Addressing the world’s climate emergency is an uphill battle, requiring a multifaceted approach including optimal deployment of green-energy alternatives. Such undertakings often involve computationally-expensive optimization of black-box models in continuous parameter space. We observe good performance on the DW-2000Q QPU - even using default settings - and higher sensitivity of performance to a number of samples and annealing time for the Advantage QPU. These results are promising and potentially justify further investment in hardware, software, and optimization research, in particular, in the area of solvers for dense QUBOs.