Ayesa uses quantum technology to optimise Spain’s national grid

Ayesa and Iberdrola are developing a solution to maximise availability, based on forecasts for demand.

Ayesa, a global provider of technology and engineering services, is working with Iberdrola to develop a quantum computing solution to optimise Spain’s national grid, managed by transmission network operator i-DE.

Analysing and optimising the electrical infrastructure of a company with more than 11 million customers represents a significant challenge. This is made even more difficult by constant changes in the market. These include the generation of energy for personal use as well as new means of storage, and have seen traditional top-down energy studies become largely obsolete. Instead, what is required are studies that consider all the ways in which energy flows (down-top, from-to, to-from, etc.), as well as an ability to anticipate future needs in order to ensure they are met.

The current landscape requires a comprehensive management strategy for national grids that includes:

• the effective processing of vast volumes of data;
• predictions of future scenarios; and
• the optimisation of the network.

Faced with this challenge, i-DE has partnered up with Ayesa to develop a solution based on quantum computing, currently the only technology able to offer an effective solution.

Aitor Moreno, Head of Quantum Computing at Ayesa, explains: ‘Electrical grids have low, medium and high voltage sections, with the entire process, from generation to supply, being connected. The aim is for each process to automatically adjust to conditions at any given time. This will ensure an optimal and sustainable system by allowing incidents as well as changes in demand and generation to be handled in the best possible way. Having a solution able to suggest the best course of action in each case will also minimise risk’.

Harnessing the power of quantum computing

Quantum computing is a new technology that is allowing us to develop precise solutions to complex optimisation problems. This is particularly useful in environments involving topological graphs where all possible scenarios need to be evaluated in an efficient manner.

This project has seen Ayesa use quantum optimisation technology to establish optimal scenarios.

The optimisation algorithms in question (QUBO, Ising, QUOA, VQE and Quantum MonteCarlo) will be used as part of a combined hybrid model and measured based on their accuracy. Furthermore, restrictions will be implemented using Grover Adaptive Search (GAS) as well as black-box optimisation (BBO).