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At present, in the region of China Southern Power Grid, there is a case that the actual load adjustment amount of primary frequency control of some hydropower units cannot reach the theoretical value under certain working conditions, resulting in the assessment of primary frequency regulation. This paper processed the original operation data of a unit, and calculated the actual load adjustment amount and actual adjustment rate of primary frequency regulation. Compared with the theoretical value, the qualified working condition area of the primary frequency regulation process was found out. The characteristic operating points were selected in the qualified working condition area, and the multi-objective particle swarm optimization algorithm based on Pareto optimization criterion was used to find the optimal PID parameters. The simulation results show that the optimized PID parameters can make the unit have better primary frequency regulation performance index than the actual parameters of the governor.

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针对目前南方电网区域内存在水电机组在某些工况下出现一次调频实际负荷调整量达不到理论值进而造成一次调频被考核的情形,先对某机组原始运行数据进行处理,通过计算一次调频实际负荷调整量和实际调差率,观察其是否达到理论值,进而找出一次调频过程合格的工况区域,在一次调频过程合格的工况区域内选取特征工况点,并采用基于Pareto优化准则的多目标粒子群算法寻找最优的PID参数。仿真结果表明,优化后的PID参数相较于调速器实设参数可使得机组具有更为优良的一次调频性能指标。

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颜宁俊(1992-),男,硕士、工程师,研究方向为水电机组原动机及其调节系统参数与建模,E-mail:

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颜宁俊(1992-),男,硕士、工程师,研究方向为水电机组原动机及其调节系统参数与建模,E-mail:

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颜宁俊(1992-),男,硕士、工程师,研究方向为水电机组原动机及其调节系统参数与建模,E-mail:

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颜宁俊
水电能源科学 | 机电与控制工程 2023,41(7): 201-204
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水电能源科学 | 机电与控制工程 2023, 41(7): 201-204
基于多目标粒子群算法的水电机组一次调频性能分析及参数优化
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颜宁俊
作者信息
  • 大唐水电科学技术研究院,广西 南宁 530000
  • 颜宁俊(1992-),男,硕士、工程师,研究方向为水电机组原动机及其调节系统参数与建模,E-mail:

Performance Analysis and Parameter Optimization of Primary Frequency Regulation of Hydropower Units Based on Multi-objective Particle Swarm Optimization Algorithm
Ning-jun YAN
Affiliations
  • Datang Hydropower Science & Technology Research Institute, Nanning 530000, China
出版时间: 2023-07-25 doi: 10.20040/j.cnki.1000-7709.2023.20220590
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针对目前南方电网区域内存在水电机组在某些工况下出现一次调频实际负荷调整量达不到理论值进而造成一次调频被考核的情形,先对某机组原始运行数据进行处理,通过计算一次调频实际负荷调整量和实际调差率,观察其是否达到理论值,进而找出一次调频过程合格的工况区域,在一次调频过程合格的工况区域内选取特征工况点,并采用基于Pareto优化准则的多目标粒子群算法寻找最优的PID参数。仿真结果表明,优化后的PID参数相较于调速器实设参数可使得机组具有更为优良的一次调频性能指标。

水电机组  /  一次调频  /  性能分析  /  参数优化  /  多目标粒子群算法

At present, in the region of China Southern Power Grid, there is a case that the actual load adjustment amount of primary frequency control of some hydropower units cannot reach the theoretical value under certain working conditions, resulting in the assessment of primary frequency regulation. This paper processed the original operation data of a unit, and calculated the actual load adjustment amount and actual adjustment rate of primary frequency regulation. Compared with the theoretical value, the qualified working condition area of the primary frequency regulation process was found out. The characteristic operating points were selected in the qualified working condition area, and the multi-objective particle swarm optimization algorithm based on Pareto optimization criterion was used to find the optimal PID parameters. The simulation results show that the optimized PID parameters can make the unit have better primary frequency regulation performance index than the actual parameters of the governor.

hydropower units  /  primary frequency regulation  /  performance analysis  /  parameter optimization  /  multi-objective particle swarm optimization algorithm
颜宁俊. 基于多目标粒子群算法的水电机组一次调频性能分析及参数优化. 水电能源科学, 2023 , 41 (7) : 201 -204 . DOI: 10.20040/j.cnki.1000-7709.2023.20220590
Ning-jun YAN. Performance Analysis and Parameter Optimization of Primary Frequency Regulation of Hydropower Units Based on Multi-objective Particle Swarm Optimization Algorithm[J]. Water Resources and Power, 2023 , 41 (7) : 201 -204 . DOI: 10.20040/j.cnki.1000-7709.2023.20220590
2023年第41卷第7期
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doi: 10.20040/j.cnki.1000-7709.2023.20220590
  • 接收时间:2022-03-27
  • 首发时间:2026-01-28
  • 出版时间:2023-07-25
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  • 收稿日期:2022-03-27
  • 修回日期:2022-09-14
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    大唐水电科学技术研究院,广西 南宁 530000
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2种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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