大规模电力系统恢复的网架重构多目标分层协调优化

Aiming at the decision-making optimization problems of power system black-start restoration, this project investigates a multi-objective coordinative optimization technique of skeleton-network reconfiguration by proposing a two-layer unit restoration framework. The continuous dynamic process of network reconfiguration is changed into a multi-step sequential restoring process through partitioning the time axis for the system restoration, and in each time step, the optimization model is built with the consideration of the whole process optimization, the overall optimization of whole reconfiguration is then realized by the decision optimization of all the time steps. The unit restarting during the network reconfiguration is treated as a two-layer restoration process -network-layer unit restarting and plant-layer unit restarting，in view of the important influence of restarting of the first unit in each plant to the network reconfiguration, the optimization of the network reconfiguration is then modeled as a multi-objective hierarchical optimization problem of the network-layer unit restarting, the plant-layer unit restarting and restoration of the important loads. The network-layer unit restarting and the plant-layer unit restarting are separately modeled with consideration of their different restoration objective and influencing factors. With full analysis of the restoration requirements of the important loads in network reconfiguration, an evaluation model of the load importance is established, and the load restoration optimization model and solving algorithm are then developed. Based on the optimization models of the two-layer unit restarting framework and the restoration of the important loads, a multi-objective coordinative optimization model is built for the overall network-reconfiguration optimization, then the solving algorithm is developed. The investigated optimization method of network reconfiguration can determine the restarting sequence of all the units and the recovery sequence of important loads, realize the multi-objective hierarchical coordinative optimization of network reconfiguration. It will be of great importance to determine the optimized decisions of power system black-start restoration.

本项目针对黑启动恢复的决策优化问题，研究考虑机组分层恢复的网架重构多目标协调优化方法。将连续的网架重构过程划分为一系列恢复时段，建立每一时段考虑对后续网架重构影响的恢复决策模型，基于分时段的恢复决策实现整个网架重构过程的总体优化。研究机组的分层恢复策略，将网架重构转化为网络层机组恢复、厂站层机组恢复和重要负荷恢复的多目标分层优化问题。分析网络层机组和厂站层机组恢复的不同目标及影响因素，分别建立两层机组恢复的优化模型并提出各自的求解算法；研究网架重构对负荷恢复的要求，建立负荷重要性评价模型，提出网架重构中负荷恢复的优化方法；基于所建立的机组分层恢复和重要负荷恢复的优化模型，构建每一时段的网架重构多目标分层优化模型，并研究其求解算法。所提出的网架重构方法考虑系统中所有机组的恢复并同时对网架重构阶段的负荷恢复进行优化，实现了网架重构过程的总体优化决策，对大规模电力系统的黑启动恢复具有重要意义。

本项目针对大停电后电力系统的恢复决策问题，研究基于机组分层恢复的网架重构多目标协调优化方法。将连续的网架重构过程划分为一系列顺序执行的恢复时段并建立兼顾整个恢复过程的分时段多目标优化模型，基于分时段的恢复决策实现整个网架重构过程的总体优化。研究机组分层恢复策略，将发电厂的机组分为网络层机组和厂站层机组，提出了机组分层协调恢复的多目标优化模型。针对机组的启动效率随停机时间逐渐衰减的的工程实际，建立了考虑机组启动效率衰减的机组恢复顺序优化模型。研究了网架重构过程中重要负荷恢复的特点和要求，建立了负荷重要性综合评价模型，提出了考虑系统运行安全因素的负荷恢复的多目标优化方法。研究恢复路径的优化机制，提出用于路径优选的动态节点重要度指标。针对网架重构阶段通常形成的树状网架由于负荷陆续恢复可能出现的线路过载问题，提出一种以消除线路过载为目标的环网恢复决策优化方法。研究机组恢复和负荷恢复的协调机制，建立了协调网络层机组、厂站层机组和重要负荷恢复的网架重构多目标优化模型并结合分层序列法进行了优化求解。研究了串并行恢复模式下的恢复时段的动态划分机制，提出时步长度的动态确定方法，以机组恢复为核心建立了网架重构的多时段双层协调优化模型并采用基于状态优选的多种群遗传算法进行求解。提出一种网架重构决策的两步优化策略，建立了协调机组、特级负荷和线路恢复的网架重构分时段全局优化模型，结合非支配近邻免疫算法和变异系数法进行了求解。将网架重构和扩展黑启动决策结合考虑，研究了扩展黑启动方案的后续网架重构的恢复效果，并提出考虑系统恢复全过程效果的扩展黑启动方案综合评价方法。该项目研究提出的网架重构多目标分层和分时段协调优化的模型和求解方法，对大规模电力系统安全防御和恢复控制具有重要参考价值。