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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.
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.
J Probab Stat. MathSciNet Google Scholar. Di Persio L, Frigo M. Gibbs sampling approach to regime switching analysis of financial time series. J Comput Appl Math. Approximation and convergence of solutions to semilinear stochastic evolution equations with jumps. J Funct Anal. Electricity derivatives. Berlin: Springer; Cordoni F, Di Persio L. Backward stochastic differential equations approach to hedging, option pricing, and insurance problems. Int J Stoch Anal. Mills TC. Time series techniques for economists.
Cambridge: Cambridge University Press; Weron R. Modeling and forecasting electricity loads and prices: a statistical approach. New York: Wiley; Google Scholar. Gardner E. Exponential smoothing: the state of the art. J Forecast. CrossRef Google Scholar.
The admissible parameter space for exponential smoothing models. Ann Inst Stat Math. Feinberg E, Genethliou D. Load forecasting. In: Applied mathematics for restructured electric power systems. New York: Springer; Energy load forecasting using empirical mode decomposition and support vector regression. Liu K, et al. Comparison of very short-term load forecasting techniques. Polynomial chaos expansion approach to interest rate models.
The impact of population ageing on energy use: Evidence from Italy
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