论文部分内容阅读
设计了一个应用于大停电事故恢复的基于案例推理系统。系统纵向采用分层结构,抽象层体现恢复过程的一般策略,具体层案例包含恢复操作的具体措施。系统横向分成黑启动模块、网架和负荷恢复功能模块。黑启动模块中的抽象层用一个定性进程理论模型表示,模型考虑了黑启动中的主要限制条件和各类机组的启动特性,发电容量调度算法用于具体层的修正。网架、负荷恢复模块的抽象层和具体层由详细程度不同的系统潮流图表示。开发了串并行送电阶段优化算法、系统网架及负荷恢复优化算法,用于具体层的修正。该系统以基于案例推理作为主框架,把定性分析和定量分析、理论研究和电力部门的实际经验很好地结合起来,多种在线优化算法提高了系统的灵活性。
A case-based reasoning system is designed for the recovery of blackouts. The system uses a hierarchical structure vertically, the abstract layer reflects the general strategy of the recovery process, and the concrete layer case contains specific measures for the recovery operation. System is divided into black start-up module, grid and load recovery module. The abstraction layer in the black-start module is represented by a qualitative process theory model that takes into account the main constraints in black-start and the startup characteristics of various gensets, and the generation capacity scheduling algorithm for the correction of specific layers. Grid, load recovery module abstraction layer and the specific level by the different levels of detail of the system power flow diagram. Developed the serial and parallel transmission phase optimization algorithm, system grid and load recovery optimization algorithm for the correction of specific layers. The system based on case-based reasoning as the main framework, the qualitative analysis and quantitative analysis, theoretical research and practical experience of the power sector, a variety of online optimization algorithm to improve the system flexibility.