Jesús Juan

Reliability analysis for systems with large hydro resources in a deregulated electric power market

This work describes a procedure that determines the optimal allocation for the yearly energy resulting from random water inflows to the different subperiods of a year so that the expected benefits are maximized. Its main idea is to distribute the energy stored in reservoirs in each period into two parts: one is directly sold in the energy market, while the other is made available to cover any unplanned outages of thermal units. The method proposed fulfills two objectives, to distribute the hydro energy optimally according to economic criteria and to assess the impact of new market rules on the reliability of an electric system. The procedure will be illustrated by an example based on the Spanish generating system.

Using Angles to Identify Concentrated Multivariate Outliers

This article describes a procedure for the detection of multivariate outliers based on the analysis of certain angular properties of the observations. The method is simple, exploratory in nature, and particularly well suited for the detection of concentrated contamination patterns, in which the outliers appear to form a cluster, separated from the sample. It is shown that it presents good properties for the identification of contaminations on high-dimensional sample spaces and for high contamination levels, including some cases in which methods based on robust estimators (the minimum covariance determinant and minimum volume ellipsoid estimators, the Stahel–Donoho estimator, or other recent proposals) may fail. The use of the procedure is illustrated through several examples.

A simple method to identify significant effects in unreplicated two-level factorial designs

This article proposes a generalization and improvement on the method of Lenth (1989). The problem is solved by fixing outliers in highly contaminated samples. To do this a scale robust estimator is obtained and its performance is analyzed using computer simulations. The method is extremely simple to use and leads to the same results as the more complex one proposed by Box and Meyer (1986).

A Subsampling Method for the Computation of Multivariate Estimators With High Breakdown Point

All known robust location and scale estimators with high breakdown point for multivariate samples are very expensive to compute. In practice, this computation has to be carried out using an approximate subsampling procedure. In this work we describe an alternative subsampling scheme, applicable to both the Stahel-Donoho estimator and the estimator based on the Minimum Volume Ellipsoid, with the property that the number of subsamples required is substantially reduced with respect to the standard subsampling procedures used in both cases. We also discuss some bias and variability properties of the estimator obtained from the proposed subsampling process.

Long-lived activity of elements: Effect of new activation cross- sections and their uncertainties on the selection of materials for IFE reactors

Activation calculations considering the neutron environment of the first structural wall (FSW) of the inertial fusion energy (IFE) reactor HYLIFE-II are performed for each of the natural elements from H to Bi. Results are used to rank the elements under waste management considerations. The concentration limits (CLs) corresponding to hands-on recycling, remote recycling and shallow land burial (SLB) are computed by using the recently upgraded IAEA activation data library FENDL/A-2.0. Concentration limits are also computed using earlier activation libraries, such as EAF-3.1 and EAF-4.1, to assess the impact of using FENDL on activation studies for fusion. In addition, the accuracy of activation predictions based on FENDL is assessed by computing the uncertainties on the production of the nuclides dominating the long-lived activity of several important elements.

Determining material damping type by comparing modal frequency estimators

The accuracy of modal frequency and damping estimators for non-lightly damped single degree of freedom systems depend on the response parameter used as well as the damping mechanism. Therefore, in order to make accurate modal parameter measurements, the damping mechanism at play must be known to be either viscous or hysteretic a priori. Here, comparisons between the evaluated frequency values are used to glean this information. The damping mechanism of an experimental system (consisting of resilient layer and mass plate) is then determined using two simple modal parameter estimators and applying statistical methods.

Leveling reliability in systems with large hydro resources

Reliability analysis of a generating system is established in terms of the reliability characteristics of the different units in the system and in terms of the demand of energy to be satisfied. When the analysis is performed for the long-term (one year or more duration periods), the maintenance needs of thermal units as well as the time distribution of resources for units with energy restrictions, must also be taken into account. This paper describes a method for determining the optimal strategy for allocating the yearly energy resulting from random water inflows to the different subperiods of a year so that the reliability for all the subperiods is leveled. A characteristic feature of the method is that the uncertainty inherent in forecasting future available hydroenergy is transferred to the reliability index. The procedure is illustrated by an example prepared using the Spanish generating system.

Multivariate Exponential Smoothing and Dynamic Factor Model Applied to Hourly Electricity Price Analysis

Thanks to its very simple recursive computing scheme, exponential smoothing has become a popular technique to forecast time series. In this work, we show the advantages of its multivariate version and present some properties of the model, which allows us to perform a dynamic factor analysis. This analysis leads to a simple methodology to reduce the number of parameters (useful when the dimension of observations is large) via a linear transformation that decomposes the multivariate process into independent univariate exponential smoothing processes, characterized by a single smoothing parameter that goes from zero (white-noise process) to one (random walk process). A computer implementation of the expectation-maximization (EM) algorithm has been built for the maximum likelihood estimation of the models. The practicality of the method is demonstrated by its application to hourly electricity price predictions in some day-ahead markets, such as Omel, Powernext, and Nord Pool markets, whose forecasts are given as examples. This article has supplementary material online.

Long-term generation scheduling in systems with large hydro resources in a deregulated electric power market

This work describes a procedure that determines the optimal allocation for the yearly energy resulting from random water inflows to the different subperiods of a year so that the expected benefits are maximized. Its main idea is to distribute the energy stored in reservoirs in each period into two parts: one is directly sold in the energy market, while the other is made available to cover any unplanned outages of thermal units. The method proposed fulfills two objectives, to distribute the hydro energy optimally according to economic criteria and at the same time to maximize the reliability of the system. The procedure is illustrated by an example based on the Spanish generating system.

Analysis of French electric market using heteroscedastic models of time series

A dynamic long memory regression model with autoregressive errors is considered for the analysis of hourly electricity spot prices. The method provides reliable and accurate forecasts of hourly prices in the electricity market of France, Powernext day-ahead. The presence of significant autocorrelation in squared residual recommends to fit a conditional heteroscedastic time series model. These models together have appealing economic and statistical implications.