A priori interconnect prediction and technology extrapolation are closely intertwined. Interconnect predictions are at the core of technology extrapolation models of achievable system power, area density and speed. Technology extrapolation, in turn, informs a priori interconnect prediction via models of interconnect technology and interconnect optimizations. In this paper, we address the linkag...

The fluctuation of active power output of wind farm has many negative impacts on large-scale wind power integration into power grid. In this paper, flywheel energy storage system (FESS) was connected to AC side of the doubly-fed induction generator (DFIG) wind farm to realize smooth control of wind power output. Based on improved wind power prediction algorithm and wind speed-power curve modeli...

It has been demonstrated with recent software implementations of context modeling the capability of PPM (Prediction by Partial Matching) [1] type of algorithms to achieve very high compression rates. However, the cost is high in terms of computational complexity and low speed. Hardware implementations of compression algorithms are capable of increasing compression speed by at least an order of ...

Power Compiler: A Gate-Level Power Optimization and Synthesis System p. 74 Elastic History Buffer: A Low-Cost Method to Improve Branch Prediction Accuracy p. 82 Design Optimization for High-Speed Per-address Two-level Branch Predictors p. 88 PA-8000: A Case Study of Static and Dynamic Branch Prediction p. 97 Discrete Drive Selection for Continuous Sizing p. 110 Continuous Retiming: Algorithms a...

Elman Neural Network has been an efficient system identification tool in many areas. However, one of the problems often associated with this type of network is that the speed of learning is too slow. The HF Elman neural network is presented for the modeling of unknown delay and high-order nonlinear system. Then chaos searching is imported to train it, make BP algorithm can skip the local minimu...

In this brief, constrained multi variable model predictive control (MPC) strategy is investigated for a GE9001E gas turbine power plant. So the rotor speed and exhaust gas temperature are controlled manipulating the fuel command and compressor inlet guide vanes position. A nonlinear model is introduced using conventional mathematical models and ARX identification procedure as gas turbine plant ...

Model-based performance predictions and reconfigurations enable optimizing resource efficiency while ensuring that Quality-of-Service demands are met in today’s complex ITsystems. The Descartes Modeling Language (DML) and the Palladio Component Model (PCM) are two architectural performance modeling formalisms applied in this context. This paper compares DML to PCM concerning similarities, diffe...

It is important to improve the accuracy of wind speed forecasting for wind parks management and wind power utilization. In this paper, a novel hybrid approach known as WTT-TNN is proposed for wind speed forecasting. In the first step of the approach, a wavelet transform technique (WTT) is used to decompose wind speed into an approximate scale and several detailed scales. In the second step, a t...