Optimization and evaluation of simulation model for diesel generator set with pulse load
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摘要: 针对柴油发电机组-三相不控整流器-DC/DC变换器-脉冲负载系统中柴油发电机组的输出特性，提出仿真模型与试验电源输出电压（流）波形契合度的评价指标，以判断模型的仿真程度；提出了基于反向（BP）传播神经网络算法的同步发电机励磁电压输出动态限幅方法，应用于脉冲负载下柴油发电机组的模型优化。试验验证表明：27组算例中，初始仿真模型有18组波形实时契合度值不足90%，优化仿真模型27组值均大于90%。说明本文提出的优化方法使仿真模型比初始模型更加有效，可应用于后续柴油发电机组带脉冲负载系统的研究。
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关键词:
- 模型优化 /
- 脉冲负载 /
- 反向传播神经网络算法 /
- 波形实时契合度 /
- 动态限幅方法
Abstract: Aiming at the output characteristics of diesel generator set with pulse load, an index is proposed to evaluate the consistency of output voltage (current) waveform to judge the simulation degree of the model. Also, a dynamic limiting method for synchronous generator excitation voltage output based on BP neural network algorithm is proposed, and it is applied to the model optimization of diesel generator set. Experimental results show that among the 27 sets of examples, 18 groups’ real-time waveform proximity (RWP) values are less than 90% in the original simulation but in the optimized simulation, the RWP values of all the test groups are higher than 90%, indicating that the optimized simulation model is more effective, and can be applied to further research on diesel generator set with pulse load. -
图 2 MATLAB/Simulink平台DGS-PL系统初始仿真模型
Figure 2. Initial simulation model of DGS-PL system
图 3 初始仿真模型电源输出电压波形与试验波形对比图
Figure 3. Comparison of AC output voltage waveforms between initial simulation and test
图 4 初始仿真模型电源输出电流波形与试验波形对比图
Figure 4. Comparison of AC output current waveforms between initial simulation and test
图 5 初始仿真模型电源输出频率与试验对比图
Figure 5. Comparison of AC frequency between initial simulation and test
图 6 仿真模型电源输出电压波形与试验波形
Figure 6. AC output voltage waveforms of initial simulation and test
图 7 采样点5000～5500区间的波形ue与us
Figure 7. Waveforms of sample point 5000 to 5500 of ue and us
图 8 励磁参考电压限值的柴油发电机组仿真模型
Figure 8. Simulation model of diesel generator set with limiting reference excitation voltage
图 10 初始仿真模型、优化仿真模型及试验电源输出电压波形对比图
Figure 10. Comparison waveforms of initial simulation, optimized simulation and test
表 1 初始仿真模型电源输出电压采样波形契合度值
Table 1. Real-time waveform proximity values of AC output voltage of initial simulation
group Pk/kW D/% Ts/ms R/% group Pk/kW D/% Ts/ms R/% group Pk/kW D/% Ts/ms R/% 1 15 10 20 89.93 10 30 10 20 86.81 19 50 10 20 85.71 2 15 10 40 91.09 11 30 10 40 89.65 20 50 10 40 89.39 3 15 10 80 88.58 12 30 10 80 89.77 21 50 10 80 88.60 4 15 50 20 90.06 13 30 50 20 89.59 22 50 50 20 87.69 5 15 50 40 95.02 14 30 50 40 93.40 23 50 50 40 93.31 6 15 50 80 92.88 15 30 50 80 92.22 24 50 50 80 91.85 7 15 90 20 89.99 16 30 90 20 84.24 25 50 90 20 82.74 8 15 90 40 90.70 17 30 90 40 85.49 26 50 90 40 85.57 9 15 90 80 86.45 18 30 90 80 84.75 27 50 90 80 86.30 
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表 2 BP神经网络参数辨识的学习样本
Table 2. Learning samples for BP neural network parameter recognition
group Pk/kW D/% Ts/ms Ipk/A Uac/V $\bar f $/Hz VH/V VL/V 1 30 50 2 34.91 251.73 49.27 4.20 4.00 2 30 50 10 35.06 250.69 48.93 4.20 4.00 3 30 50 20 34.83 250.37 49.11 4.20 4.00 36 40 85 56 35.71 250.26 49.21 5.00 4.50 37 40 90 56 34.02 251.78 48.68 6.00 4.60 38 50 40 56 35.01 250.19 48.99 6.00 4.00 63 15 10 80 35.24 250.23 48.93 4.00 3.70 64 15 10 90 36.58 249.96 48.78 4.00 3.65 65 15 10 100 37.05 249.88 49.02 4.00 3.65
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表 3 优化仿真模型电源输出电压采样波形契合度值
Table 3. Real-time waveform proximity values of AC output voltage of optimized simulation
group Pk/kW D/% Ts/ms R/% group Pk/kW D/% Ts/ms R/% group Pk/kW D/% Ts/ms R/% 1 15 10 20 96.73 10 30 10 20 94.17 19 50 10 20 92.59 2 15 10 40 99.14 11 30 10 40 97.91 20 50 10 40 94.37 3 15 10 80 97.44 12 30 10 80 96.37 21 50 10 80 94.6 4 15 50 20 97.01 13 30 50 20 97.72 22 50 50 20 93.11 5 15 50 40 97.7 14 30 50 40 98.87 23 50 50 40 94.93 6 15 50 80 96.69 15 30 50 80 97.90 24 50 50 80 94.48 7 15 90 20 95.88 16 30 90 20 96.18 25 50 90 20 91.4 8 15 90 40 95.42 17 30 90 40 95.69 26 50 90 40 92.37 9 15 90 80 96.39 18 30 90 80 93.83 27 50 90 80 90.82
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