Titulo Estágio
Quantum Computing for Optimizing Power Flow in Energy Grids
Áreas de especialidade
Engenharia de Software
Local do Estágio
DEI-FCTUC
Enquadramento
There is a large body of compelling evidence that Computation as we have known and used for decades is under challenge. As new models for computation emerge, its limits are being pushed beyond what pragmatically had been seen in practice. In this line, Quantum Computing (QC) has received renewed worldwide attention. Having its foundations been thoroughly studied, mainly from the point of view of its physical implementation, their potential has, even if preliminarily, just been witnessed.
In an article published in Nature in October 2019, Google describes how using a self-built 54-qubit processor correctly executed, in only 200 seconds, a benchmark that even the world’s fastest supercomputer would have taken an estimation of 10,000 years to complete; this way showing the so-called quantum supremacy.
In a follow-up, IBM has disputed the foundations of such estimation, and mainly the claim that quantum supremacy has been reached. IBM’s argument is mainly about the assertion that a properly crafted supercomputer could have reached the same result even more efficiently than the Google quantum computer. However, no empirical demonstration was provided to support such assertion. In essence, Google’s experiment provides clear evidence of the progress that has been made in terms of superconducting-based quantum computing. IBM itself has also made substantial progress to build universal quantum computers to support business, engineering and science.
The field of QC is evolving at a pace faster than people originally expected. For example, in March 2020 Honeywell announced a revolutionary quantum computer based on trapped-ion technology with quantum volume 64 – the highest quantum volume ever achieved, twice as the state of the art, previously owned by IBM. Quantum volume is a unit of measure indicating the fidelity of a quantum system. This important achievement shows that the field of quantum computing may reach industrial impact much sooner than originally expected.
In this project, we will explore the potential of QC to address computational issues within the energy sector.
The electric grid is undergoing a disruptive revolution. As electric vehicles, demand side management or distributed generation resources become more common, the need for better techniques for grid management becomes apparent.
Grid operators are facing an increasingly dynamic and fast-changing system and need the correct set of tools to find optimal points for operation according to grid requirements and customers’ needs.
The optimal power flow is one of the most important optimization challenges, as it calculates the optimal set-point and respective scheduling for generation units. This is complex economically (set up an efficient market equilibrium), electrically (nonlinearities of alternating current), and computationally (includes nonlinear, nonconvex functions of the system's physical characteristics). More robust, efficient, and better-than-local optimization would provide a potential benefit to the electrical grid and to consumers.
The optimal power flow problem is characterized by the search of an optimal solution to a specific object function (e.g. minimize transmission/distribution losses or operational cost) subject to: power flow; constraints; operational/assets limitations.
Objetivo
The candidate will join a group of researchers who are doing intensive, foundational work on Quantum Computing. In this line, the proposal is actually jointly co-supervised by UC and IST.
The general goal is to study, propose and improve algorithms that can benefit from quantum computing in the context of the energy sector.
In concrete, we aim at reaching the following goals:
- to study and critically analyse the state of the art in the quantum computing paradigm, with a focus on its application to the energy sector;
- to design and implement a quantum algorithm for power flow optimization in energy grids;
- to validate and assess the proposed algorithm in practice;
- to release and disseminate the proposed algorithm within the scientific and industrial communities.
Plano de Trabalhos - Semestre 1
- Trimester 1: Study the literature, the tools and the frameworks that are available for Quantum Computing.
- Trimester 2: Design a quantum algorithm, or a set of quantum algorithms, either fully quantum or hybrid, to improve the state of the art solutions to power flow optimization. Write an intermediate report.
Plano de Trabalhos - Semestre 2
- Trimester 3: Implement the designed algorithm within an Open Quantum framework, such as IBM's Qiskit or Google's Cirq.
- Trimester 4: Validate the obtained implementation. Thesis writing.
Condições
The eligible student will have at disposal all the necessary computational platforms, tools and devices.
He will work within a research team that is working on related issues.
It might also be possible to ensure funding for the student in the form of a research grant (Bolsa de Investigação para Licenciado).
Orientador
João Paulo Fernandes e Rui Maranhão Abreu (jpf@dei.uc.pt, rui.maranhao@tecnico.ulisboa.pt)
jpf@dei.uc.pt 📩