Algorithms for the Sustainable Energy Emergency

研究问题我们能否展示一种算法，以尊重能源系统的物理约束和特征的方式加速社会的脱碳努力，可由系统运营商实施，对社会公平和公正，并符合行为科学和经济学的最佳实践？EPSRC研究领域概率控制系统，以人为本的设计，网络物理系统，数字化，能源系统转型，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，社会已经发展到期望电网在任何时候都有足够的电力供应。很有可能的是，这将不再是仅期望使用低碳供应的情况，特别是在供应的很大一部分来自不可控制的太阳能和风能的能源系统中。这代表着系统运营商的范式转变，他们需要将重点从确保有足够的供应转向管理消费。这些变化要求社会与网格合作，这意味着网格在本质上变得越来越网络物理。博士将重点展示有效管理网格消耗所需的算法。这是高度跨学科的性质，因此将与来自经济学，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。共享经济的经验将得到借鉴。IPCC第六次评估报告（2022年）明确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的风险。如果人们没有充分参与，或者过渡没有以公平的方式进行，也会有发生强烈反应的真实的风险。这些算法旨在降低这种风险，并确保尽可能实现公平和道德的过渡。能源系统的数字化是以这种方式运行能源系统的必要手段。数字化将商业模式转变为提供更多的即服务型商业模式，其中有一些持续的承诺，而不是简单的前期交易。因此，与能源系统的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证明其数学性质（稳定性等），并验证他们是否实现了所需的结果。目前的计划是用真实的人进行一项实验，让他们参与到一个虚拟的能源世界中，在这个世界中部署新的算法，并评估它们的有效性。此外，还将展示另一个可持续交通领域的相关应用，该应用的重点是管理电动自行车电池中存储的能量消耗，以最大限度地减少空气污染对骑自行车者的影响。博士学位的新颖方面与算法本身有关，我们相信这将导致管理能源系统的新策略，从而有助于脱碳工作的有效性和效率。

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.