Modeling Energy Community Operations as a QUBO Problem for Quantum Optimization

Abstract

Energy communities are collectives that manage their own production, distribution, and consumption of energy, usually from renewable sources. To increase efficiency and sustainability, the scheduling of the loads on the basis of the user needs, the electricity prices, the availability of local renewable energy and the battery storage capacity must be optimized. Quantum computing, leveraging principles like superposition and entanglement, offers new computational power for complex optimization tasks. This paper lays the basis for exploring the potential of quantum computing in optimizing the operation of energy communities by modeling the problem as a Quadratic Unconstrained Binary Optimization (QUBO) problem.