The Autonomic Power System

该计划的重点是2050年的电力网络。在转向脱碳能源网络的过程中，供热和运输部门将完全融入电力系统。因此，能源网络面临的巨大挑战是在电力系统中实现支持这一转变的根本性变革，而不受当前基础设施、运营规则、市场结构、法规和设计指南的限制。将塑造2050年电力网络的驱动因素有很多：能源价格上涨;发电可用性的变化增加;系统惯性降低;由于电动汽车和热泵等负载的增长而增加利用率;电动汽车作为随机流动负载和能量存储;分布式发电水平提高;促进发电的能源种类更加多样化;增加客户参与。这些变化意味着，由于技术、社会和商业方面的原因，未来的能源网络将比今天的网络更难管理和设计。为了迎合这种复杂性，未来的能源网络必须组织，以提供适当的真实的时间决策技术，通过提供增加的灵活性和可控性。这些技术必须协调大量不同组件和功能的同时操作，包括存储设备、需求侧动作、网络拓扑、数据管理、电力市场、电动汽车充电机制、动态额定系统、分布式发电、网络功率流管理、故障水平管理、供应恢复和燃料选择。此外，未来的灵活电网将为能源交易理念和投资决策提供更多选择。由于不确定性和复杂性的增加，与这些决策和网络的实时控制相关的风险和影响将更难识别和量化。我们提出了2050年自主电力系统的设计作为要研究的重大挑战。这借鉴了计算机科学界对自主计算的看法，并将其扩展到电力网络。这个概念是基于生物自主系统，它设定了高层次的目标，但将如何实现这些目标的决策委托给了较低层次的智能。没有明显的集中控制，行为往往出现在低层次的互动。这使得高度复杂的系统能够实现实时和即时的操作优化。我们认为，这种方法将需要管理2050年复杂的跨国电力系统，其中有数百万个有源设备。自主电力系统将自我配置，自我修复，自我优化和自我保护。该提案的重点不是将已建立的自主计算技术应用于电力系统（因为它们不存在），而是设计一个依赖于分布式智能和本地化目标设置的自主电力系统。这是从目前的智能电网愿景和路线图向前迈出的重要一步。自治电力系统是一个完全集成的分布式控制系统，它能真实的实时地自我管理和优化所有的网络操作决策。为了实现这一目标，需要进行基础研究，以确定可实现的分布式控制水平（或分布式，集中式和分层控制之间的平衡）及其对跨国互联电网的投资决策，弹性，风险和控制的影响。该计划中的研究雄心勃勃，挑战了许多当前的哲学和设计方法。它也是多学科的，将促进电力系统，复杂性科学，计算机科学，数学，经济学和社会科学之间的交叉。

This proposal focuses on the electricity network of 2050. In the move to a decarbonised energy network the heat and transport sectors will be fully integrated into the electricity system. Therefore, the grand challenge in energy networks is to deliver the fundamental changes in the electrical power system that will support this transition, without being constrained by the current infrastructure, operational rules, market structure, regulations, and design guidelines. The drivers that will shape the 2050 electricity network 2050 are numerous: increasing energy prices; increased variability in the availability of generation; reduced system inertia; increased utilisation due to growth of loads such as electric vehicles and heat pumps; electric vehicles as randomly roving loads and energy storage; increased levels of distributed generation; more diverse range of energy sources contributing to electricity generation; and increased customer participation. These changes mean that the energy networks of the future will be far more difficult to manage and design than those of today, for technical, social and commercial reasons. In order to cater for this complexity, future energy networks must be organised to provide increased flexibility and controllability through the provision of appropriate real time decision-making techniques. These techniques must coordinate the simultaneous operation of a large number of diverse components and functions, including storage devices, demand side actions, network topology, data management, electricity markets, electric vehicle charging regimes, dynamic ratings systems, distributed generation, network power flow management, fault level management, supply restoration and fuel choice. Additionally, future flexible grids will present many more options for energy trading philosophies and investment decisions. The risks and implications associated with these decisions and the real-time control of the networks will be harder to identify and quantify due to the increased uncertainty and complexity.We propose the design of an autonomic power system for 2050 as the grand challenge to be investigated. This draws upon the computer science community's vision of autonomic computing and extends it into the electricity network. The concept is based on biological autonomic systems that set high-level goals but delegate the decision making on how to achieve them to the lower level intelligence. No centralised control is evident, and behaviour often emerges from low-level interactions. This allows highly complex systems to achieve real-time and just-in-time optimisation of operations. We believe that this approach will be required to manage the complex trans-national power system of 2050 with many millions of active devices. The autonomic power system will be self-configuring, self-healing, self-optimising and self-protecting. This proposal is not focused on the application of established autonomic computing techniques to power systems (as they don't exist) but the design of an autonomic power system, which relies on distributed intelligence and localised goal setting. This is a significant step forward from the current Smart Grid vision and roadmaps. The autonomic power system is a completely integrated and distributed control system which self-manages and optimises all network operational decisions in real time. To deliver this, fundamental research is required to determine the level of distributed control achievable (or the balance between distributed, centralised, and hierarchical controls) and its impact on investment decisions, resilience, risk and control of a transnational interconnected electricity network. The research within the programme is ambitious and challenges many current philosophies and design approaches. It is also multi-disciplinary, and will foster cross-fertilisation between power systems, complexity science, computer science, mathematics, economics and social sciences.