面向能源集成的压缩空气储能系统建模与优化研究

As a clean physical storage technology, the compressed-air energy storage (CAES) enjoys various advantages including large capacity, long service period, fast response capability, and so on. The adiabatic CAES without fuel combustion can produce electricity, heating, and cooling energy at the same time, and provides an effective solution for harnessing renewable generation, flattening the load over time by shaving peaks and filling valleys, facilitating the transition to low carbon energy industry, as well we supporting the development of energy internet technology. This project launches a cross-disciplinary research on the multi-energy production, conversion, and storage processes in the adiabatic CAES system, quantifies the quality change in different forms of energies, so as to guide the system configuration and design under variable and wide operating conditions, and establish mathematical models which are suitable for energy management studies. For the adiabatic CAES based energy integration center or energy hubs which offer electricity, heating, and cooling energies to urban demands, this project studies capacity planning and production scheduling problems based on advanced mathematical theory including distributionally robust optimization and hierarchal game theory. Equivalent mathematical programs in forms of convex optimization and mixed-integer linear programming will be developed through dual transformation and optimality conditions, and can be efficiently solved via commercial software. In this way, the shortcomings of traditional optimization theory on tackling uncertainties and coping with multiple decision makers can be overcome. This research helps improve the CAES technology and promotes its applications in future integrated energy systems.

作为一种清洁物理储能技术，压缩空气储能具有容量大、寿命长、响应速度快等优点。其中绝热压缩空气储能无需燃料补燃、具备电-热-冷联供联储能力，是解决风光电力有效消纳、实现电网削峰填谷、支撑能源结构清洁化转型、推动能源集成等能源互联网技术创新的有效手段之一。本项目拟对绝热压缩空气储能系统能量生产、转换、存储等环节进行交叉学科研究，揭示能量品位变化和能效提升的量化指标，指导变工况、宽范围运行条件下系统配置与优化设计，进而建立适用于能源集成站调度的压缩空气储能系统数学模型。针对城镇/工业园区多能互补网络中的以压缩空气储能为核心的大型电-热-冷能源集成站，采用分布鲁棒优化和主从博弈等先进数学工具对其容量规划和调度问题进行建模，进一步基于凸优化和混合整数线性规划研究快速可靠的求解算法，弥补传统优化方法在应对不确定性和多主体决策方面的不足。本项目研究有助于推动CAES技术的发展及其在综合能源系统中的应用。

新能源接入比例的不断提高对电力系统中的灵活性资源提出了更高的要求。大规模储能技术是平滑新能源出力波动性、提高输电通道平均利用率、提供灵活调峰容量及实现多能源融合的主要措施之一。为支撑2050年可再生能源发展规划和碳中和目标，美国、欧洲、中国等市场的储能容量总需求达450GW。目前已商业化的大规模物理储能技术主要包括抽水蓄能和压缩空气储能，前者约占全球储能容量的99%，但因建址条件及潜在生态环境等因素，发展已渐趋平缓。近二十年来，压缩空气储能因容量大、寿命长、响应速度快等优点得到了国内外多个大型企业及研究机构的关注，欧、美、日、中、加等国家和地区也纷纷部署了压缩空气储能技术发展路线。..先进绝热压缩空气储能（Advanced Adiabatic Compressed Air Energy Storage, AA-CAES）是一种通过空气压缩热能的回收再利用从而摒弃天然气补燃的新技术。压缩储能时, AA-CAES利用弃风（光）、低谷电等电能或风能等机械能驱动压缩机，经绝热压缩（压缩系统）回收压缩热，解耦存储空气压力势能（储气库）和压缩热能（蓄热系统）；膨胀释能时，通过绝热膨胀利用压缩热能替代天然气补燃，实现空气压力势能和压缩热能的耦合释能，清洁无碳排放。AA-CAES 是一种可灵活部署于源、网、荷侧的清洁储能技术，具有能量搬移与容量备用的常规灵活性、热电联供与热电联储的供能灵活性等独特优点。项目以挖掘AA-CAES调度灵活性、促进电-热-冷多能集成为目标，系统研究了AA-CAES的热力学特性，分析了AA-CAES电-热-冷多能联供能力与综合能效；建立了适用于电力系统调度的AA-CAES宽工况运行模型，搭建了基于Matlab/Simulink的AA-CAES仿真平台。进一步研究了AA-CAES电站层面的优化控制策略，包括AA-CAES机组的宽工况预测控制和AA-CAES电站参与电网调峰的鲁棒在线调度；构建了以CAES为核心的能源枢纽参与电力市场和电-热多能源市场的博弈模型，分析了市场均衡，对市场模式的设计提出了建议。项目研究成果有助于AA-CAES技术的推广应用，发挥AA-CAES独特的储能循环对新能源电力系统和综合能源系统的支撑作用。