Due to the economic and technical advantages, the use of solar energy is expanding in developed countries. The extraction of maximum power in solar power plants is an important issue that requires extensive research. Extracting the maximum possible power in solar power plants can increase the efficiency of this type of renewable energy sources (RESs). Climatic condition is a very important feature of solar systems. In fact, radiation and temperature are two important parameters that affect the efficiency of solar systems. This paper suggests a novel maximum power point tracking (MPPT) technique based on the sliding mode controller (SMC) to extract the maximum power of photovoltaic (PV) systems in different climatic circumstances. To obtain the optimal coefficients of the SMC online, the Grey wolf optimizer (GWO) algorithm is employed. SMC coefficients are applied for the variable perturb and observe (P&O) step of MPPT. The proposed GWO-SMC controller can eliminate oscillations in the transient mode and guarantee stability. The findings of the simulation indicate that with the use of an MPPT controller for the solar-PV system, such as P&O, Fuzzy Logic (FLC), Incremental Conductance (INC), the β method, and hill climbing (HC) MPPT, the system will operate more efficiently. The method that has been suggested is tested in a number of different climate conditions. The findings indicate that the proposed technique has an efficiency of 99%, which demonstrates a substantially superior response time when reaching the MPP in comparison to prevalent methods, which have an efficiency of 92 to 97%. The results of the simulations allow for the various approaches to be ranked as follows: 1. GWO-SMC, 2. FLC, 3. INC, 4. β method, 5. P&O, 6. HC with response times of 0.14 s, 0.17 s, 0.23 s, 0.25, 0.28 s and 0.35, respectively. The fluctuations using the combinatorial GWO-SMC technique is 4.31 W, while that of the P&O is 74.56 W. Through simulation and testing with the MATLAB software, the developed method's performance is evaluated to make a comparison.
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Maximum power point tracking
Sliding mode controller
Grey wolf optimizer
Perturb and observe
Renewable energy sources
Fuzzy logic controller
Artificial neural networks
Partial shading conditions
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This work was supported by the National Natural Science Foundation of China (No.61862051), the Science and Technology Foundation of Guizhou Province (No.ZK549, No. 1299), the Top-notch Talent Program of Guizhou province (No.KY080), the Natural Science Foundation of Education of Guizhou province(No.203) and the Funds of Qiannan Normal University for Nationalities (No. qnsy2018003, No. qnsy2019rc09, No. qnsy2018JS013, No. qnsyrc201715).
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Hai, T., Zain, J.M. & Nakamura, H. Maximum power point tracking technique based on variable step size with sliding mode controller in photovoltaic system. Soft Comput 27, 3829–3845 (2023). https://doi.org/10.1007/s00500-022-07588-6
- Photovoltaic (PV)
- Maximum power point (MPP)
- Grey wolf optimizer (GWO) algorithm