Abstract
The parallel and off grid switching of distributed photovoltaic power grid will cause sudden changes in voltage and current, which is a key factor affecting its stable operation. Therefore, a research on the parallel and off grid smooth switching control method of distributed photovoltaic power grid based on deep reinforcement learning is proposed. The in-depth reinforcement learning method DQN algorithm is used to build the energy management model of the distributed photovoltaic power grid, explore the characteristics and laws of the distributed photovoltaic power grid, and on this basis, in-depth analysis of the transient phenomenon of the parallel off grid switching of the distributed photovoltaic power grid is carried out. Based on the PQ and VF control principles, the grid connected controller and the off grid controller are designed, and the smooth parallel off grid switching control strategy is formulated, The smooth switching control of the parallel and off grid of the distributed photovoltaic power grid can be achieved by implementing the strategy. The experimental data show that the minimum value of the sudden change coefficient of voltage and current obtained by the proposed method is 0.1 and 0.2, which fully proves that the proposed method has better control effect of parallel and off grid switching.
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References
Wang, Z., Zhang, J., Zhang, Y.: Research on photovoltaic output power prediction method based on machine learning. Comput. Simul. 37(4), 71–75,163 (2020)
Tévar-Bartolomé, G., Gómez-Expósito, A., Arcos-Vargas, A., RodrÃguez-Montañés, M.: Network impact of increasing distributed PV hosting: A utility-scale case study. Solar Energy 217, 173–186 (2021)
Qu, Y., Zeng Kai, O., Hong, Z., et al.: Island detection and seamless switching control of pv-bes microgrid with phase-locked loop based on improved Gaussian filter. Adv. Power Syst. Hydroelectr. Eng. 38(7), 38–46 (2022)
Shiwei, X., Qingquan, J., Pan, L., et al.: Efficiency improvement control strategy for photovoltaic generation through dc dynamic reconfiguration. Trans. China Electrotech. Society 36(9), 1761–1770 (2021)
Chang, W., Wu, L., Wu, C., et al.: Coactive design of explainable agent-based task planning and deep reinforcement learning for human-UAVs teamwork. Chinese J. Aeronaut. 33(11), 110–125 (2020)
Liu, Q., Liu, Z., Xiong, B., et al.: Deep reinforcement learning-based safe interaction for industrial human-robot collaboration using intrinsic reward function[J]. Adv. Eng. Inform. 49(12), 101360 (2021)
Patel, N., Gupta, N., Kumar, A., Babu, B.C., et al.: Pseudo affine projection assisted multitasking approach for power quality improvement in grid-interactive photovoltaic (PV) system. IET Power Electron. 13(13), 2905–2916 (2020)
Bakhshi-Jafarabadi, R., Sadeh, J.: New voltage feedback-based islanding detection method for grid-connected photovoltaic systems of microgrid with zero non-detection zone. IET Renew. Power Gener.Gener. 14(10), 1710–1719 (2020)
Hussein, A.A., Chen, X., Alharbi, M., et al.: Design of a grid-tie photovoltaic system with a controlled total harmonic distortion and tri maximum power point tracking. IEEE Trans. Power Electron. 35(5), 4780–4790 (2020)
Ai, C., Gao, W., Chen, L., et al.: Bivariate grid-connection speed control of hydraulic wind turbines. J. Franklin Inst. 358(1), 296–320 (2020)
Du, W., Wang, Y., Wang, X., et al.: Magnifying effect of weak grid connection for a PMSG to induce torsional sub-synchronous oscillations under the condition of open-loop modal resonance. IET Renew. Power Gener. Gener. 14(4), 580–590 (2020)
Babu P.N., Guerrero, P., Siano, P., et al.: An improved adaptive control strategy in grid-tied PV system with active power filter for power quality enhancement. IEEE Syst. J. 15(2), 2859–2870 (2021)
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Liu, X., Liu, W., Liu, L., Zhou, H., Liu, Y., Xu, Y. (2024). Smooth Switching Control Method for Parallel and Off Grid of Distributed Photovoltaic Power Grid Based on Deep Reinforcement Learning. In: Wang, B., Hu, Z., Jiang, X., Zhang, YD. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 532. Springer, Cham. https://doi.org/10.1007/978-3-031-50571-3_11
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