Integrated Operation and Planning for Smart Electric Distribution Networks (OPEN)

智能配电网综合运营规划（OPEN）

• 批准号: EP/K006274/1
• 负责人: Nick Jenkins
• 金额: $ 127.72万
• 依托单位: CARDIFF UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FK006274%2F1
• 关键词: Integrated; Operation; Planning; Smart; Electric

The UK has a commitment to reduce its greenhouse gas emissions by at least 80% by 2050 relative to 1990 levels. DECC's 2050 Pathway Analysis shows the various ways through which we can achieve this target. All feature a high penetration level of renewable generation and a very substantial uptake of electrification of heat and transport, particularly from 2030 onwards. This will place unprecedented demand and distributed generation on electricity supply infrastructure, particularly the distribution systems due to their size. If a business as usual model is to apply, then the costs of de-carbonisation will be very high. Being equally confronted by the pressure of global climate change and sustainable development, the Chinese government has declared that by 2020 the carbon emission per-unit GDP will reduce to 40-45% of that in 2008. However China also needs to meet a 10% annual demand increase which has been on-going for the past 20 years, and this rate of growth is expected to continue for at least another 10 years. Therefore reinforcement of current distribution networks in an economic and sustainable way while meeting customers' rising expectation of supply quality and reliability is one of the basic requirements of Smart Grid development in China. It is a matter of urgency to investigate how to develop and adapt the current distribution network using Smart Grid interventions in order to facilitate timely connection of low carbon and sustainable technologies in a cost-effective manner. This is a global challenge faced by UK, China and many other countries.Our consortium brings together leading researchers from the UK and China to jointly investigate the integrated operation and planning for smart distribution networks to address two key research challenges:(1) Conventional network operational and planning approaches do not address the emerging opportunities offered by increased measurement and control and do not deal with the inevitable uncertainties of smart distribution networks.(2) A general understanding of how national or regional electricity distribution infrastructure should be developed and operated using Smart Grid interventions is required urgently by those making policy within Distribution companies and in Government/Regulators. Such an understanding cannot be gained from running conventional power system analysis tools and then manually assessing the results.New techniques and approaches will be investigated to address these important questions(1) Distribution state estimation and probabilistic predictive control approaches will be used to determine the location and control policies of smart grid interventions including Soft Open Points and electronic embedded hybrid on-load tap changers.(2) Novel dynamic pricing techniques will be proposed to resolve conflicts between energy markets and network operation and find synergies where these exist.(3) A very fast network assessment tool and a rolling planning tool that will bridge the gap between planning and operation will be developed.(4) New visualisation and reporting techniques will be developed to give network planners, operators as well policy makers clear insights as to how Smart Grid interventions can be used most effectively. Complementary, cross-country expertise will allow us to undertake the challenging research with substantially reduced cost, time and effort. The research will build upon the long-time well established collaborations between partner institutions of the two countries. Our ambition is to provide a strategic direction for the future of smart electricity distribution networks in the 2030-2050 time frame and deliver methodologies and technologies of alternative network operation and planning strategies in order to facilitate a cost effective evolution to a low carbon future.

英国承诺到2050年将其温室气体排放量相对于1990年水平减少至少80%。DECC的2050年路径分析显示了我们可以实现这一目标的各种方法。所有这些都具有可再生能源发电的高渗透率，特别是从2030年起，供热和运输电气化的吸收量非常大。这将对电力供应基础设施产生前所未有的需求和分布式发电，特别是由于其规模的配电系统。如果采用一种"一切照旧“的模式，那么去碳化的成本将非常高。面对全球气候变化和可持续发展的双重压力，中国政府宣布，到2020年，单位GDP碳排放量将减少到2008年的40-45%。然而，中国还需要满足过去20年来每年10%的需求增长，预计这一增长率将持续至少10年。因此，以经济和可持续的方式加强现有的配电网，同时满足客户对供电质量和可靠性不断提高的期望，是中国智能电网发展的基本要求之一。迫切需要研究如何使用智能电网干预措施开发和调整当前的配电网络，以便以具有成本效益的方式及时连接低碳和可持续技术。这是英国、中国和其他许多国家面临的全球性挑战，我们的联盟汇集了来自英国和中国的领先研究人员，共同研究智能配电网的综合运营和规划，以解决两个关键的研究挑战：（1）传统的网络运营和规划方法无法解决日益增加的测量和控制所带来的新机遇，也无法处理智能配电网不可避免的不确定性。(2)配电公司和政府/监管机构制定政策的人员迫切需要对如何使用智能电网干预措施开发和运营国家或区域配电基础设施有一个总体了解。通过运行传统的电力系统分析工具，然后手动评估结果，无法获得这样的理解。将研究新的技术和方法来解决这些重要问题。（1）配电状态估计和概率预测控制方法将用于确定智能电网干预措施的位置和控制策略，包括软开放点和电子嵌入式混合有载分接开关。(2)将提出新的动态定价技术，以解决能源市场和网络运营之间的冲突，并找到协同效应，这些存在。(3)将开发一个非常快速的网络评估工具和一个滚动规划工具，以弥合规划和运营之间的差距。(4)将开发新的可视化和报告技术，为网络规划者、运营商以及政策制定者提供关于如何最有效地使用智能电网干预措施的清晰见解。互补的跨国专业知识将使我们能够以大幅降低的成本，时间和精力进行具有挑战性的研究。该研究将建立在两国合作机构之间长期良好的合作基础上。我们的目标是在2030-2050年的时间框架内为智能配电网络的未来提供战略方向，并提供替代网络运营和规划策略的方法和技术，以促进经济高效地向低碳未来发展。

项目成果

Soft Open Points for Supply Restoration in Medium Voltage Distribution Networks

中压配电网供电恢复的软开路点

• 发表时间: 2015
• 作者: Cao W

Topological properties of medium voltage electricity distribution networks

• DOI: 10.1016/j.apenergy.2017.06.113
• 发表时间: 2018-01
• 期刊: Applied Energy
• 影响因子: 11.2
• 作者: Sathsara Abeysinghe;Jianzhong Wu;M. Sooriyabandara;M. Abeysekera;Tao Xu;Chengshan Wang

Benefits analysis of Soft Open Points for electrical distribution network operation

• DOI: 10.1016/j.apenergy.2015.12.022
• 发表时间: 2016-03
• 期刊: Applied Energy
• 影响因子: 11.2
• 作者: Wanyu Cao;Jianzhong Wu;N. Jenkins;Chengshan Wang;T. Green

Operating principle of Soft Open Points for electrical distribution network operation

• DOI: 10.1016/j.apenergy.2015.12.005
• 发表时间: 2016-02
• 期刊: Applied Energy
• 影响因子: 11.2
• 作者: Wanyu Cao;Jianzhong Wu;N. Jenkins;Chengshan Wang;T. Green

Feeder load balancing in MV distribution networks using soft normally-open points

• DOI: 10.1109/isgteurope.2014.7028874
• 发表时间: 2014-10
• 期刊: IEEE PES Innovative Smart Grid Technologies, Europe
• 作者: Wanyu Cao;Jianzhong Wu;N. Jenkins