# Improving the Energy Conversion Efficiency for Hydrokinetic Turbines Using MPPT Controller
## 1 Introduction
Because the velocity of flowing water is variable and unpredictable, developing reliable methods to track the optimal operation point of the hydrokinetic turbines is necessary in order to extract the maximum available power at a certain time. In [11], MATLAB software was used to obtain real-time point to point discrete MPPT simulation applicable to the wind energy system, which uses a permanent magnet synchronous generator (PMSG). The system model has a three-phase rectifier and a buck converter with its input ratio controlled by a PWM (pulse width modulation) signal from the maximum power point controller. In [12], an MPPT algorithm that uses a neural network compensator for the uncertainties in wind turbine generation systems is proposed. A proportional integral (PI) controller determines the duty cycle of the DC/DC converter and the parameters are determined by a genetic algorithm. By imposing certain variations for the wind speed and air density, the power coefficient is kept approximately at its maximum value. Other studies, such as [13], focused on implementing the MPPT algorithm to hybrid solar-wind systems, aiming at extracting the maximum power (tracked by a boost converter) from both sources. A single modified P&O control algorithm that reduces the complexity of the overall system was applied and compared with conventional P&O algorithm. In [14], the modeling and simulation results for a hybrid wind solar energy system using MPPT were presented. The proposed system presented power control strategies of a grid-connected hybrid generation system with versatile power transfer. Two MPPT control methods (TSR and optimal torque, OT) are used in [15] for a 1.5 MW wind turbine under different wind conditions: 6, 8, and 10 m/s. Even if the TSR method has some advantages over the commercial OT method, both have limitations. For example, the TSR controller gives better results than the OT controller in terms of optimal TSR tracking, power production performance, and faster response but has significant variations of rotor speed and power output that induce large loads for the wind turbine components. Thus, the algorithm could be useful for large wind turbine designers in deciding whether to maximize power output or optimize component loads. In [16], the P&O method is applied to a 3 kW wind turbine considering various electrical loads and wind velocities. An increase in power output was found for different operating conditions, with the MPPT algorithm providing the best results for a load of 200 \(\Omega\) and 6.5 m/s wind velocity and proving its efficiency in enhancing the performance of wind turbine systems. In [17], a HCS type MPPT algorithm consisting of PMSG, uncontrolled rectifier, and DC boost converter was applied for a hydrokinetic turbine. A PI controller was used for capturing the maximum power output of the system. Thus, the modified algorithm improved the fixed step HCS algorithm by reducing the oscillation at the steady-state condition. The variation of water velocity from 0.5 m/s to 2 m/s was considered and the results provided by the two algorithms (simple HCS and modified HCS along with PI) were compared. It was found that the second approach provided better results, with the hydrokinetic system harnessing more power. In [18], an analysis of different expert control systems applied in MPPT of wind turbines was performed. The conclusion of the study was that the contribution of an expert system based on neural network, fuzzy logic control, or intelligent search algorithms improved the non-linearity of the variables of a system. Another approach is reported in [19], consisting of a novel maximum power tracking strategy for wind turbine systems based on a hybrid wind velocity forecasting algorithm. In the controlling strategy, to optimize the output power, the authors proposed a state feedback control technique to achieve the rotor flux and rotor speed tracking purpose based on the MPPT algorithm verified by simulation.