Intelligent maximum power extraction control for wind energy conversion systems based on online Q-learning with function approximation

Abstract

Abstract-This paper proposes an intelligent maximum power point tracking (MPPT) algorithm for variable-speed wind energy conversion systems (WECSs) based on an online Q-learning algorithm. Instead of using the conventional Qlearning that uses a lookup table to store the action values for the discretized states, artificial neural networks (ANNs) are used as function approximators to output the action values by using the electrical power and rotor speed of the generator as inputs. This eliminates the need for a large storage memory. The proposed method learns the optimal speed control strategy of the WECS by updating the connecting weights of the ANNs, which has a lower computational cost than the conventional Qlearning method. Moreover, the knowledge of wind turbine characteristics or wind speed measurement is not required in the proposed method. The proposed method is validated by simulations for a WECS equipped with a doubly-fed induction generator (DFIG) and experimental results for an emulated WECS equipped with a permanent-magnet synchronous generator (PMSG).

A neural adaptative step size method for maximum power point tracking in low power wind turbine systems

“…Chun Wei [7,8] presents then reinforcement learning (RL) which use tables [7], or a set of 3 multilayer percept neural network (ANN) as the evaluation possible action [8]. The use of a lo consumes a lot of memory or gives precision over the space states.…”

A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems

“…The overall system performance of this type of method is good even under varying climatic conditions. Although it is possible only when proper rules are designed by the user with adequate knowledge of the system for selection of the appropriate rule base, membership functions, and high requirement of memory is also a major issue [32,[130][131][132][133]. Different FLC based MPPT algorithms are presented in [107,108,[117][118][119]134].…”