Intelligent Local Energy Communities: A Multiagent System Approach

Abstract

The electric power grid undergoes a transformation, with many consumers becoming both producers and consumers of electricity. This transformation poses challenges to the existing grid as it was not designed to have reverse power flows. Local energy communities are effective in addressing those issues and engaging grid users to play an active role in the energy transition. Such communities encourage the consumption of the excess of renewable energy locally, which reduces the stress on the grid and the costs for the users. In this paper, we present a multiagent system developed to implement an intelligent local energy community. The multiagent system models the energy grid as a network of computational agents that solve energy flow problems in a coordinated way and use the solutions for controlling flexible loads. The model effectively distributes the tasks among the agents considering the flows of electricity and heat. The Alternative Direction Method of Multipliers determines the agent interaction protocol. The obtained results demonstrate the ability of the multiagent system to automate an intelligent operation of the community while reducing the energy costs and ensuring the grid stability.