In existing wind farms, the overall power output can be increased through yaw control. However, the cooperative control of start/stop, yaw and turbines positions is often overlooked, leading to wake superposition to downstream wind turbines and suboptimal power output. This paper proposes a synchronized optimized method that considers start/stop, yaw and turbines positions control based on a three-dimensional wake model and yaw flow superposition model. The objective function of the proposed strategy is to maximize the power output of the Chapman Ranch (CR) wind farm. Four cases are considered: start-stop, yaw control, start-stop & yaw control and start-stop & yaw & turbines positions control. The particle swarm algorithm is introduced to optimize the wind farm layout. According to the results, considering start-stop, yaw and turbines positions optimization can not only increase the annual power output of the wind farm by 8.85 %, but also avoid the colliding wake in the CR wind farm. However, the other three cases will cause colliding wake in some fields of the CR wind farm. This study provides important guidance on improving the overall power output of existing wind farms.

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We present a general solution for steering microrobotic
swarm by dynamic actuating fields. In our approach, the
motion of micro-robots is controlled by changing the actuating
direction of a field applied to them. The time-series sequence
of actuating field’s directions can be computed automatically.
Given a target position in the domain of swarm, a governing
field is first constructed to provide optimal moving directions at
every points. Following these directions, a robot can be driven
to the target efficiently. However, when working with a crowd of
micro-robots, the optimal moving directions on different agents
can contradict with each other. To overcome this difficulty, we
develop a novel steering algorithm to compute a statistically
optimal actuating direction at each time frame. Following a
sequence of these actuating directions, a crowd of micro-robots
can be transported to the target region effectively. Our steering
strategy of swarm has been verified on a platform that generates
magnetic fields with unique actuating directions. Experimental
tests taken on aggregated magnetic micro-particles are quite
encouraging.@en