Development of a maximum power point tracking algorithm for a counter-rotating dual-rotor wind turbine

Abstract

Relevance: although the share of renewable energy sources in the global energy system is increasing year by year, the rapid growth in demand for electricity and the limited availability of traditional fuel resources necessitate the development of new, highly efficient energy technologies. In particular, wind energy is of particular importance due to its environmental cleanliness, renewability, and wide geographical coverage. In particular, according to the Bes law, the maximum energy received from the wind flow is limited by 59.3%, and the circular flow (wake) formed behind the rotor further increases energy losses. As a result, the efficiency of SRWT systems in low and medium wind speeds is significantly reduced. From this point of view, counter-rotating two-rotary wind turbines (CRWT) have recently become the focus of scientific research. In CRWT systems, the second rotor

allows for the reuse of the circular flow energy exiting the first rotor, increasing the total power factor to 15-30%. This makes CRWT a particularly promising solution for regions with low wind speeds. However, the widespread implementation of CRWT systems is associated with a number of unresolved scientific and technical problems. One of the most important among them is the task of accurate and stable monitoring of the maximum power point tracking (MPPT). Traditional MPPT algorithms (TSR, Perturb & Observe, Hill Climb, and others) are mainly developed for single-rotor systems, and their direct application to two-rotor, aerodynamically interconnected systems is considered ineffective. In the CRWT system, due to the aerodynamic interaction between the front and rear rotors, the distribution of torques, and the zero dependence of rotational speeds, there is no single power extremum, and the problem of multidimensional optimization arises. This leads to a decrease in the stability of existing MPPT algorithms, power fluctuations, and energy losses. Moreover, despite the growing need for intelligent control, real-time adaptation, and intelligent algorithms in modern wind energy systems, research on high-speed and stable MPPT algorithms adapted for CRWT, taking into account rotor interaction, is insufficient. Existing scientific works mainly focus on aerodynamic or structural aspects, and the issue of deep integration of control algorithms is insufficiently covered.

Aim: development of a stable and highly efficient real-time monitoring algorithm for the maximum power point tracking (MPPT), taking into account aerodynamic and electromechanical interactions between the front and rear rotors for a two-rotor counter-rotation wind turbine (CRWT), as well as scientific substantiation of its energy, dynamic, and economic efficiency.

Methods: the complex of theoretical, computational, algorithmic and experimental research methods: optimization theory, gradientless search, and heuristic methods are used.

Results: an expanded mathematical model is proposed that takes into account the aerodynamic interaction between the front and rear rotors in a two-rotor wind turbine rotating oppositely. A new hybrid MPPT algorithm has been developed that determines individual optimal working points for the front and rear rotors and adaptively adjusts their interaction.