Scalable multi-agent microgrid negotiations for a transactive energy market

Distributed energy resources are becoming increasingly common and forcing change in conventional energy markets with growing attention given to transactive energy networks that allow power trading between neighboring microgrids or distributed energy resources customers to supplement transactions with an electric utility. This study develops and evaluates a generalizable method for managing energy trading between microgrids in a grid-connected network through multi-agent techniques. The approach is demonstrated for a 3-node network and a 9-node network for a simulated year with hourly load and solar data for each unique microgrid agent. Results are compared against baseline networks without trading enabled to quantify a 3.6% and 5.4% reduction in the levelized cost of energy, respectively, with trading enabled for the 3-node and 9-node cases. Local energy storage capacities are varied to examine impact on the levelized cost of energy and trading behaviors. Results indicate that trading between microgrids reduces the levelized cost of energy for each individual node and the whole network, and that certain trends emerge between agents that allow some microgrids to operate at a lower cost than others.