Power extraction has become a critical consideration in tidal stream turbine (TST) systems. In practice, the lumped disturbances under varying tidal current conditions may deteriorate the maximum power point tracking (MPPT) performance and cumulate fatigue damage over-rated power. Besides, the conventional pitch controllers are sensitive to parameter uncertainties of the nonlinear TST system. In this paper, a novel output power internal control strategy based on pseudo-tip-speed ratio and adaptive genetic algorithm (PTSR-AGA) is proposed to improve the anti-interference ability and reliability. The proposed control scheme consists of two parts. The first part proposes the PTSR method for MPPT to predict the TST’s operating point which contributes reducing the logical errors assigned to swell disturbances. The second part designed an AGA for the optimization of the pitch controller to conduct its angle delay. A reduced pitch control strategy is applied to the preprocessing of the pitch controller to reduce the mechanical wear over the rated power. The comparative simulation results validate the TST system can obtain a higher power efficiency of energy capture and a smoother power output with the proposed control strategies at full range of tidal current speed.

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With the increasing penetration of distributed generation (DG) in the distribution network, the original network structure of the distribution network has been changed. In addition, the randomness and intermittency of renewable power generation will also have an impact on the voltage and power flow of the distribution network. To solve this problem, this paper proposes a reactive power optimization control method for distribution network with DGs based on second-order oscillating particle swarm optimization (PSO) algorithm with a constriction factor. Considering the economic operation of the distribution network, the proposed control method realizes the coordinated operation of the DGs and battery group with the conventional static reactive power compensation device, so as to improve the voltage quality of the distribution network and reduce the system network loss. At the same time, an improved second-order oscillating PSO algorithm is proposed to improve the speed and convergence of the multiobjective algorithm. Finally, the effectiveness of the proposed control method is verified by using MATLAB/Simulink on IEEE 33 bus distribution network with DGs in both static and dynamic situations.