Ever increasing integration of renewable energy sources into the electric power grid and their variability demand networks of local character utilizing advanced control algorithms. Microgrids, defined as objects consisting of locally coupled generators and loads with well defined electrical boundaries and the capacity to work independently with respect to the power grid, are the most common model used to implement power networks ot the new generation. This work presents a method to control power flows within the microgrid using model predictive control. Single dimensional coordination parameters result in the problem structure that enables an efficient use of parametric solutions of partial problems posed for individual network components, which drastically lowers global microgrid-wide problem computation requirements. Quadratic criterion function enables implementation of well adjusted algorithms (Breakpoint Search and Variable Fixing ) used to solve the continuous quadratic knapsack problem. Global micrigrid-wide problem is defined piecewise along n-dimensional hyper-rectangles allowing simple iterative solution method. However, problem structure is best utilized by the single-shot method. Capabilities of the described control method are tested using several scenarios of generator to load power ratios as well as day-long and week-long power profiles in order to properly test short and long term phenomena of the microgrid system that are caused by changes in load and generator power levels.