Wind-system performance optimization using microprocessor control

When wind-energy conversion systems are used to produce electrical power by the use of synchronous alternators driven by fixed-pitch impellers, they often do not extract maximum possible energy from the wind. This is because they do not maintain an optimal rotational speed in relation to wind speed. Therefore, their efficiency is good only over a narrow range of wind speeds;In this dissertation, a technique for optimizing the efficiency of wind energy conversion systems is described that is based only on the measurement of the wind system output voltage without the requirement for direct measurement of the wind speed or rotational speed of the alternator. A description is given of the design philosophy and construction for a microprocessor-based controller that implements the optimizing technique and is adaptable to different types of wind systems. A method for taking performance data based on a modified Method of Bins is described. Test results of six different experiments involving two wind systems are included;The results obtained demonstrate that with the described microprocessor-based controller, a substantial improvement over normal performance of wind-driven alternators can be achieved

Correlated Cascades: Compete or Cooperate

In real world social networks, there are multiple cascades which are rarely independent. They usually compete or cooperate with each other. Motivated by the reinforcement theory in sociology we leverage the fact that adoption of a user to any behavior is modeled by the aggregation of behaviors of its neighbors. We use a multidimensional marked Hawkes process to model users product adoption and consequently spread of cascades in social networks. The resulting inference problem is proved to be convex and is solved in parallel by using the barrier method. The advantage of the proposed model is twofold; it models correlated cascades and also learns the latent diffusion network. Experimental results on synthetic and two real datasets gathered from Twitter, URL shortening and music streaming services, illustrate the superior performance of the proposed model over the alternatives