A Review of Control Techniques for Wind Energy Conversion System

Abstract

Wind energy is the most efficient and advanced form of renewable energy (RE) in recent decades, and an effective controller is required to regulate the power generated by wind energy. This study provides an overview of state-of-the-art control strategies for wind energy conversion systems (WECS). Studies on the pitch angle controller, the maximum power point tracking (MPPT) controller, the machine side controller (MSC), and the grid side controller (GSC) are reviewed and discussed. Related works are analyzed, including evolution, software used, input and output parameters, specifications, merits, and limitations of different control techniques. The analysis shows that better performance can be obtained by the adaptive and soft-computing based pitch angle controller and MPPT controller, the field-oriented control for MSC, and the voltage-oriented control for GSC. This study provides an appropriate benchmark for further wind energy research.

Hybrid two‐stage adaptive maximum power point tracking for stand‐alone, grid integration, and partial shaded PV system

“…Traditional approaches are often utilised in a wide range of applications since they are simple and inexpensive to execute like perturb and observe (P&O), incremental conductance (INC), and so forth. [7][8][9][10] Even though P&O, and INC MPPT strategies are popular and work well when irradiance is uniform, they cannot track the MPP when irradiance changes quickly and there are partial shading conditions (PSC). These strategies also suffer from significant steady-state oscillations and poor convergence speed, which are their biggest problems.…”

“…There are two primary categories that can be used to classify solar MPPT algorithms: traditional and soft computing MPPT approaches. Traditional approaches are often utilised in a wide range of applications since they are simple and inexpensive to execute like perturb and observe (P&O), incremental conductance (INC), and so forth 7–10 . Even though P&O, and INC MPPT strategies are popular and work well when irradiance is uniform, they cannot track the MPP when irradiance changes quickly and there are partial shading conditions (PSC).…”

Giant Trevally Optimization Approach for Probabilistic Optimal Power Flow of Power Systems Including Renewable Energy Systems Uncertainty

“…The symbol Γ(.) indicates the incomplete gamma function, while R stands for solar irradiance, which is quantified in W/m 2 .…”

“…In recent years, the power grid has seen a significant surge in the incorporation of RESs, notably wind and photovoltaic systems [1,2]. These sources offer significant advantages, such as reduced pollution and the conservation of resources.…”

“…However, their integration into power systems has introduced new challenges due to growing uncertainties in load demands and variations in power production. Consequently, effectively managing these sources is pivotal for their successful integration into the network, ensuring a safe and financially viable energy market [1][2][3]. To achieve this, it is crucial to account for the probabilistic nature of WE and PV units while integrating such intermittent power sources into the grid.…”