The maximum power point tracking technology for photovoltaic power generation has achieved fruitful results after years of development, However, the balance between the rapidity and stability of the maximum power point tracking and the tracking effect when the external environment is abrupt is poor. The purpose of this paper is to study a new variable step admittance increment method, and on this basis, optimize the design to achieve fast and stable tracking of the system. This paper proposed an improved fuzzy PID control algorithm, through algorithm combining fuzzy control and fuzzy PID to realize hierarchical control. This paper integrate the hierarchical idea in CSO algorithm and learning methods of part of the same generation into PSO algorithm, and obtained the improved PSO algorithm. Optimized the fuzzy PID parameters of solar photovoltaic system, and improved the software flow of the system. Using Simulink for modeling and simulation, the results show that the fuzzy PID controller optimized by PSO can smoothly reach the steady state in a short time when the step response occurs, which improved the response speed of the system, and there is no obvious overshoot, dynamic and steady-state performance performed well.

Yi Liang. Optimal Design of Solar Photovoltaic Power MPPT——Based on Fuzzy PID Control and Improved Particle Swarm Algorithm. International Journal of Engineering Technology and Construction (2021), Vol. 2, Issue 2: 1-13. https://doi.org/10.38007/IJETC.2021.020201.

[1] Kasaeian A, Eshghi A T, Sameti M. A review on the applications of nanofluids in solar energy systems. International Journal of Heat & Mass Transfer, 2015, 43(2):584-598. https://doi.org/10.1016/j.rser.2014.11.020

[2] Pospischil A, Furchi M M, Mueller T. Solar-energy conversion and light emission in an atomic monolayer p-n diode. Nature Nanotechnology, 2013, 9(4):257-261. https://doi.org/10.1038/nnano.2014.14

[3] Dincer I, Dost S. A perspective on thermal energy storage systems for solar energy applications. International Journal of Energy Research, 2015, 20(6):547-557.

[4] Hernandez R R, Easter S B, Murphy-Mariscal M L, et al. Environmental impacts of utility-scale solar energy. Renewable & Sustainable Energy Reviews, 2014, 29(7):766-779. https://doi.org/10.1016/j.rser.2013.08.041

[5] Lewis N S. Research opportunities to advance solar energy utilization.. Science, 2016, 351(6271):aad1920. https://doi.org/10.1126/science.aad1920

[6] Liu X, Coxon P R, Peters M, et al. Black silicon: fabrication methods, properties and solar energy applications. Energy & Environmental Science, 2014, 7(10):3223-3263. https://doi.org/10.1039/C4EE01152J

[7] Amankwah‐Amoah J. Solar Energy in Sub‐Saharan Africa: The Challenges and Opportunities of Technological Leapfrogging. Thunderbird International Business Review, 2015, 57(1):15-31. https://doi.org/10.1002/tie.21677

[8] Cho M, Masui H, Iwai S, et al. Three Hundred Fifty Volt Photovoltaic Power Generation in Low Earth Orbit. Journal of Spacecraft & Rockets, 2014, 51(1):379-381. https://doi.org/10.2514/1.A32559

[9] Jahromi M A Y, Farahat S, Barakati S M. Optimal size and cost analysis of stand-alone hybrid wind/photovoltaic power-generation systems. Civil Engineering Systems, 2014, 31(4):283-303.

[10] Hasanuzzaman M, Alamin A Q, Khanam S, et al. Photovoltaic power generation and its economic and environmental future in Bangladesh. Journal of Renewable & Sustainable Energy, 2015, 7(1):4527-4536. https://doi.org/10.1063/1.4906910 

[11] Kawabe K, Tanaka K. Impact of Dynamic Behavior of Photovoltaic Power Generation Systems on Short-Term Voltage Stability. IEEE Transactions on Power Systems, 2015, 30(6):3416-3424. https://doi.org/10.1109/TPWRS.2015.2390649

[12] Yu W, Sheng Z, Hong H. Cost and CO 2 reductions of solar photovoltaic power generation in China: Perspectives for 2020. Renewable & Sustainable Energy Reviews, 2014, 39(6):370-380. https://doi.org/10.1016/j.rser.2014.07.027

[13] Chao K H, Huang C H. Bidirectional DC-DC soft-switching converter for stand-alone photovoltaic power generation systems. Iet Power Electronics, 2014, 7(6):1557-1565. https://doi.org/10.1049/iet-pel.2013.0335

[14] Wang Y, Xue L, Pedram M. A Near-Optimal Model-Based Control Algorithm for Households Equipped With Residential Photovoltaic Power Generation and Energy Storage Systems. IEEE Transactions on Sustainable Energy, 2016, 7(1):77-86. https://doi.org/10.1109/TSTE.2015.2467190

[15] Banaei M R, Ardi H, Alizadeh R, et al. Non-isolated multi-input–single-output DC/DC converter for photovoltaic power generation systems. Power Electronics Iet, 2014, 7(11):2806-2816. https://doi.org/10.1049/iet-pel.2013.0977

[16] Hosenuzzaman M , Rahim N A , Selvaraj J , et al. Global prospects, progress, policies, and environmental impact of solar photovoltaic power generation. Renewable and Sustainable Energy Reviews, 2015, 41(2):284-297. https://doi.org/10.1016/j.rser.2014.08.046

[17] Sun D , Ge B , Liang W , et al. An Energy Stored Quasi-Z Source Cascade Multilevel Inverter based Photovoltaic Power Generation System. IEEE Transactions on Industrial Electronics, 2015, 62(9):1-1. https://doi.org/10.1109/TIE.2015.2499246

[18] Bergesen J D , Heath G A , Gibon T , et al. Thin-Film Photovoltaic Power Generation Offers Decreasing Greenhouse Gas Emissions and Increasing Environmental Co-benefits in the Long Term. Environmental Science & Technology, 2014, 48(16):9834-9843. https://doi.org/10.1021/es405539z

[19] Dongdong H , Zaijun W U , Xiaobo D , et al. A power quality composite control strategy based on large-scale grid-connected photovoltaic power generation. Power System Protection & Control, 2015, 43(3):107-112.

[20] Fonseca Junior J G D S, Oozeki T, Ohtake H, et al. Regional forecasts of photovoltaic power generation according to different data availability scenarios: a study of four methods. Progress in Photovoltaics Research & Applications, 2015, 23(10):1203-1218. https://doi.org/10.1002/pip.2528