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摘要:
为提升智能优化算法辨识太阳电池参数的精度和准确度，提出一种基于排序概率量化机制和混沌扰动JAYA算法(RCJAYA)的辨识方法。RCJAYA算法根据排序概率选择不同方式对个体进行更新，以平衡局部和全局搜索能力，保持种群多样性；对最优个体进行混沌扰动，发掘更优解替代最差解，提升种群质量；采用替换策略更新陷入停滞的个体，提升算法性能。通过RCJAYA算法辨识参数得到的太阳电池单、双二极管的电流均方根误差最优值分别为9.8602×10−4 A、9.8258×10−4 A，与JAYA等5种算法对比，结果表明，RCJAYA算法更具优势。根据辨识结果计算出模拟电流，与实测电流进行比对，在单、双二极管上的平均误差分别为0.00084 A、0.00082 A，表明RCJAYA算法辨识的参数值准确可靠。
Abstract:A JAYA algorithm based on the ranking probability quantization mechanism and chaotic perturbation (RCJAYA) is proposed as a discrimination approach to increase the precision and accuracy of the intelligent optimization algorithm to detect solar cell parameters.The RCJAYA algorithm selects different ways to update individuals according to the ranking probability to balance the local and global search ability and maintain the population diversity; chaotic perturbation is applied to the optimal individuals to discover a better solution. The replacement strategy is used to update the stagnant individuals and improve the performance of the algorithm. When compared to the five algorithms such as JAYA, the root mean square error of the current of the single and double diodes of solar cells achieved by the RCJAYA algorithm is 9.8602×10−4 A and 9.8258×10−4 A, respectively. The results show that the RCJAYA algorithm has more advantages. The simulated current is calculated according to the identification results compared with the measured current, and the average error is 0.00084 A and 0.00082 A for single and double diodes, respectively, which indicates that the parameter values identified by RCJAYA are accurate and reliable.
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Key words:
- solar cell /
- parameter identification /
- JAYA algorithm /
- ranking probability /
- chaotic perturbation
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图 5 单二极管模型的RCJAYA 模拟数据和实测数据比较
Figure 5. Comparison of measured data and simulated data of RCJAYA for single diode model
图 6 双二极管模型的RCJAYA 模拟数据和实测数据比较
Figure 6. Comparison of measured data and simulated data of RCJAYA for double diode model
图 4 RCJAYA算法单、双二极管模型电流误差值比较
Figure 4. Comparison of current error value of RCJAYA algorithm single and double diode model
表 1 单、双二极管模型待辨识参数范围
Table 1. Range of parameters to be identified for single and double diode models
参数 下界 上界 $ {I}_{\mathrm{p}\mathrm{h}}/\mathrm{A} $ 0 1 $ {I}_{\mathrm{s}\mathrm{d}},{I}_{\mathrm{s}\mathrm{d}1},{I}_{\mathrm{s}\mathrm{d}2}/ {\mu }\mathrm{A} $ 0 1 $ {R}_{\mathrm{S}} $/Ω 0 0.5 $ {R}_{\mathrm{s}\mathrm{h}} $/Ω 0 100 $ n,{n}_{1},{n}_{2} $ 1 2 
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表 2 单二极管参数辨识电流RMSE值统计结果
Table 2. Statistical results of current RMSE values for single diode parameter identification
A 算法 最优值 最差值 平均值 标准差 RCJAYA 9.8602×10−4 9.8602×10−4 9.8602×10−4 1.0598×10−13 JAYA[9] 9.8946×10−4 1.4783×10−3 1.1617×10−3 1.8796×10−4 IJAYA[14] 9.8603×10−4 1.0622×10−3 9.9204×10−4 1.4033×10−5 PGJAYA[17] 9.8602×10−4 9.8603×10−4 9.8602×10−4 1.4485×10−9 STLBO[16] 9.8602×10−4 9.8655×10−4 9.8607×10−4 1.8602×10−5 GWOCS[21] 9.8607×10−4 9.9095×10−4 9.8874×10−4 2.4696×10−6
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表 3 双二极管参数辨识电流RMSE值统计结果
Table 3. Statistical results of current RMSE values for double diode parameter identification
A 算法 最优值 最差值 平均值 标准差 RCJAYA 9.8258×10−4 9.8909×10−4 9.8557×10−4 1.3743×10−6 JAYA[9] 9.8934×10−4 1.4793×10−3 1.1767×10−3 1.9356×10−4 IJAYA[14] 9.8293×10−4 1.4055×10−3 1.0269×10−3 9.8325×10−5 PGJAYA[17] 9.8263×10−4 9.9499×10−4 9.8582×10−4 2.5375×10−6 STLBO[16] 9.8252×10−4 2.4480×10−3 1.0585×10−3 2.8978×10−4 GWOCS[21] 9.8334×10−4 1.0017×10−3 9.9411×10−4 9.5937×10−6
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表 4 各算法单二极管模型最佳辨识参数
