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Sieniutycz; Warsaw, Poland M. Velarde; Madrid, Spain. You will also find instructions for authors there. User Account Log in Register Help. Search Close. Advanced Search Help. Add to Cart. Online ISSN See all formats and pricing Online. Prices are subject to change without notice. Prices do not include postage and handling if applicable. Frontmatter Editorial by Hoffmann, Karl Heinz. Volume 43 Issue 4 Oct , pp. Volume 42 Issue 4 Oct , pp. Volume 41 Issue 4 Oct , pp.

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Biosphera vince il National ENERGY GLOBE Award Italy – Biosphera Equilibrium

Volume 23 Issue 3 Jan , pp. Volume 22 Issue 2 Jan , pp. Volume 21 Issue 1 Jan , pp. Volume 20 Issue 1 Jan , pp. Volume 19 Issue 4 Jan , pp. Volume 18 Issue 3 Jan , pp. A producer of non-programmable renewable sources which has produced more than declared in an area with positive aggregate unbalance will be required to pay a penalty, as it has helped to increase the unbalance in the area.

1st Edition

Similar thing happens in the case in which the actor has produced less than declared and the macro-zone has negative aggregate imbalance. Conversely, if a producer is unbalanced in the opposite direction to the macrozonal aggregate imbalance he is rewarded as he is helping to balance the market.

In the present section we analyse the theoretical mathematical foundation of the method that will be later used to concrete address our energy balance task. In particular, in order to make the present work as much as self-contained as possible, we provide an overview of standard approaches that can be used in similar frameworks, referring the interested reader to, e.

The exponential smoothing model Let us first consider the exponential smoothing ES , see, e. When one concerns the study of time series, the AutoRegressive Moving Average ARMA models play a central role because they are capable of describe weakly stationary stochastic processes with a rather restricted set of assumptions, being mainly based on the use of two polynomials: the first one takes into account the autoregressive character of the data set, while the second takes into account the moving average.

As often have been pointed out in literature, see, e. Open image in new window. The model selection procedure consists of several steps. Concerning the ES model, after having chosen a time window, we estimate it considering the associated AIC value. As regard the exogenous variables, several choices can be made.

The second exogenous parameter that has to be taken into account is temperature. The evaluation has been obtained according to the following criterion: we fix a time window and we fit all the models, then we check the volatility of the times series to decide the best threshold, using it to predict the next day imbalance.

Then, if the forecasted value is above the threshold in absolute value, we enter the market. Afterwards, we check with the actual datum if the predicted imbalance sign is correct, and we shift the time series to repeat the procedure. Acknowledgements The authors gratefully acknowledge BeFree s. Di Persio L, Perin I. An ambit stochastic approach to pricing electricity forward contracts: the case of the German energy market.

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Novel approaches to the energy load unbalance forecasting in the Italian electricity market

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