Energy Distribution Optimization Using Variational Quantum Algorithms

Abstract

Quantum computing is emerging as a key tool for enhancing energy management, particularly in areas like resource allocation and renewable energy distribution. Although fault-tolerant quantum computers are still in development, current Noisy Intermediate-Scale Quantum (NISQ) technology shows promise for solving optimization problems using variational quantum algorithms. In this paper, the energy distribution problem for a community with one battery is solved using the Quantum Approximate Optimization Algorithm (QAOA) and the Variational Quantum Eigensolver (VQE) in quantum circuit simulators. This proof of concept provides insights into their potential and limitations for real-world energy applications.