Future’s penetration of more distributed generation will have an effect on the power system’s stability and controllability. In general, wind power as a distributed generator does not have inertial response and does not supply control power. A third characteristic of wind power is that it is not conventionally controlled and its main resource is fluctuating. This paper describes a methodology t...

Abstract: Two existing approaches to functional principal components analysis (FPCA) are due to Rice and Silverman (1991) and Silverman (1996), both based on maximizing variance but introducing penalization in different ways. In this article we propose an alternative approach to FPCA using penalized rank one approximation to the data matrix. Our contributions are four-fold: (1) by considering i...

With the development of wind generation, the calculation of available transfer capability (denoted as ATC) considering wind generation has very high application value. Based on the maximum function, this paper presents an ATC model. The characteristic of the new model is twofold. First, it considers wind turbines connected to power system and static security of power system simultaneously. Seco...

This paper investigates the multi-dimensional non-linear exponential smoothing prediction method under different weight coefficients, so as to realize short-term of original wind power output. Based on current research fluctuation prediction, this firstly proposes a new nonlinear method. corresponding forecast volatility is obtained. Then, wavelet packet decomposition used further secondary flu...

We introduce StoDynProg, a small library created to solve Optimal Control problems arising in the management of Renewable Power Sources, in particular when coupled with an Energy Storage System. The library implements generic Stochastic Dynamic Programming (SDP) numerical methods which can solve a large class of Dynamic Optimization problems. We demonstrate the library capabilities with a proto...

The maximum entropy ansatz, as it is often invoked in the context of time-series analysis, suggests the selection of a power spectrum which is consistent with autocorrelation data and corresponds to a random process least predictable from past observations. We introduce and compare a class of spectra with the property that the underlying random process is least predictable at any given point fr...

We discuss the statistical effects of predicting the power output of spatially distributed wind farms. Our forecasting procedure provides the expected power output for a time horizon up to 48 hours. It is based on the large scale wind field prediction which is generated operationally by the German weather service. In this paper we focus on the reduction of the forecast error for the aggregated ...

We present a new method for multi-component power spectra estimation in multifrequency observations of the CMB. Our method is based on matching the cross and auto power spectra of observation maps to their expected values. All the component power spectra are estimated, as well as their mixing matrix. Noise power spectra are also estimated. The method has been applied to full-sky Planck simulati...