the proposed control framework, we iteratively formulated a finite horizon Mixed Integer Linear Programming (MILP) problem. The MATLAB simulation results demonstrated the superiority of the proposed control technique in terms of excellent performance and economic benefits of the micro-grids.