Aim. This work presents the amelioration of direct power control using synergetic-super twisting algorithms for asynchronous generators integrated into dual-rotor wind turbine systems. Method. The main role of the direct power control is to control the active and reactive powers and reduce the harmonic distortion of stator current of asynchronous generator for variable speed dual-rotor wind turbine systems. The traditional strategy is more attractive due to its high efficiency and simple algorithm. Super twisting algorithms are a non-linear command strategy; characterized by robustness against the parameters change or disturbances, it gives a good power quality under different conditions such as changing generator parameters. Novelty. Synergetic-super twisting algorithms are designed. Synergetic-super twisting algorithms construction is based on synergetic command and super twisting algorithms in order to obtain a robust control strategy and a fast system with acceptable precision. We use in our study a 1.5 MW asynchronous generator integrated to dual-rotor wind turbine system in order to regulate the active and reactive powers. Results. As shown in the results figures using synergetic-super twisting algorithms the ameliorate performances especially minimizes the torque, active and reactive power undulations, and reduces harmonic distortion of stator current (THD = 0.19 %) compared to traditional strategy.

In the present work, a new approach for improving voltage stability by optimal location of the Flexible AC Transmission Systems (FACTS) devices has been discussed. We used Genetic Algorithm (GA) as an optimization technique to search the good placements of different FACTS systems in great electrical networks and its contribution to enhance voltage stability. Various FACTS devices were used in our study such as SVC, TCSC, SSSC, STATCOM, TCVR, TCPST and UPFC. The search of optimal parameters of those devices has been also investigated. The method presented in the paper was tested by using Matlab/environment. In addition, the proposed method has been implemented and tested on various IEEE power systems; 14Bus, 57Bus, and 118Bus. The obtained results show the validity of the proposed method.

Aim. This paper presents the minimization of reactive and active power ripples of doubly fed induction generators using super twisting algorithms and pulse width modulation based on neuro-fuzzy algorithms. Method. The main role of the indirect active and reactive power control is to regulate and control the reactive and active powers of doubly fed induction generators for variable speed dual-rotor wind power systems. The indirect field-oriented control is a classical control scheme and simple structure. Pulse width modulation based on an adaptive-network-based fuzzy inference system is a new modulation technique; characterized by a simple algorithm, which gives a good harmonic distortion compared to other techniques. Novelty. adaptive-network-based fuzzy inference system-pulse width modulation is proposed. Proposed modulation technique construction is based on traditional pulse width modulation and adaptive-network-based fuzzy inference system to obtain a robust modulation technique and reduces the harmonic distortion of stator current. We use in our study a 1.5 MW doubly-fed induction generator integrated into a dual-rotor wind power system to reduce the torque, current, active power, and reactive power ripples. Results. As shown in the results figures using adaptive-network-based fuzzy inference system-pulse width modulation technique ameliorate effectiveness especially reduces the reactive power, torque, stator current, active power ripples, and minimizes harmonic distortion of current (0.08 %) compared to classical control.