Quantum Inspired DC Optimal Power Flow Under Frequency Constraint

This study uses quantum-inspired techniques to ad-dress the DC optimal power flow problem considering frequency constraints. Although numerous analytical and data-driven meth-ods have been developed to solve DC-OPF under stability security constraints, this problem has never been addressed in the context of quantum computing. This paper proposed a novel algorithm based on quantum computing principles that improves both the accuracy and efficiency of solving DC-OPF solutions while dealing with the complexity of frequency stability requirements. This method simplifies the frequency security constraint by converting it into an inertia constraint, incorporating all variables from the frequency deviation equation. This transformed constraint is then integrated into the DC-OPF model. This method will be tested on the IEEE 14 bus system using the IBM qiskit simulation tool. The alternate direction method of multipliers is used as a quantum optimization technique and validates the results against classical methods. Our findings show that this quantum-inspired approach effectively optimizes power flow and maintains frequency stability, indicating its significant potential to enhance modern power systems for more resilient and efficient energy management.