Abstract

Abstract

Abstract
In this study a novel two-stage stochastic programming based day-ahead joint energy and reserve scheduling model is developed. Demand-side as a reserve resource is explicitly modeled through responsive load aggregations, as well as large industrial consumers that directly participate in the scheduling procedure. Furthermore, a risk-hedging measure is introduced, namely the Conditional Value-at-Risk (CVaR), to analyze the behavior of energy and reserve scheduling by both the generation and the demand-side for a risk-averse ISO. The proposed methodology is tested on the practical non-interconnected insular power system of Crete, Greece, which is characterized by a significant penetration of Renewable Energy Sources (RES).

Abstract
The agricultural commodities are important to economies of several countries, especially in Brazil. Despite the amount of money involved, as knows that in agribusiness activities do not have accurate information in all the process. Therefore some research centers in Brazil, such as Center for Advanced Studies on Applied Economics - CEPEA, collect and provide daily price indices of these commodities, on several agricultural products, and spread information to these researchers markets, producers and formulators public policy. The idea is to understand the evolution and pattern for the time series of Grains price indices for seven years. The aim of this paper is find common patterns on time series, i.e. highlight events that happens frequently over seven year of daily grain prices quotation in several products. The results give an understanding of the dynamic of these grains time series, such as, some important aspects were detect was these products competes in fields for crops.

Abstract
In this paper we propose the gravitational search algorithm to design PID control structures. The controller design is performed considering the objectives of set-point tracking and disturbance rejection, minimizing the integral of the absolute error criterion. A two-degrees-of-freedom control configuration with a feedforward pre-filter inserted outside the PID feedback loop is used to improve system performance for both design criteria. The pre-filter used is a Posicast controller designed simultaneously with a PID controller. Simulation results are presented which show the proposed technique merit.

Abstract
The current literature in wind power forecast is focused in generating accurate uncertainty forecasts and communicating this information to the end-user. Multi-temporal decision-making problems require information about the temporal trajectory of wind power for the next hours. Presently, this information is provided through a set of temporal trajectories (or scenarios). This paper aims at contributing with an alternative approach for communicating this information through simultaneous prediction intervals. These intervals include the temporal dependency of forecast errors since they provide information about the probability of having the observed wind power trajectory fully inside the quantiles forming the interval. First, a learning sample of temporal trajectories are generated with the Gaussian copula method and using the marginal prediction intervals. Then, two methods proposed in the literature are used to construct the simultaneous intervals. The quality of these intervals is evaluated for three real wind farms.