HubNet: Research Leadership and Networking for Energy Networks (Extension)

HubNet：能源网络的研究领导力和网络（扩展）

• 批准号: EP/N030028/1
• 负责人: Tim Green
• 金额: $ 261.2万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FN030028%2F1
• 关键词: HubNet; Research; Leadership; Networking; Energy

The pace of increase in renewable energy use in UK electricity is impressive with 19% of electricity sourced from renewables in 2014 (DUKES 2015) and half of that being produced by wind turbines. Use of large quantities of variable generation sources has already caused changes to the way electricity networks are designed and operated but as penetration pushes onward to 30% and thence to 50%, it becomes significantly more challenging to maintain the stability and availability that people have come to expect. It is widely said that the resolution of this problem is offered by a smart grid but despite much discussion of smart grids there is still a lack for detailed specification of the intelligent and automated functions required to operate network of the future..An example smart grid feature is that, to a much greater extent than today, demand needs to be influenced to follow available generation. With the advent of half-hourly resolution of electricity bills, facilitated by smart meters, there is a mechanism in place to reward customers who make their consumption flexible and responsive to changes in electricity availability and price. In this example of "smart" technology there are very many questions over how exactly this might work, how people would engage with this technology and how coordination of millions of individual actions will add up to stable operation of the grid.We set out to answer two broad questions. First, how exactly should new computational techniques help mange the future grid? Specifically how can we use decentralised control to perform demand-supply balancing (and voltage control, etc.) at a local level and facilitate coordination and collaboration between decentralised controllers. Also, as part of that, how do advances in data analytics help gain useful control information from the masses of data being produced in the system. Second, in this more complex system, how do we analyse the risk of a system failure and design in resilience to mitigate risk. Traditionally we have had good models of the probability of the failure of, say, a transformer. How can we analyse and design for the highly variable behaviour of customers' responses to short term electricity prices and the short term fluctuation of PV and wind energy. New design principles are needed to ensure continued high reliability of supply. Being smart about the use of decentralised control and the harnessing of newly available data is crucial to ensuring we provide an electricity system able to incorporate large amounts of renewable energy without burdening us with undue cost or degrading performance.Alongside these specific technical ambitions, HubNet maintains its role in bringing together the many academic groups who can contribute, not just electrical power engineering but also computational sciences, energy economics and behavioural modelling. Further, our role is to be the conduit for the academic community to converse with the network operators and equipment vendors so as to keep our research relevant to the sector's major challenges and provide a route to demonstrate and deploy our findings. We will continue to help identify the key research questions for the community to address and we will continue to use our findings as evidence to support energy policy and regulation.

英国电力中可再生能源使用的增长速度令人印象深刻，2014年19%的电力来自可再生能源（DUKES 2015），其中一半由风力涡轮机产生。大量可变发电源的使用已经改变了电网的设计和运营方式，但随着渗透率提高到30%，进而达到50%，保持人们所期望的稳定性和可用性变得更加具有挑战性。人们普遍认为，智能电网可以解决这个问题，但尽管对智能电网进行了大量讨论，但仍然缺乏对未来网络运行所需的智能和自动化功能的详细规范。智能电网的一个典型特征是，在比今天大得多的程度上，需要影响需求以跟随可用的发电。随着智能电表推动的半小时电费结算的出现，有一种机制可以奖励那些灵活消费并对电力供应和价格变化做出反应的客户。在这个“智能”技术的例子中，有很多问题关于这到底是如何工作的，人们将如何参与这项技术，以及数百万个人的行动如何协调起来以稳定电网的运行。首先，新的计算技术到底应该如何帮助管理未来的网格？具体来说，我们如何使用分散控制来执行供需平衡（和电压控制等）。并促进分散控制器之间的协调和协作。此外，作为其中的一部分，数据分析的进步如何帮助从系统中产生的大量数据中获得有用的控制信息。第二，在这个更复杂的系统中，我们如何分析系统故障的风险，并进行弹性设计以减轻风险。传统上，我们已经有了关于（例如）Transformer故障概率的良好模型。我们如何分析和设计客户对短期电价的反应以及光伏和风能的短期波动的高度可变行为。需要新的设计原则来确保持续的高供电可靠性。明智地使用分散式控制和利用新获得的数据，对于确保我们提供一个能够纳入大量可再生能源的电力系统，而不会给我们带来不必要的成本负担或降低性能至关重要。除了这些具体的技术目标，HubNet保持其在汇集众多学术团体方面的作用，这些学术团体可以做出贡献，不仅仅是电力工程，还有计算科学、能源经济学和行为建模。此外，我们的角色是成为学术界与网络运营商和设备供应商匡威的渠道，以便使我们的研究与该行业的主要挑战保持相关，并提供一条展示和部署我们的研究结果的途径。我们将继续帮助确定社区需要解决的关键研究问题，并将继续利用我们的研究结果作为支持能源政策和监管的证据。

项目成果

Planning With Multiple Transmission and Storage Investment Options Under Uncertainty: A Nested Decomposition Approach

• DOI: 10.1109/tpwrs.2017.2774367
• 发表时间: 2018-07
• 期刊: IEEE Transactions on Power Systems
• 影响因子: 6.6
• 作者: P. Falugi;I. Konstantelos;G. Strbac

Coordinated Operation of Gas and Electricity Systems for Flexibility Study

• DOI: 10.3389/fenrg.2020.00120
• 发表时间: 2020-07
• 期刊: ArXiv
• 作者: H. Ameli;Meysam Qadrdan;G. Strbac

What is an electricity blackout?

什么是停电？

• 发表时间: 2016
• 作者: Dent, CJ

Strategic Network Expansion Planning with Electric Vehicle Smart Charging Concepts as Investment Options

• DOI: 10.1016/j.adapen.2021.100077
• 发表时间: 2021-12
• 期刊: Advances in Applied Energy
• 作者: Stefan Borozan;S. Giannelos;G. Strbac

A Self-Organizing Multi-Agent System for Distributed Voltage Regulation

• DOI: 10.1109/tsg.2021.3070783
• 发表时间: 2021-03
• 期刊: IEEE Transactions on Smart Grid
• 影响因子: 9.6
• 作者: B. A. Faiya;Dimitrios Athanasiadis;Minjiang Chen;S. Mcarthur;I. Kockar;Haowei Lu;F. de León