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Model predictive direct power control of energy storage quasi-Z-source grid-connected inverter

Tang Min'an, Yang Shangmei, Zhang Kaiyue, Wang Qianqian, Liu Chenggang, Dong Xuewang

Archives of Electrical Engineering

2022

Vol. 71, nr 1

21--35

In order to overcome the shortcoming of large switching losses caused by variable switching frequency appears in the conventional finite control set model predictive control (FCS-MPC) algorithm, a model predictive direct power control (MP-DPC) for an energy storage quasi-Z-source inverter (ES-qZSI) is proposed. Firstly, the power prediction model of the ES-qZSI is established based on the instantaneous power theory. Then the average voltage vector in the 𝛼𝛽 coordinate system is optimized by the power cost function. Finally, the average voltage vector is used as the modulation signal, and the corresponding switching signal with fixed frequency is generated by the shoot-through segment space vector pulse width modulation (SVPWM) technology. The simulation results show that the ES-qZSI realizes six shoot-through actions per control cycle and achieves the constant frequency control of the system, which verifies the correctness of the proposed control strategy.

Application of multi-objective fruit fly optimisation algorithm based on population Manhattan distance in distribution network reconfiguration

Tang Minan, Zhang Kaiyue, Wang Qianqian, Cheng Haipeng, Yang Shangmei, Du Hanxiao

Archives of Electrical Engineering

2021

Vol. 70, nr 2

307--323

In order to optimise the operation state of the distribution network in the presence of distributed generation (DG), to reduce network loss, balance load and improve power quality in the distribution system, a multi-objective fruit fly optimisation algorithm based on population Manhattan distance (pmdMOFOA) is presented. Firstly, the global and local exploration abilities of a fruit fly optimisation algorithm (FOA) are balanced by combining population Manhattan distance (PMD) and the dynamic step adjustment strategy to solve the problems of its weak local exploration ability and proneness to premature convergence. At the same time, Chebyshev chaotic mapping is introduced during position update of the fruit fly population to improve ability of fruit flies to escape the local optimum and avoid premature convergence. In addition, the external archive selection strategy is introduced to select the best individual in history to save in external archives according to the dominant relationship amongst individuals. The leader selection strategy, external archive update and maintenance strategy are proposed to generate a Pareto optimal solution set iteratively. Lastly, an optimal reconstruction scheme is determined by the fuzzy decision method. Compared with the standard FOA, the average convergence algebra of a pmdMOFOA is reduced by 44.58%. The distribution performance of non-dominated solutions of a pmdMOFOA, MOFOA, NSGA-III and MOPSO on the Pareto front is tested, and the results show that the pmdMOFOA has better diversity. Through the simulation and analysis of a typical IEEE 33-bus system with DG, load balance and voltage offset after reconfiguration are increased by 23.77% and 40.58%, respectively, and network loss is reduced by 57.22%, which verifies the effectiveness and efficiency of the proposed method.