An optimization Approach Based on the Interior-Point Methodology for the Tertiary Control of Modernized Microgrids

With the rise in popularity of the modernized microgrids (MMGs), the addition of a controller to maximize economic efficiency while taking into account environmental impact is crucial. Tertiary control is at the highest control level, considering economic concerns related to the optimal operation of the microgrid and using a sampling time from minutes to hours; tertiary controls manage the flow of power between the microgrid and the connected grid. In MMGs' tertiary controls, the use of optimization algorithms to minimize an objective function with equality and inequality constraints allows for powerful control over the system. In this paper, the interior-point algorithm is proposed and utilized in order to minimize the required objective. The suggested method is robust against weather conditions and accommodates varying demands in both ac and dc grids. To perform optimization and simulations, MATLAB outputs a lookup table, which can be easily implemented into any system. This is a 2-dimensional array with ac load requirements on the rows and dc load requirements on the columns. Furthermore, due to load capabilities, where the resolution of the system gets too fine, simple algebra can fill in the missing information. Visualization of these results is key to understand what MMG's devices would output for a certain load.