Quantum mechanics

Control (management)

Voltage

Rotor (electric)

Engineering

Power optimizer

Power (physics)

Computer science

Grid

Maximum power point tracking

Permanent magnet synchronous generator

Mechanical engineering

Rectifier (neural networks)

Stochastic neural network

Induction generator

Physics

Mathematics

Shunt generator

Inverter

Artificial intelligence

Geometry

Turbine

Wind power

Generator (circuit theory)

Topology (electrical circuits)

Control theory (sociology)

Artificial neural network

Recurrent neural network

Magnet

Machine learning

Electrical engineering

IEEE Journal of Emerging and Selected Topics in Power Electronics

This article presents the design and optimization of a multiphase doubly excited generator (DEG) for wind turbine applications in a dc grid. The DEG has two rotors: 1) a wound field excited (WFe) rotor, which in principals is similar to a conventional synchronous generator (SG) and 2) a surface-mounted permanent magnet excited (PMe) rotor that has a similar operation as a PM generator. The DEG is connected to a multileg passive rectifier whose output is connected to a dc wind grid. The dual rotor topology allows modification of the output power and voltage of the DEG while eliminating the need for an active power electronic converter. The DEG is parametrized and undergone a multiobjective optimization solved by employing a differential evolution algorithm (DEA). The DEG output power, mass, and efficiency are optimized subject to a list of prescribed constraints. To verify the design procedures a small-scale DEG is built and tested in the laboratory, whose results are presented in this article.

A Wind Turbine Generator Design and Optimization for DC Collector Grids