Algorithms for the Sustainable Energy Emergency

研究问题我们是否可以展示一种算法，以尊重能源系统的物理约束和特征，由系统操作员实施，对社会公平公正，并符合行为科学和经济学的最佳实践？EPSRC研究随机控制系统、以人为中心的设计、网络物理系统、数字化、能源系统转换、可持续技术、共享经济、反馈系统、电力系统工程、经济学、行为科学。摘要在发达国家，社会越来越期望电网始终有足够的电力供应。这很有可能不再是只希望使用低碳供应的情况，特别是在一个能源系统中，很大一部分供应来自太阳能和风能，而这两种能源是无法控制的。对于系统运营商来说，这代表着一种范式的转变，他们将需要将重点从确保足够的供应转移到专注于管理消费。这些变化要求社会与电网合作，这意味着电网本质上变得越来越具有网络物理性质。博士学位将专注于演示实现有效管理电网消耗所需的算法。这在本质上是高度跨学科的，因此将与经济学、行为科学和电力系统工程等领域的专家合作。将与全球电力系统转型联盟密切合作。将依靠从共享经济中学习。政府间气候变化专门委员会第六次评估报告(2022年)明确指出了所需变化的规模和速度，这些变化将极大地影响人们的生活，并带来加剧现有社会不平等的真实风险。如果人们没有充分参与，或者如果过渡没有以公平的方式完成，也存在真正的反弹风险。这些算法的目的是降低这种风险，并尽可能确保公平和合乎道德的过渡。能源系统的数字化是以这种方式运行能源系统的必要工具。数字化转变了商业模式，提供更多的即服务类型的商业模式，其中有一些持续的承诺，而不是简单的预付交易。因此，与能源系统运营和融资相关的商业模式也需要改变。所采取的方法是设计算法来证明它们的数学属性(稳定性等)，并验证它们达到了所需的结果。目前的计划是用真人进行一项实验，让他们参与部署新算法的虚拟能源世界，并评估它们的有效性。此外，还将展示可持续交通中的另一个相关应用，重点是管理电动自行车电池中存储的能量的消耗，以将空气污染对骑自行车的人的影响降至最低。PHD的新颖方面与算法本身有关，我们相信这些算法将导致管理能源系统的新策略，从而有助于脱碳努力的有效性和效率。

Research questionCan we demonstrate algorithms which accelerate society's decarbonisation efforts in a way that respects the physical constraints and characteristics of the energy system, is implementable by the system operator, is fair and equitable for society, and is in line with best practise from behavioural science and economics?EPSRC Research AreasProbabilistic control systems, human centered design, cyberphysical systems, digitalisation, energy system transition, sustainable technologies, sharing economy, feedback systems, power systems engineering, economics, behavioural science. SummaryIn developed nations, society has grown to expect that there is always enough electricity supply available from the grid at all times. It is highly likely that that will no longer be the case where it is desired to use low carbon supply only, in particular in an energy system where a significant proportion of the supply comes from solar and wind which are uncontrollable. This represents a paradigm shift for the system operators who will need to shift their focus from ensuring there is enough supply to instead focus on managing consumption. The changes require society to work with the grid, which means that the grid becomes increasingly cyberphysical in nature.The PhD will focus on demonstrating algorithms required to enable effective management of grid consumption. This is highly interdisciplinary in nature, and as such there will be collaboration with experts from domains like economics, behavioural science and power systems engineering. There will be close collaboration with the Global Power System Transformation Consortium. Learnings from the sharing economy will be relied upon. The IPCC Sixth Assessment report (2022) made clear the scale and pace of change that is required, these changes will drastically impact people's lives and present a real risk of exacerbating existing societal inequalities. There is also the real risk of backlash if people are not sufficiently involved or if the transition is not done in an equitable manner. The algorithms will aim to reducing this risk and ensure there is a fair and ethical transition insofar as possible.Digitalisation of the energy system is a necessary vehicle for operating the energy system in this way. Digitalisation transforms business models to delivering more as-a-service type business models where there is some ongoing commitment rather than a simple upfront transaction. As such, the business models associated with the operation and financing of the energy system also need to change. The approach taken is to design algorithms prove their mathematical properties (stability etc.), and validate that they achieve the required outcomes. The current plan is to conduct an experiment with real people where they participate in a virtual energy world where the new algorithms are deployed and assess their effectiveness. Additionally, another related application in sustainable transport will be demonstrated, which is focused around managing the consumption of energy stored in electric bike batteries to minimise the impact of air pollution on cyclists.The novel aspects of the PhD relate to the algorithms themselves which we believe will lead to new strategies to manage the energy system and therefore contribute to the effectiveness and efficiency of the decarbonisation effort.