Study of Energy Loss for Distributed Power-Flow Assignment in a Smart Home Environment

Abstract

Today, renewable energy resources are a critical component of distributed energy systems. However, their intermittent nature makes them unstable energy sources, making them very difficult to use optimally in any energy system. Battery storage is a viable solution for this issue. In this paper, we consider distributed power-flow assignment consisting of unstable power generators, unpredictable power loads, and multiple energy storage systems (ESSs), with different combinations of logical power connections between them. We propose power-flow assignment (PFA) algorithms to deal with single and multiple loads to address the possibility of reducing energy loss and improving distributed power-flow assignment with the presence of ESSs in a smart home environment. Simulation results reveal that the increment of logical power connections between generators, loads, and storage systems can significantly reduce energy loss. The proposed PFA algorithms can reduce energy loss by about 67% compared to a power-flow assignment for which all the generated power is stored in an ESS directly during winter. The results further show that spring has the highest energy loss and stored energy in ESS compared to other seasons.