Table 4. Optimal identification parameters of single diode model for each algorithm
算法 $ {I}_{\mathrm{p}\mathrm{h}}/\mathrm{A} $ $ {I}_{\mathrm{s}\mathrm{d}}/ \mu \mathrm{A} $ $ {R}_{\mathrm{S}} $/Ω $ {R}_{\mathrm{s}\mathrm{h}} $/Ω $ n $ $ {{X}}_{\mathrm{R}\mathrm{M}\mathrm{S}\mathrm{E}} $/A RCJAYA 0.7608 0.3230 0.0364 53.7188 1.4812 9.8602×10−4 JAYA[9] 0.7608 0.3281 0.0364 54.9298 1.4828 9.8946×10−4 IJAYA[14] 0.7608 0.3228 0.0364 53.7595 1.4811 9.8603×10−4 PGJAYA[17] 0.7608 0.3230 0.0364 53.7185 1.4812 9.8602×10−4 STLBO[16] 0.7608 0.3230 0.0364 53.7184 1.4812 9.8602×10−4 GWOCS[21] 0.7608 0.3219 0.0364 53.6320 1.4808 9.8607×10−4
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表 5 各算法双二极管模型最佳辨识参数
Table 5. Optimal identification parameters of double diode model for each algorithm
算法 $ {I}_{\mathrm{p}\mathrm{h}}/\mathrm{A} $ $ {I}_{\mathrm{s}\mathrm{d}1}/ \mu \mathrm{A} $ $ {R}_{\mathrm{S}} $/Ω $ {R}_{\mathrm{s}\mathrm{h}} $/Ω $ {n}_{1} $ $ {I}_{\mathrm{s}\mathrm{d}2}/ \mu \mathrm{A} $ $ {n}_{2} $ $ { {X}}_{\mathrm{R}\mathrm{M}\mathrm{S}\mathrm{E}} $/A RCJAYA 0.7608 0.6333 0.0367 55.2141 2.0000 0.2399 1.4560 9.8258×10−4 JAYA[9] 0.7607 0.0061 0.0364 52.6575 1.8436 0.3151 1.4788 9.8934×10−4 IJAYA[14] 0.7061 0.0051 0.0376 77.8519 1.2186 0.7509 1.6247 9.8293×10−4 PGJAYA[17] 0.7608 0.2103 0.0368 55.8135 1.4450 0.8853 2.0000 9.8263×10−4 STLBO[16] 0.7608 0.2336 0.0367 55.3382 1.4538 0.6849 2.0000 9.8252×10−4 GWOCS[21] 0.7608 0.5377 0.0367 54.7331 2.0000 0.2486 1.4588 9.8334×10−4
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表 6 RCJAYA算法获得的单、双二极管模型的电压、电流和误差的计算值
Table 6. Calculated values of voltage, current and error obtained by RCJAYA for single and double diode model
编号 $ {V}_{\mathrm{L}}/\mathrm{V} $ $ {I}_{\mathrm{L}}/\mathrm{A} $ $ {I}_{\mathrm{s}\mathrm{i}\mathrm{m}-\mathrm{S}}/\mathrm{A} $ $ {I}_{\mathrm{s}\mathrm{i}\mathrm{m}-\mathrm{D}}/\mathrm{A} $ $ {I}_{\mathrm{I}\mathrm{A}\mathrm{E}-\mathrm{S}} $/A $ {I}_{\mathrm{I}\mathrm{A}\mathrm{E}-\mathrm{D}} $/A 1 −0.2057 0.7640 0.76411183 0.76399868 0.00011183 0.00000132 2 −0.1291 0.7620 0.76268722 0.76261260 0.00068722 0.00061260 3 −0.0588 0.7605 0.76137945 0.76134002 0.00087945 0.00084002 4 0.0057 0.7605 0.76017814 0.76017052 0.00032186 0.00032948 5 0.0646 0.7600 0.75907936 0.75909955 0.00092064 0.00090045 6 0.1185 0.7590 0.75806650 0.75810936 0.00093350 0.00089064 7 0.1678 0.7570 0.75711580 0.75717399 0.00011580 0.00017399 8 0.2132 0.7570 0.75616549 0.75622840 0.00083451 0.00077160 9 0.2545 0.7555 0.75511092 0.75516422 0.00038908 0.00033578 10 0.2924 0.7540 0.75368773 0.75371456 0.00031227 0.00028544 11 0.3269 0.7505 0.75141438 0.75139946 0.00091438 0.00089946 12 0.3585 0.7465 0.74737639 0.74731136 0.00087639 0.00081136 13 0.3873 0.7385 0.74013817 0.74002886 0.00163817 0.00152886 14 0.4137 0.7280 0.72740044 0.72726898 0.00059956 0.00073102 15 0.4373 0.7065 0.70698699 0.70686916 0.00048699 0.00036916 16 0.4590 0.6755 0.67528950 0.67521975 0.00021050 0.00028025 17 0.4784 0.6320 0.63076274 0.63075753 0.00123726 0.00124247 18 0.4960 0.5730 0.57193024 0.57198108 0.00106976 0.00101892 19 0.5119 0.4990 0.49961177 0.49968789 0.00061177 0.00068789 20 0.5265 0.4130 0.41366500 0.41371920 0.00066500 0.00071920 21 0.5398 0.3165 0.31754974 0.31754137 0.00104974 0.00104137 22 0.5521 0.2120 0.21223258 0.21213072 0.00023258 0.00013072 23 0.5633 0.1035 0.10238239 0.10218079 0.00111761 0.00131921 24 0.5736 −0.0100 −0.00851637 −0.00877755 0.00148363 0.00122245 25 0.5833 −0.1230 −0.12521967 −0.12553766 0.00221967 0.00253766 26 0.5900 −0.2100 −0.20810980 −0.20839172 0.00189020 0.00160828 注：$ {I}_{\mathrm{I}\mathrm{A}\mathrm{E}-\mathrm{S}} $平均误差为0.00083882 A，$ {I}_{\mathrm{I}\mathrm{A}\mathrm{E}-\mathrm{D}} $平均误差为0.00081883 A。
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