Multi-agent-based energy management for a fully electrified residential consumption

Abstract

This paper aims to employ multi-agent-based energy management and optimization to design a set of interconnected micro-grids with the ability to exchange electricity with the main grid. Initially, the micro-grid components, their governing mathematical model, and the pricing mechanism are introduced. In the next step, the energy management framework is constructed based on three objective functions: minimizing electricity costs, maximizing renewable energy penetration, and providing maximum possible satisfaction. A multi-agent system composed of several operational agents is presented. To evaluate the applicability of the proposed approach case study was conducted. The proposed multi-agent-based optimization is employed to define the most promising solution for the energy system. The solution contains PV power installation, battery storage capacity, home appliances operational schedule, and the energy flow between micro-grids and the main grid. Simulation results indicated that the average annual earnings of the households from interacting with the main grid could be enhanced by 32.9% after performing the optimization procedure. Finally, variations in the distribution classes and investment costs were conducted to observe the effect of changing presumed parameters. Varying the investment costs revealed that for PV-specific investment costs greater than 1500 $/kW, employing solar power generation is not favorable from an economic point of view. However, it should be noted that the required PV installation capacity and hence the required investment strongly depends on the available solar energy. As a result, for regions with smaller annual irradiation, the configuration of the energy system may be quite different. To sum up, the study's overall results show that the proposed multi-agent optimization framework provides a powerful tool to design and operate energy systems composed of several energy sources and versatile users.