The paper presents a novel energy management algorithm for residential consumers. The strategy proposed in this work is a combination of the rule based approach considered by the authors and the genetic algorithm. The proposed hybrid algorithm is designed to effectively schedule the virtual and the actual storage facilities present in a residential complex powered by solar panels and main grid. The suggested methodology tries to make the residential complex more autonomous by making it less reliable on the main grid, which is possible by reducing the power import from the utility grid. Further, in this work the virtual storage units are fitted in series with noncritical loads and scheduled based on the instructions given by the consumer and hence there will be maximum consumer satisfaction. Also, the virtual storage units present in the residence can also support the grid by effectively handling the reactive power to a certain extent. The combined usage of virtual storage units like the AC electric springs and the actual storage facilities like the batteries to attain certain benefits for residential consumers is probably the first attempt. A 24 h load curve of a residence consisting of higher constant impedance loads and roof top solar modules is considered for testing the efficiency of the proposed algorithm. The simulation studies required to prove the robustness of the proposed strategy are conducted in MATLAB.