Quantum computing for energy systems optimization
With the rising demand for energy and the need for environmental protection, there has been a primary interest in the design, control, and planning of energy systems. New energy resources are also being integrated into energy systems rendering optimal management and control of available resources to be a key issue in harnessing new technologies. Without optimal utilization of resources, the cost of investment for these technologies cannot be justified. Therefore, optimization tools and algorithms provide a suitable way to solve complex energy systems problems in this field.
Quantum computing provides a novel approach to help solve some of the most complex problems while offering an essential speed advantage over conventional computers.
Classical optimisation methods applied to large-scale renewable and sustainable energy systems to perform multi objective optimisation result in use of high computational effort.
While solving large instances of complex problems with deterministic technique is intractable, approximate algorithms should be considered. Quantum computers realize such approximate algorithms intrinsically.
Quantum computing is a game-changer technology that is able to tackle such intractable problems and may produce good solutions in reasonable runtimes.
Unlike classical computers exploring the entire space of feasible solutions, quantum computers focus on exploring selected feasible subspaces, thus inducing a quantum speedup.
Read and download the full paper here.
It’s a very interesting publication from Cornell University.
