A priority-based seven-layer strategy for energy management cooperation in a smart city integrated green technology

The notion of smart city is based on using both bidirectional power and data flows. For that, designing a persuasive control model for power flow becomes a big and crucial part in a smart city to optimize the power balance between production and consumption. So, a seven-layer smart city energy management strategy (SLSCEMS) for multiple home energy cooperation is presented in this paper. The optimised aims of this strategy are smoothing the smart homes power demand profiles, reducing the electricity bills (E.B), and gaining a total free charging of Plug-in Electric Vehicles (PEVs). This approach has been designed as hierarchic local and global layers. The first one is divided into three layers that aim to transfer the energy between each smart home and its own Renewable Energy sources (RES) and PEVs. The second one is split into four layers that aim to transfer the energy between each smart home and its PEVs, the neighboring homes and their RES, and the smart grid. All optimised layers are based on Particle Swarm Optimization (PSO) algorithm. The proposed strategy is evaluated in a city that contains one hundred homes classified into five categories, each category is designated by its power profile and its flexible number of RESs and PEVs. Simulation results show a decrease in the daily E.B of 26.24%, 2.42%, 60.33%, 29.51%, and 2.38% respectively of the five categories. So, these numerical results prove that the proposed SLSCEMS has considerable efficiency.

Automated summary

This paper proposes a seven-layer smart city energy management strategy to optimize power flow and achieve smooth power demand profiles, reduce electricity bills, and enable free charging of electric vehicles. The strategy is based on the Particle Swarm Optimization algorithm and utilizes a hierarchical structure to transfer energy between smart homes, renewable energy sources, and electric vehicles. Simulation results demonstrate significant efficiency of the proposed strategy.