Abstract
For the past few years, wind energy is the most popular non-traditional resource among renewable energy resources and it’s significant to make full use of wind energy to realize a high level of generating power. Moreover, diverse maximum power point tracking (MPPT) methods have been designed for varying speed operation of wind energy conversion system (WECS) applications to obtain optimal power extraction. Hence, a novel and meta-heuristic technique, named enhanced atom search optimization (EASO), is designed for a permanent magnet synchronous generator (PMSG) based WECS, which can be employed to track the maximum power point. One of the most promising benefits of this technique is powerful global search capability that leads to fast response and high-quality optimal solution. Besides, in contrast with other conventional meta-heuristic techniques, EASO is extremely not relying on the original solution, which can avoid sinking into a low-quality local maximum power point (LMPP) by realizing an appropriate trade-off between global exploration and local exploitation. At last, simulations employing two case studies through Matlab/Simulink validate the practicability and effectiveness of the proposed techniques for optimal proportional-integral-derivative (PID) control parameters tuning of PMSG based WECS under a variety of wind conditions.
Highlights
In a wind energy conversion system (WECS), the kinetic energy of wind is transformed into mechanical energy via a wind turbine, and this energy is converted into electrical energy via employing a generator [5]
The described enhanced atom search optimization (EASO) is compared with genetic optimization (GA) [34] and particle swarm optimization (PSO) [35] in three cases, namely, step-variation of wind speed, low-frequency random wind, and highfrequency random wind
A large number of maximum power point tracking (MPPT) strategies have been developed for permanent magnet synchronous generator (PMSG) based WECS, these techniques are basically less efficient and difficult in searching the maximum power point (MPP)
Summary
To meet the increasing demand for energy in this century and reduce the pollution caused by coal and oil power plants, there is an urgent need for a sustainable and environmentally friendly source of green energy. For the sake of solving this problem, the maximum power point tracking (MPPT) algorithm is usually used to enhance the efficiency of WECS [9], which major role of this algorithm is to keep the output power of the wind turbine at the maximum power point (MPP) without being affected by the change of wind speed. Matayoshi et al [14] used TSR method, which owns great advantages when the wind speed can be accurately known This method uses a feedback control loop to maintain the fan running near the optimal TSR, which are fast response speed and high efficiency of maximum power tracking, but it owns drawbacks are that it must have the equipment to accurately measure the wind speed. Patnaik et al [19] presented a novel MPPT control of wind energy based on the traditional power feedback method considering the influence of the changing loss of the power generation system.
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