基于旋转降维和稀疏谱逼近的微能源网随机优化运行方法

With the development of the micro-energy network, increasing distributed generation and combining the multi-energy bring the tricky high dimensional uncertainties (e.g. intermittent renewable power, smart electronic devices, demand response, cyber-physical system, etc.). The high-dimensional uncertainties and dynamics has increased the complexity of optimal operation of micro-energy network. This project focuses on the multi-objective stochastic optimization of micro-energy network with high-dimensional uncertainty. The contents involve primarily the following aspects: firstly, we analyze the time-varying characteristics of uncertain parameters in the micro-energy network. Considering the influence of the dependence between the uncertain parameters and states of network on the operation, we model the high-dimensional uncertain parameters and reduce the dimension. Secondly, the sparse approximation of the exact solution of stochastic problem is studied based on the spectral decomposition of vector random field. We built the deterministic equivalent model of the multi-objective stochastic optimization problem. At last, the sliced inverse regression based sparse approximation is studied to improve the accuracy of sparse approximation. Integration of uncertainty quantification technology, this project has important scientific significance and application value for the optimal operation of micro-energy network in uncertain environment. Therefore, the problem of multi-energy integration optimization is solved to improve the safety and economical operation level, it promotes effective interconnection and efficient use of diverse energy sources.

高比例可再生能源并网和电气热多能源的互联，来自间歇性新能源发电、电力电子智能设备、需求侧响应、信息物理系统等多重复杂不确定性，给微能源网优化运行与控制带来极大挑战。本项目围绕计及高维不确定性的微能源网多目标优化运行问题展开研究，研究内容包含以下几个方面：首先，分析微能源网运行中不确定参数的时变特征，以及不确定因素与系统各状态之间依赖关系对系统运行的影响，将描述多重不确定性的高维随机空间压缩映射到低维空间。其次，基于高维不确定参数的谱分解降维技术，研究随机问题精确解的稀疏谱逼近技术，建立计及风险约束微能源网多目标随机优化运行问题的低维凸确定性等价形式。最后，结合随机旋转降维技术，研究基于分段逆回归的降维压缩感知算法，提高多目标随机优化问题精确解空间的谱逼近精度。以解决微能源网多能源融合优化问题，促进多元能源有效互联和高效利用，提高微能源网在不确定环境下的安全经济运行水平。

新能源分布式发电是比较成熟且成本可控的电力减碳方案，在“双碳”目标推动下，大量分布式电源的广泛接入给电网调控带来巨大挑战。在源-网-荷-储互动增强的背景下，本项目围绕计及高维不确定性的分布式微能源网优化运行问题展开研究，研究内容包含以下几个方面：首先，分析了分布式微能源网运行中不确定参数的时变特征，考虑随机时序性对风、光间歇性可再生能源和负荷这些电网运行中的节点注入功率的随机特性进行建模，近一步剖析不确定因素与系统各状态之间依赖关系对系统运行的影响。然后，基于高维不确定参数的谱分解降维技术，研究源-网-荷多重时序不确定性建模技术，建立随机问题精确解的稀疏谱近似逼近模型。最后，应用基于多目标多层评估方法对最优调控系统进行综合评价，为多能互补互济性能评估提供理论支撑。以解决含高比例新能源的多元协同融合优化问题，通过多能源协同调控技术提高系统的降碳成效，促进能源有效互联和高效利用，为大量分布式微能源网接入下的高效减排和灵活调控提供了有益参考。