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工程科学与技术:2022,54(1):5-15
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一种面向未来能源系统的综合能源架构——基于能源多板块智能耦合的绿色能源系统ENSYSCO
(1.四川大学 中德能源研究中心,成都 610065;2.德国克劳斯塔尔工业大学 地下能源系统研究所,克劳斯塔尔–采勒菲尔德 38678;3.下萨克森能源研究中心,戈斯拉尔 38640;4.四川大学 计算机学院,成都 610065)
An Integrated Framework to Better Fit Future Energy Systems—Clean Energy Systems Based on Smart Sector Coupling (ENSYSCO)
(1.Sino-German Energy Research Center, Sichuan Univ., Chengdu 610065, China;2.Inst. of Subsurface Energy Systems, Clausthal Univ. of Technol., Clausthal–Zellerfeld 38678, Germany;3.Energy Research Centre of Lower Saxony, Goslar 38640, Germany;4.College of Computer Sci., Sichuan Univ., Chengdu 610065, China)
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投稿时间:2021-07-07    修订日期:2021-10-20
中文摘要: 为避免大量温室气体排放导致的剧烈气候变化给全球发展带来难以估量的破坏性影响,当今世界的大部分国家正迅速提升其能源生产中可再生资源的比重,以加速能源转型并实现在21世纪中叶达成碳中和的承诺。然而,旧有的能源系统在形成之初并未考虑对可再生资源的大规模融合,因此在面对此类资源具有的间歇、波动与随机等特性时,其往往较为脆弱。基于对既往智能电网技术和德国提出的能源利用多板块耦合技术进展的总结,同时考虑到大规模地下储能的潜力和基于人工智能的监控、分析和预测的广泛应用,作者提出了一种基于智能多板块耦合的清洁能源系统(clean energy systems based on smart sector coupling,ENSYSCO)的面向未来的综合能源架构。首先,ENSYSCO架构通过对电力多元转换/逆转技术(power-to-X-to-power)的应用将能源的生产、消费和存储3大板块紧密耦合在一起。大规模地下储能的引入在大幅提升系统冗余度及灵活性的同时,也令所在国家或地区获得了更加充沛且稳定的能源储备。其次,未来能源系统中出现的各种功能复合体会导致更复杂的供需关系,同时也迫切需要与之适配的多元运输网络。物理与数据混合驱动的轻量化人工智能方法既赋予管理系统强大分析、决策和反馈能力,也令整个系统的运转更高效、坚固且节能。最后,ENSYSCO架构中以地下抽水蓄能为代表的大多数技术都已足够成熟,并且可以立即投入工业化应用。对可再生增强型地热系统和人工智能管理系统的进一步研究,将有助于ENSYSCO架构推动中国更快、更好地实现碳中和目标。
Abstract:In order to avoid the severe climate changes caused by a large amount of greenhouse gas emissions from bringing destructive impact on global development, most countries are rapidly increasing the proportion of renewable resources in their energy production to accelerate the energytransition and realize the commitment of achieving carbon neutrality by the middle of this century. However, the legacy system did not consider the large-scale integration of renewable resources at the beginning of its formation. Therefore, it is often vulnerable to the intermittent, fluctuating and random characteristics of such resources. In this paper, based on the summing upand development of the smart grid and the sector coupling concept of energy utilization raised by Germany, and taking into account the widespread adoption of large-scale underground storage and AI-based (artificial intelligence) monitoring, analysis and forecasting, an integrated future framework named clean energy systems based on smart sector coupling (ENSYSCO) is proposed. Firstly, ENSYSCO closely couples the three sectors of energy’s production, consumption and storage through applying the power-to-X-to-power techniques. The introduction of large-scale underground storage on one hand greatly improves the redundancy and flexibility of the system, on the other hand enables the regions to obtain a more abundant and stable energy reserve. Secondly, various functional complexes within the future energy system lead to more complex supply-demand relationships, and at the same time, there is an urgent request for proper transport grids. The lightweight AI method driven by the hybrid of physics and data not only endows the governance system powerful analysis, decision-making and feedback capabilities, but also makes the operation of the entire system more efficient, robust and energy-saving. Finally, most of the techniques in the ENSYSCO framework, e.g. the pumped-storage hydroelectricity in mines (PSHm), are mature enough and can be put into industrial applications immediately. Further research on the regenerative enhanced geothermal system (REGS) and the AI governance will help ENSYSCO to promote China’s achievement of carbon neutrality more effective.
文章编号:202100659     中图分类号:    文献标志码:
基金项目:四川省国际科技创新合作项目(2021YFH0010)
作者简介:第一作者:侯正猛(1963-),男,教授,博士.研究方向:二氧化碳封存;油气、地热资源开发;大规模地下储能;碳中和等.E-mail:hou@tu-clausthal.de;通信作者:冯文韬,E-mail:Wtfeng2021@scu.edu.cn
引用文本:
侯正猛,冯文韬.一种面向未来能源系统的综合能源架构——基于能源多板块智能耦合的绿色能源系统ENSYSCO[J].工程科学与技术,2022,54(1):5-15.
HOU Zhengmeng,FENG Wentao.An Integrated Framework to Better Fit Future Energy Systems—Clean Energy Systems Based on Smart Sector Coupling (ENSYSCO)[J].Advanced Engineering Sciences,2022,54(1):5-15.