基于鲁棒优化的网架重构机组恢复顺序优化

发布时间：2018-12-11 12:23

【摘要】：在当前以火电为主的系统中,大停电后机组恢复时间的长短对重构效果影响显著。针对机组启动准备时段和启动时段可能出现的时间延迟,以最小化重构期间的电量不足为优化目标,构建了计及火电机组启动时间不确定性的机组恢复顺序鲁棒优化模型。通过交叉粒子群算法与CPLEX优化求解相结合,可获得量化表征恢复效果和运行可靠性的机组恢复顺序,为调度人员应对可能出现的最严重机组恢复迟滞场景提供了更加全面的决策参考。对于调度人员自行拟定的机组恢复顺序,还可根据运行经验预估其成功实施的概率,通过CPLEX求解并筛选关键时步,为调度人员有的放矢地保证恢复效果提供量化指导。针对新英格兰10机39节点系统和某区域电网的仿真结果验证了该方法的有效性。
[Abstract]:In the current thermal power system, the recovery time of the unit after a power outage has a significant impact on the reconstruction effect. Aiming at the possible delay in start-up preparation period and start-up period and minimizing the power shortage during reconfiguration, a robust optimization model of unit recovery sequence considering the uncertainty of start-up time of thermal power unit is constructed. By combining cross-particle swarm optimization with CPLEX optimization, the recovery sequence of the unit can be obtained by quantifying the recovery effect and operation reliability. It provides a more comprehensive decision reference for dispatcher to deal with the most serious recovery delay scenario. For the unit recovery sequence drawn up by the dispatcher, the probability of its successful implementation can be estimated according to the operation experience, and the key time step can be solved and screened by CPLEX, which can provide quantitative guidance for the dispatcher to ensure the recovery effect in a targeted way. The effectiveness of the proposed method is verified by simulation results for a 10-machine 39-bus system and a regional power grid in New England.
【作者单位】：华北电力大学电气与电子工程学院;
【基金】：国家自然科学基金资助项目(51277076,51677071)
【分类号】：TM732

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