Abstract
The energy efficiency and the development of environmentally correct policies are current topics, especially when applied to the industrial sector with the objective of increasing the competitiveness of the enterprises. Portuguese textile dyeing sector, being a major consumer sector of primary energy, needs to adopt measures to improve its competitiveness. Biomass appears to be a viable and preferred alternative energy source for the sector, while simultaneously develops an entire forest industry devoted to the supply of forest solid fuels. This work carries out a comprehensive PEST (political, economic, social and technological) analysis, which analyses Political, Economic, Social and Technological aspects of the replacement of the fossil fuels traditionally used in this sector by biomass, providing a framework of environmental factors that influence the strategic management of the companies. The main advantages are the reduction of external dependence on imported fuel due to the use of an endogenous renewable resource, the creation and preservation of jobs, the increased competitiveness of the sector by reducing energy costs, the use of national technology and the reduction of greenhouse gases emissions.

Abstract
In this paper, an innovative bi-level model is developed for the interactions of the plug-in electric vehicle (PEV) parking lot (PL) with the upstream markets through an aggregator in the system. The preferences of the PEVs on using the PL are also considered in the study. The PEVs have a choice in participating in grid-to-vehicle or vehicle-to-grid modes with fixed or flexible amount of departed state of charge (SOC). The PL assigns various tariffs for different requirements of the PEVs. In this study, the mutual effect of the variation of PEV tariffs and the PL's behavior in the market is investigated. It is shown that the preferences of PEVs can significantly affect the PL's strategy. The changes of the equilibrium prices for PL and aggregator interaction are thoroughly analyzed in response to changes in PEV tariffs to illustrate their influence on their behavior.

Abstract
The inevitable need of new infrastructures for encouraging plug-in electric vehicles (PEVs) penetration into the system has drawn various attentions towards the required studies. In this regard, the PEVs parking lot (PL) has shown to have proper potentials. Other than providing a charging place for the PEVs, PLs can be considered as an integrated form of PEV batteries and act as storage in the system. However, the accuracy of PL's operation can be enhanced through detailed modeling of various affecting factors such as PEV's preferences on using the charging capability of the PL. In this study, a new model to add the PEVs' preferences in the PL's market participation problem is proposed. Various categories of PEVs are considering based on their arrival/departure pattern, duration of stay in the PL, and charging requirements. The results showed a considerable difference in PL's strategy in market participation, with and without considering PEVs' preferences.

Abstract
This paper aims to optimize the behavior of Plug-in Electric Vehicle (PEV) parking lots considering the interaction with renewable energy resources. In the proposed model, the PEV parking lot can participate in the day-ahead energy, spinning reserve and regulation markets. On this basis, behavior of the PEV parking lot in a distribution system is modeled consisting of wind and photovoltaic power producers. Moreover, the model consists of uncertainty characteristics of PEV behavior, wind and photovoltaic power generation. In order to tackle the mentioned uncertainties, a stochastic programming approach is utilized to maximize the profit of the parking lot operator. Numerical cases are studied to show the effectiveness of the proposed model. The results indicate that renewable energy resources have significant impacts on the behavior of PEV parking lot.

Abstract
In this paper a probabilistic model to solve the economic dispatch (ED) problem considering the uncertainty introduced by power sources, such as wind and solar, is presented. Assuming the forecasting error to be modeled by a beta probability distribution function (PDF), the proposed methodology presented in this paper allows the incorporation of this PDF in the optimization model, obtaining the PDF of power production of thermal and renewable generators, energy not supplied, excess of electricity, and generation cost. The results obtained from the proposed methodology are compared with those obtained from Monte Carlo Simulation (MCS) approach, observing a good agreement.

Abstract
This paper deals with a control technique for multilevel converter topologies base on Direct Lyapunov Control Method (DLCM) for integration of Renewable Energy Resources (RER) into the power grid. The compensation of variations in reference current components is considered properly in this control plan, which is the main contribution and novelty of this work in comparison with other control strategies. The proposed control technique provides the injection of harmonic current components of loads via the interfacing system, which is based on multilevel converter topologies and compensation of loads reactive power. Then, the active power in fundamental frequency will be supplied through the main grid and a unity Power Factor (PF) between the grid current and load voltage is obtained during the connection of nonlinear load to the grid. High performance of DLCM is validated through simulation results during dynamic and steady-state operating conditions.