Multi-Period Optimization of Hybrid Energy Systems Using Mixed Integer Linear Programming

The integration of hybrid energy systems (HES) into the electric power grid is gaining traction due to the need of establishing a clean and sustainable energy system for satisfying the increasing load demand. Such integration enables integration of renewable energy sources in the form of HES that is scalable from small as well as large-scale integration. Nevertheless, the commonly preferred renewable energy sources (RESs), such as, solar and wind energy have significantly limited economic feasibility owing to their unpredictability and intermittency. Energy storage systems (ESSs) are among the key solutions to mitigate the impact of variable renewable energy sources on the grid by acting as an energy buffer. In this paper, a multi-period optimization technique is formulated for the appropriate scheduling of ESSs in a HES that acts as a model of a residential district consisting of several houses with installed PV systems and connections to the main electricity grid. To further verify the method's effectiveness, the results are obtained for both summer and winter season scenarios.