The Autonomic Power System

自主动力系统

• 批准号: EP/I031650/1
• 负责人: Stephen McArthur
• 金额: $ 436.94万
• 依托单位: University of Strathclyde
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FI031650%2F1
• 关键词: Autonomic; Power; System

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.

该提案的重点是2050年的电力网络。在转移到脱碳的能源网络中，热量和运输部门将完全集成到电力系统中。因此，能源网络中的巨大挑战是提供电力系统的根本变化，这将支持这种过渡，而不会受到当前基础架构，运营规则，市场结构，法规和设计指南的约束。塑造2050电力网络2050的驱动因素很多：上涨的能源价格；发电的可用性增加；减少系统惯性；由于电动汽车和热泵等负载的增长而增加的利用；电动汽车作为随机铺设的负载和储能；分布生成的水平增加；有助于发电的更多能源范围更多样化；并增加了客户的参与。这些变化意味着，出于技术，社会和商业原因，未来的能源网络将比当今的能源网络更难管理和设计。为了满足这种复杂性，必须组织未来的能源网络，以通过提供适当的实时决策技术来提高灵活性和可控性。这些技术必须协调大量各种组件和功能的同时运行，包括存储设备，需求副作用，网络拓扑，数据管理，电力市场，电动汽车充电系统，动态评级系统，分布式发电，网络电力流量管理，网络电源管理，故障水平管理，供应恢复和燃料恢复和燃料选择。此外，未来的灵活网格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，与这些决策和网络实时控制相关的风险和含义将更加难以识别和量化。我们建议对2050年的自主能力系统的设计作为旨在调查的巨大挑战。这取决于计算机科学界对自主计算的愿景，并将其扩展到电网络中。该概念基于设定高级目标的生物自主系统，但将如何实现这些目标实现为较低级别的智能。没有明显的集中控制，而且行为通常来自低级相互作用。这允许高度复杂的系统实现对操作的实时和及时优化。我们认为，将需要这种方法来管理拥有数百万个主动设备的2050年复杂的跨国电力系统。自主力系统将是自我调节，自我修复，自我优化和自我保护。该提案并不集中于已建立的自主计算技术在电力系统中的应用（因为它们不存在），而是依赖于分布式智能和局部目标设定的自主能力系统的设计。这是从当前的智能电网愿景和路线图迈出的重要一步。自主功率系统是一个完全集成和分布式的控制系统，它可以实时自我管理和优化所有网络操作决策。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，集中和层次控制之间的平衡）及其对跨国互连电网络的投资决策，弹性，风险和控制的影响。该计划中的研究是雄心勃勃的，挑战了许多当前的哲学和设计方法。它也是多学科的，并且将在电力系统，复杂性科学，计算机科学，数学，经济学和社会科学之间促进交叉灌输。

项目成果

Operation and Control Zones for Future Complex Power Systems

• DOI: 10.1109/greentech.2013.47
• 发表时间: 2013-04
• 期刊: 2013 IEEE Green Technologies Conference (GreenTech)
• 作者: V. Alimisis;Chiara Piacentini;J. King;P. Taylor

Active network management using distributed constraint optimisation

• DOI: 10.1109/pesmg.2013.6672504
• 发表时间: 2013-07
• 期刊: 2013 IEEE Power & Energy Society General Meeting
• 作者: Dimitrios Athanasiadis;S. Mcarthur

Efficient Temporal Piecewise-Linear Numeric Planning With Lazy Consistency Checking

具有惰性一致性检查的高效时间分段线性数值规划

• DOI: 10.1109/tai.2022.3146797
• 发表时间: 2022
• 期刊: IEEE Transactions on Artificial Intelligence
• 作者: Bajada J

Temporal Plan Quality Improvement and Repair using Local Search

使用本地搜索进行时间计划质量改进和修复

• 发表时间: 2014
• 作者: Bajada, J

Temporal Planning with Semantic Attachment of Non-Linear Monotonic Continuous Behaviours

具有非线性单调连续行为语义依附的时间规划

• 发表时间: 2015
• 作者: Bajada, J