  The formation of energy communities is pivotal for advancing decentralized
and sustainable energy management. Within this context, Coalition Structure
Generation (CSG) emerges as a promising framework. The complexity of CSG grows
rapidly with the number of agents, making classical solvers impractical for
even moderate sizes (number of agents>30). Therefore, the development of
advanced computational methods is essential. Motivated by this challenge, this
study conducts a benchmark comparing classical solvers with quantum annealing
on Dwave hardware and the Quantum Approximation Optimization Algorithm (QAOA)
on both simulator and IBMQ hardware to address energy community formation. Our
classical solvers include Tabu search, simulated annealing, and an exact
classical solver. Our findings reveal that Dwave surpasses QAOA on hardware in
terms of solution quality. Remarkably, QAOA demonstrates comparable runtime
scaling with Dwave, albeit with a significantly larger prefactor. Notably,
Dwave exhibits competitive performance compared to the classical solvers,
achieving solutions of equal quality with more favorable runtime scaling.
