A General Probabilistic Forecasting Framework for Offshore Wind Power Fluctuations

Accurate wind power forecasts highly contribute to the integration of wind power into power systems. The focus of the present study is on large-scale offshore wind farms and the complexity of generating accurate probabilistic forecasts of wind power fluctuations at time-scales of a few minutes. Such complexity is addressed from three perspectives: (i) the modeling of a nonlinear and non-stationary stochastic process; (ii) the practical implementation of the model we proposed; (iii) the gap between working on synthetic data and real world observations. At time-scales of a few minutes, offshore fluctuations are characterized by highly volatile dynamics which are difficult to capture and predict. Due to the lack of adequate on-site meteorological observations to relate these dynamics to meteorological phenomena, we propose a general model formulation based on a statistical approach and historical wind power measurements only. We introduce an advanced Markov Chain Monte Carlo (MCMC) estimation method to account for the different features observed in an empirical time series of wind power: autocorrelation, heteroscedasticity and regime-switching. The model we propose is an extension of Markov-Switching Autoregressive (MSAR) models with Generalized AutoRegressive Conditional Heteroscedastic (GARCH) errors in each regime to cope with the heteroscedasticity. Then, we analyze the predictive power of our model on a one-step ahead exercise of time series sampled over 10 min intervals. Its performances are compared to state-of-the-art models and highlight the interest of including a GARCH specification for density forecasts

Ground state of the Kagome-like S=1/2 antiferromagnet, Volborthite Cu3V2O7(OH)2.2H2O

Volborthite compound is one of the very few realizations of S=1/2 quantum spins on a highly frustrated kagome-like lattice. Low-T SQUID measurements reveal a broad magnetic transition below 2K which is further confirmed by a peak in the 51V nuclear spin relaxation rate (1/T1) at 1.4K$\pm$0.2K. Through 51V NMR, the ground state (GS) appears to be a mixture of different spin configurations, among which 20% correspond to a well defined short range order, possibly of the $\sqrt{3} \times \sqrt{3}$ type. While the freezing involve all the Cu$^{2+}$ spins, only 40% of the copper moment is actually frozen which suggests that quantum fluctuations strongly renormalize the GS.Comment: 4 pages, 4 figures, to appear in PR

17O NMR study of the intrinsic magnetic susceptibility and spin dynamics of the quantum kagome antiferromagnet ZnCu3(OH)6Cl2

We report through 17O NMR, an unambiguous local determination of the intrinsic kagome lattice spin susceptibility as well as that created around non-magnetic defects issued from natural Zn/ Cu exchange in the S=1/2 (Cu2+) herbertsmithite ZnCu3(OH)6Cl2 compound. The issue of a singlet-triplet gap is addressed. The magnetic response around a defect is found to markedly differ from that observed in non-frustrated antiferromagnetic materials. Finally, we discuss our relaxation measurements in the light of Cu and Cl NMR data [cond-mat 070314] and suggest a flat q-dependence of the excitations.Comment: Accepted for publication in Phys. Rev. Lett., 3 jan. 2008 Figure 1 has been modified to include a two-components fit of the 17O NMR spectru