四川电网智能调度系统的设计与实现  被引量:2

Design and Implementation of Intelligent Scheduling System for Sichuan Power Grid

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作  者:陈颖[1] 周剑[1] 银涛[1] 张宏图[1] 刘巍[1] 何川[1] 王岸[1] 付凤翔 

机构地区:[1]国网四川省电力公司,四川成都610094 [2]四川中电启明星信息技术有限公司,四川成都610041

出  处:《四川电力技术》2016年第3期75-79,共5页Sichuan Electric Power Technology

摘  要:截止目前,四川省统一调度电厂200多家,电厂众多、情况复杂并且约束条件多,调度实时分析自动化程度不高,调峰时压力较大;并且对实时出力情况交互困难,对超短期发电出力实时调整缺乏有效手段进行算法支撑,发电出力实时调整需要综合考虑超短期负荷预测、日内用电计划、日内发电计划、联络线计划、流域水情变化及断面潮流限额。采用合理分配算法,计算出合理的电厂实时发电调令,并自动群发给满足算法要求的电厂,保证电网的发用电平衡,实现安全调度的科学执行。四川电网智能调度系统的建设,优化发电出力的实时调整,智能科学地发布调令,提高了发电出力调整的工作效率和规范性,实现发电出力实时调整工作的智能化,保障了电网安全运行。So far, there are more than 200 unified-dispatched power plants .Because there are so many power plants , the sit-uation is more complicated and constrained .The degree of automation of real -time scheduling analysis is not high , the pres-sure is higher during peak load regulation , the real-time interaction of output is difficult to be done , and there lacks efficient measures for real-time regulation of ultra -short -term generation output .The real -time regulation of generation output must consider many situations , such as ultra-short-term load forecasting , intraday electricity supply plan , intraday genera-tion scheduling , tie line planning , watershed hydrologic changes and interface power flow limitation , the reasonable real -time generation dispatching order is calculated using the reasonable allocation algorithm and automatically batched sending to the power plants who meet the requirements of the algorithm so as to ensure the balance of power supply and generation and to a -chieve the scientific implementation of security scheduling .The construction of intelligent scheduling system for Sichuan power grid optimizes the real-time regulation of generation output , issues the dispatching order scientifically , improves the efficien-cy and normalization of generation output regulation , realizes the intelligent real -time regulation of generation output and en-sures the safe operation of power grid .

关 键 词:智能调度 实时调度 超短期负荷预测 

分 类 号:TM734[电气工程—电力系统及自动化]

 

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