Stochastic Optimal Regulation Service Strategy for a Wind Farm Participating in the Electricity Market

As modern wind farmshave the ability to provideregulation service for the power system, wind power plant operators may be motivated to participate in the regulating market to maximize their profit.In this paper, anoptimal regulation servicestrategy for a wind farm to participate in the regulatingmarket is proposed. The relationship between up regulation price and wind power level,and the relationship between the probability of up regulation and the wind power level are studied. Thestochastic optimizationis adopted to find the optimal ratiofor regulation service. The Monte Carlo method is used in the stochastic optimization to deal with the uncertainty of the up regulation price and the up regulation activation of the power system.The Danish short-term electricity market and a wind farm in western Denmark are chosen to evaluate the effect of the proposed strategy. Simulation results showthe proposed strategy can increase the revenue of wind farms by leavinga certain amount of wind powerfor regulation service

Loss Minimizing Operation of Doubly Fed Induction Generator Based Wind Generation Systems Considering Reactive Power Provision

The paper deals with control techniques for minimizing the operating loss of doubly fed induction generator based wind generation systems when providing reactive power. The proposed method achieves its goal through controlling therotor side q-axis current in the synchronous reference frame. The formula for the control reference is explicitly deduced in this paper considering the losses of the generator, the power electronic devices and the filter. Three control strategies are compared with the proposed method under different wind speeds and differentreactive power references. The simulation results validate the effectiveness of the proposed method

SuperChat: Dialogue Generation by Transfer Learning from Vision to Language using Two-dimensional Word Embedding and Pretrained ImageNet CNN Models

The recent work of Super Characters method using two-dimensional word embedding achieved state-of-the-art results in text classification tasks, showcasing the promise of this new approach. This paper borrows the idea of Super Characters method and two-dimensional embedding, and proposes a method of generating conversational response for open domain dialogues. The experimental results on a public dataset shows that the proposed SuperChat method generates high quality responses. An interactive demo is ready to show at the workshop.Comment: 5 pages, 2 figures, 1 table. Accepted by CVPR2019 Language and Vision Worksho