Dynamics Analysis of Microgrids Integrated with EV Charging Stations based on Quantum Approximate Optimization Algorithm

A Quantum Approximate Optimization Algorithm (QAOA) is introduced in this paper to analyze the impact of electric vehicle (EV) charging stations on the dynamic operations of microgrids via exploring the maximum power sections in the system. Mathematically, the problem is formulated into a weighted Max-Cut problem. To efficiently address this NP hard problem, quantum computing is leveraged through finding the maximum energy state of the problem's Hamiltonian based on adiabatic theorem. Numerical examples test and verify the effectiveness of QAOA in getting the microgrid system's maximum power sections considering the integration of EV charging stations. This quantum computing will shed light on the development of quantum algorithms for power systems to resolve the challenges that are hard to solve by using classical computers.