Utilizing Coalition Games to Optimize Micro-grid Distribution Networks

he concept of micro-grids, one of the cutting-
edge research topics in smart grid, is proposed to ease the
load on the main grid by networking groups of distributed
renewable generators (e.g. solar panels, PHEVs (Plug-in Hy-
brid Electric Vehicles), wind turbines, etc.) and small loads.
While most existing research has focused on system control and
communication technologies inside micro-grids, this paper uses
cooperative game theory to develop novel coalition formation
algorithms for electricity trading based on the micro-grid (MG)
locations and cable power losses. To achieve this purpose, novel
coalition formation algorithms that group together single MGs
into partitions by forming disjoint MG coalitions are formulated.
Every MG has a random energy surplus or demand either to
sell or to buy among themselves within coalitions in order to
reduce the power losses associated with using power from the
main grid. The coalition formation algorithms are evaluated in
terms of 1) average power loss per MG, 2) average coalition
size, 3) average operation and utility calls per MG with dynamic
changes of power surplus over a day. Three game theory methods
(merge-and-split, switch operation, and weak-merge-weak-split
in coalition formations) are evaluated and compared with a
non-cooperative and a brute-force method to form coalitions.
Simulation results show game theory methods always yield good
performance.