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作 者:周攀 周建中[2] 赖昕杰 邓磊 许颜贺 ZHOU Pan;ZHOU Jianzhong;LAI Xinjie;DENG Lei;XU Yanhe(Technology Center,State Grid Xinyuan Company Ltd.,Beijing 100161,China;School of Hydropower and Information Engineering,Huazhong University of Science and Technology,Wuhan 430074,Hubei,China)
机构地区:[1]国网新源控股有限公司技术中心,北京100161 [2]华中科技大学水电与数字化工程学院,湖北武汉430074
出 处:《水力发电》2020年第3期85-90,共6页Water Power
基 金:国家重点研发计划课题(2016YFC0402205);国家电网公司科技项目(52573015000G)。
摘 要:为提高抽水蓄能机组低水头工况下的控制品质,提出了一种基于精细化模型的抽水蓄能机组低水头分数阶PID(FOPID)控制多目标优化策略。首先,充分考虑过水系统、水泵水轮机等机构非线性,建立抽水蓄能机组调节系统精细化模型。在此基础上,引入时间绝对误差积分指标(ITAE)衡量FOPID的控制性能,构造额定水头和低水头工况下机组控制品质的目标函数。进一步,提出了混合变异-邻域搜索多目标粒子群算法对所建模型进行求解。结果表明,本文提出的多目标优化策略在保证机组额定水头工况控制性能的同时提升了机组在低水头工况下的控制品质,优化结果可为机组的安全稳定运行提供决策支持。In order to improve the control quality of pumped-storage units under low water head condition,a kind of multi-objective optimization strategy for fractional PID(FOPID)controller is proposed based on the refined model of pump-turbine governing system(PTGS).Firstly,the refined model of PTGS is constructed by fully considering the nonlinearity of water diversion system and pump-turbine.Then,the integral of time multiplied absolute error criterion(ITAE)is adopted as objectives to evaluate the control performance of FOPID under rated and low water head conditions.Moreover,the hybrid-mutation and neighbourhood-search mechanisms are introduced into the multi-objective particle swarm optimization to solve the refined model.The result shows that the proposed strategy is able to significantly improve the control quality of PTGS under low water head condition and provide decision support for the stable operation of pumped-storage units.
关 键 词:抽水蓄能机组 低水头工况 分数阶PID 粒子群算法 多目标优化
分 类 号:TV743[水利工程—水利水电工程]
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