Abstract
Demand response (DR) provides enormous opportunities to distribution system operators so as to conduct the power system in a sustainable manner. Due to the increasing penetration of electric vehicles (EV) in the power system, the necessity of enhancing flexibility has gained importance in the charging operation process. With the aid of the smart grid concept and DR programs, more flexible grid operations are provided. In this study, an optimal day-ahead EV charging strategy through electric vehicle parking lots (EVPL) aggregators is intended for the purpose of maximizing the load factor during daily operation. Furthermore, the behavioral uncertainty of EVs and peak load limitation based DR programs are also taken into account in the devised model. In order to reveal the effectiveness of the proposed EVPL aggregator energy management strategy, various case studies are performed, and credible results are reported.

Abstract
Understanding the role of the climate on the wine production is one of the major concerns of this sector since the environment usually determines the output of this industry. There are only a few previous studies that attempted to compile these environmental effects as an index, usually considering the temperature and the precipitation as their core variables. The present study suggests a new climate index which is based on descriptive statistics. Our index tries to mimic the target region characteristics and avoid the past studies premise of imposing previously conceived restrictions such as a fixed optimal climate. We then used yearly production and daily temperature data (1950-2016) from the Portuguese Minho wine region to test our proposed index and compare it with Ribéreau-Gayon and Peynaud (RGP, Ribéreau-Gayon et al., 2003) and Growing Degree-Days (GDD, Winkler et al., 1974) indexes. Our results showed that the newly proposed index may outperform the explanatory power of the other indexes and, in addition, may output interesting and unknown characteristics such as the different ideal temperatures regarding the studied region. © The Authors, published by EDP Sciences, 2018.

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The uncertainty and variability as a consequence of modern utilization of wind power in the electrical system besides unpredicted contingencies of the system components can impose crucial challenges on the Independent System Operator's (ISO) performance. In such a situation, increasing operational flexibility is the main way to cover wind power unpredictability and to enable secure operation of the power system. To this end, this paper proposes a flexible security-constrained program to schedule supply-side and demand-side via an optimal pricing and incentive scheme. The considered demand response (DR) programs include time of use (TOU), real-time pricing (RTP), critical peak pricing (CPP), as well as emergency demand response program (EDRP). The study aims to find the most effective DR scheme among a set of DR programs to improve the efficiency of electricity markets while guaranteeing the security and environmental restrictions through minimization of two objective functions, the ISO's operational cost and pollutant emissions from generation units.

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