考虑多重扰动下气网络瞬态特性和风电动态模糊集的电-气耦合系统协同优化方法研究

With the expansion of the installed capacity of renewable energy such as wind power and the upgrading of the exploitation and supply technology for natural gas resources, power system and natural gas system with increasingly closer relationship are faced with the dual-network coupled collaborative optimization problem across time and space scales. In this connection, this project will study the basic theory and optimization technology of dual-network cooperative operation under the combined effect of wind power uncertainty and various disturbance factors and controllable parameters such as source, network and load in natural gas system for power-gas coupled system with wind power integration based on high dimensional data mining technology, uncertainty modeling theory and distributionally robust optimization method. Firstly, a refined transient model which can accurately describe the real-time operation state of natural gas system and a hierarchical control simulation solution method are proposed. Secondly, the principal component analysis and kernel density estimation method are employed to construct dynamic fuzzy set for wind power output combining spatial-temporal correlation and probability distribution uncertainty. At last, a distributionally robust optimization for power system and a multi-dimensional performance optimization method for gas system are developed. Moreover, a multi-decision layered cooperative scheduling framework is established to solve the cooperative optimization strategy for the coupled system with the multiplex control performance level of gas system. The research results of this project are expected to provide theoretical and technical support for the collaborative optimization of power-gas coupled system with wind power integration.

随着风电等可再生能源装机规模的扩展及天然气资源开采供应技术的提升，联系日益紧密的电力系统和天然气系统面临着跨时空尺度双网耦合的协同优化问题。为此，本项目基于高维数据挖掘技术、不确定性建模理论及分布式鲁棒优化方法，针对含风电机组的电力-天然气耦合系统，研究风电出力不确定性及气系统源、网、荷等各类扰动因素及可控参数共同作用下双网络互动运行的基础理论和协同优化技术。首先，提出可准确描述天然气系统实时运行状态的精细化瞬态建模方法及其层次控制仿真求解方法；其次，利用主成分分析及核密度估计方法构建融合时空关联性、概率分布不确定性的风电出力动态模糊集；最后，提出电力系统分布式鲁棒优化及气系统多维性能优化方法，并建立耦合系统多决策协同调度框架，以求解气系统多重控制性能等级下电-气耦合系统的协同优化决策。本项目研究成果预期可对含风电机组电力-天然气耦合系统的协同优化问题提供理论和技术支持。

本课题针对含风电机组电力-天然气耦合系统的协同优化难题，从天然气网络瞬态流动建模、风电功率高维不确定性描述、多能流系统跨时空融合协同优化运行等方面开展了系统深入的研究工作，取得的主要研究成果包括：.（1）建立了源、荷多重扰动因素及网络可控条件下表征天然气潮流实时动态流动特性的精细化数学模型，并提出了基于分解-协调思想的系统层级控制快速求解方法，实现了不稳定运行工况下天然气网络瞬态运行的仿真分析。.（2）首次提出了综合考虑风电出力预测误差混合关联特性和高阶不确定性的高效动态模糊集挖掘技术，实现了对高维不确定量边界信息、多时空维度关联特性及概率分布特性的多元信息有效融合，为不确定运行条件下电力-天然气网络耦合系统的协同优化建模提供了有利的数据支撑。.（3）针对含风电机组电力网络建立了基于高效动态模糊集的分布鲁棒优化模型，并结合对偶变换和广义线性决策规则求解该不确定优化问题；另一方面，针对天然气网络建立计及运行经济性、平滑性、稳定性和备用配置有效性的多目标优化模型，并提出融入决策检验的分级优化求解方法。.（4）提出了电-气耦合系统的多决策分层协同调度框架，通过电力、天然气网络间的信息交互和博弈进行迭代求解以实现其协同优化运行。此外，对极端灾害发生时电-气耦合系统的弹性提升策略制定进行了一定的探索。.本课题研究发表了SCI论文10篇，EI论文10篇；授权国家发明专利4项；研究成果可为含风电机组电力-天然气耦合系统协同优化问题的研究提供有益的参考和借鉴。