Quantum computing solutions for optimisation problems in Energy Grids

能源网格优化问题的量子计算解决方案

• 批准号: 10108062
• 金额: $ 156.82万
• 依托单位: PHASECRAFT LIMITED
• 依托单位国家: 英国
• 项目类别: Small Business Research Initiative
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10108062
• 关键词: Quantum; computing; solutions; optimisation; problems

Nowadays, most people and businesses rely on a regular and reliable supply of energy for their day-to-day activities, making the energy grid a critical infrastructure for the country. Building and maintaining grid connections is a costly exercise: building an electric grid can cost up to £1.5m per km of line - costs that are ultimately borne by either the taxpayer or the energy consumer. Being able to determine the optimal parameters for the network's infrastructure can therefore lead to significant cost savings, as well as potentially improving the network's resilience against vulnerabilities such as extreme weather events.The move towards Net Zero is also affecting the requirements on the power grid. Where once the network only needed to focus on a small number of generators with similar performance characteristics, it is now required to connect millions of smaller renewable generators, whose energy output is highly variable and often unpredictable.The increased complexity of the system translates into an exponential increase in the running time of the algorithms that have been traditionally used to optimise the grid, making them effectively no longer fit for purpose.It has long been suggested, though, that quantum computing has the potential to answer these sort of optimisation questions more efficiently than classical computers. Until recently, this was only believed possible in the longer term (requiring full-scale quantum hardware) but recent innovations by Phasecraft have changed this perspective, showing that even in the near term (when quantum computers are expected to be small-scale and noisy) there is the potential for quantum algorithms to outperform classical ones.Building on the first Phase of this project, we will continue to work with the SuperGen Energy Networks Hub and the Department for Energy Security and Net Zero to develop a quantum software solution to this problem, initially addressing proof-of-principle instances. This will ultimately facilitate future network planning and accelerate the deployment of renewables (both key goals within the _Powering Up Britain_ strategy published earlier in 2023).

如今，大多数人和企业都依靠常规和可靠的能源供应日常活动，这使得能源电网成为该国的关键基础设施。建立和维护电网连接是一项昂贵的练习：建造电网的价格最高为每公里的150万英镑 - 最终由纳税人或能源消费者诞生的成本。因此，能够确定网络基础架构的最佳参数可能会导致大量的成本节省，并有可能提高网络对极端天气事件等漏洞的弹性。向Net net net of net net of net of net Net也影响了电网的需求。一旦网络只需要专注于具有相似性能特征的少数发电机，现在需要将数百万个较小的可再生发电机连接起来，它们的能量输出高度可变且通常是不可预测的。系统的复杂性的增加转化为指数呈指数增长，从而在传统上使用量子的算法不断提出的量子，以使其更加优化，以使其更加优化，以使其成为有效的网格，以使其更加优化，以使其更加优化。与古典计算机相比，可以更有效地回答这类优化问题。直到最近，这仅在长期（需要全尺寸量子硬件）中才能相信，但是，通过文物的最新创新已经改变了这一观点，即使在近期（预计量子计算机是小规模和噪音时），即使在量子算法上，量子算法也可以超过该项目，我们将公平的范围进行量子，我们将公平地延续该项目，我们将公平地延续。安全性和净零以开发针对此问题的量子软件解决方案，最初解决原理证明实例。这最终将支持未来的网络计划并加速可再生能源的部署（在2023年前早些时候发布的英国策略构成的关键目标中）。