Dissipativity based distributed economic model predictive control for residential microgrids with renewable energy generation and battery energy storage

The combination of renewable energy generation and battery energy storage has been widely recognized as a promising solution to the problems associated with variability of renewable energy in residential microgrid. However, due to the low renewable feed-in tariffs in many countries, microgrid users are generally not motivated to install expensive battery systems if they can only be used to satisfy the objective of grid operator. From this perspective, a microgrid power market that encourages users to install batteries for energy-trading will be helpful for the deployment of batteries. For such circumstances, this paper introduces a user-driven microgrid power market. The possible pricing schemes are discussed and an illustrative price controller is presented. The potential destabilizing effect of the collective trading behavior of users is analyzed. A novel dissipativity based distributed economic model prediction control approach is proposed to allow microgrid users to optimize their own benefits while ensuring the performance and stability of the residential microgrid. A simulation study with photovoltaic energy generation and Vanadium Redox batteries is presented to illustrate the efficacy of the proposed method.