In this talk, we explore quantum optimization algorithms through the lens of quantum dynamics, with a focus on their application to practical challenges in energy management systems. We will highlight how quantum techniques—such as adiabatic evolution and quantum Hamiltonian descent—can be integrated with classical optimization frameworks to enhance decision-making in complex energy system operations. The talk will also introduce accessible quantum optimization software platforms that support hybrid quantum-classical workflows, enabling users with limited quantum expertise to model and solve energy optimization problems.