Quantum for Energy and Utilities 2026

CASE STUDY 7 Quantum sensing Improving wind resource management with more sensitive quantum-interference lidar for long-range, low-signal wind measurements For wind energy, being able to measure wind accurately from farther away, even when the signal is faint, helps at every stage. It supports choosing sites, producing lender- ready energy estimates, understanding turbine wakes and running the plant day to day through better forecasting and control. This is especially useful when you need dependable wind data across the full rotor sweep and several kilometres upwind or across a large onshore or offshore site. Higher sensitivity means the lidar stays useful in more real- world conditions. It can reach farther and cope better with haze, low aerosol levels and bright background light. When the measurements stay reliable more often, you cut down the uncertainty in energy forecasts and make smarter decisions about turbine layout and operating settings. A research team at the University of Science and Technology of China, part of the Chinese Academy of Sciences, built an early prototype of a new kind of atmospheric lidar system that uses quantum interference ideas to pick out very weak signals. It combines up-conversion detection with a Hong Ou Mandel-style interference approach to make wind measurements easier to detect when the return signal is faint. In field tests, they reported measuring wind fields out to 16 kilometres using 70 microjoules per pulse. They also reported about seven times higher detection sensitivity than conventional methods, with wind-field results that closely matched their reference comparison.11 Quantum for Energy and Utilities: Key Opportunities for Energy Transition 19