As autonomous tiling devices begin to perform floor cleaning, agriculture harvesting, surface painting tasks, with minimal or no human intervention, a new challenge arises: these devices also need to be energy efficient and be constantly aware of the energy expenditure during deployments. Typical approaches to this end are often limited to fixed morphology robots with little or no consideration for reconfiguring class of robots. The main contribution of the paper is an energy estimation scheme that allows estimating the energy consumption when a tetromino inspired reconfigurable floor tiling robot, hTetro moves from one configuration to another for completing the area covering task. To this end, the proposed model applying the Newton-Raphson algorithm in combination with Pulse width modulation (PWM)-H bridge to characterize the energy cost associated with locomotion gaits across all valid morphologies and identify optimal area coverage strategy among available options is presented. We validate our proposed approach using an 8’ × 8’ square testbed where there exist 12 possible solutions for complete area coverage however with varying levels of energy cost. Then, we implemented our approach to our hTetro platform and conducted experiments in a real-life environment. Experimental results demonstrate the application of our model in identifying the optimal area coverage strategy that has the least associated energy cost.