基于Hausdorff距离的电-热-气综合能源系统分布鲁棒优化调度

Distributed Robust Optimal Scheduling of Electric Thermal Gas Integrated Energy System Based on Hausdorff Distance

电-热-气综合能源系统(combined electricity-gas-heat system,CEGHS)的优化调度已成为国内外研究的热点。为进一步分析CEGHS各网间的互补特性及优化调度潜力,提高新能源的消纳能力。首先以热电联产机组、燃气轮机、P2G装置等耦合元件为基础,建立以系统综合成本最优为目标的CEGHS优化调度模型。其次,针对传统鲁棒优化在处理风电不确定性问题上的局限性,基于豪斯多夫(Hausdorff)距离在整体相似性度量上的特性,推导出基于数据驱动的不确定性概率分布集,构建基于Hausdorff距离的CEGHS分布鲁棒优化调度模型。最后,针对模型中非线性方程复杂且求解困难的问题,将CEGHS模型中的非线性方程通过不同的线性化手段进行转换,并采用两阶段分布鲁棒优化提高求解效率。算例采用改进的CEGHS系统进行仿真,结果表明了所提模型的可行性和优化调度方法的优势。

The optimal scheduling of combined electricity-gas-heat system(CEGHS) has become a hot research spot at home and abroad.In order to further analyze the complementary characteristics and optimal scheduling potential and improve the new energy consumption capacity between networks of CEGHS,this paper firstly establishes the CEGHS optimal scheduling model aiming at the optimal comprehensive cost of the system based on the coupling components such as cogeneration units,gas turbines and P2G devices.Secondly,in view of the limitations of the traditional robust optimization in dealing with the wind power uncertainty,based on the characteristics of Hausdorff distance in the overall similarity measurement,a data-driven-based uncertainty probability distribution set is derived,and the distribution robust optimal scheduling model of electric heating gas CEGHS based on the Hausdorff distance is constructed.Finally,aiming at the problem that the nonlinear equations in the model are complex and difficult to solve,the nonlinear equations in the CEGHS model are transformed by different linearization methods,and a two-stage distributed robust optimization is adopted to improve the solution efficiency.The example is simulated with the improved CEGHS system,and the results show the feasibility of the proposed model and the advantages of the optimal scheduling method.