Analysis of Transmission System Adequacy Considering the Constrained Fuzzy Power Flow

Power flow calculations are one of the most important tools for power system planning and operation. The need to account for uncertainties when performing power flow studies led, among others methods, to the development of the fuzzy power flow (FPF). This kind of models is especially interesting when a scarcity of information exists, which is a common situation in liberalized power systems (where generation and commercialization of electricity are market activities). In this framework, the symmetric/constrained fuzzy power flow (SFPF/CFPF) was proposed in order to avoid some of the problems of the original FPF model. The SFPF/CFPF models are suitable to quantify the adequacy of transmission network to satisfy “reasonable demands for the transmission of electricity” as defined, for instance, in the European Directive 2009/72/EC. In this work it is illustrated how the SFPF/CFPF may be used to evaluate the impact on the adequacy of a transmission system originated by specific investments on new network elements

Probabilistic Security Constrained Fuzzy Power Flow Models

In restructured power systems, generation and commercialization activities became market activities, while transmission and distribution activities continue as regulated monopolies. As a result, the adequacy of transmission network should be evaluated independent of generation system. After introducing the constrained fuzzy power flow (CFPF) as a suitable tool to quantify the adequacy of transmission network to satisfy 'reasonable demands for the transmission of electricity' (as stated, for instance, at European Directive 2009/72/EC), the aim is now showing how this approach can be used in conjunction with probabilistic criteria in security analysis. In classical security analysis models of power systems are considered the composite system (generation plus transmission). The state of system components is usually modeled with probabilities and loads (and generation) are modeled by crisp numbers, probability distributions or fuzzy numbers. In the case of CFPF the component’s failure of the transmission network have been investigated. In this framework, probabilistic methods are used for failures modeling of the transmission system components and possibility models are used to deal with 'reasonable demands'. The enhanced version of the CFPF model is applied to an illustrative case.

Chemical Composition and Bioactive Compounds in Bananas and Postharvest Alterations

Bananas arise as one of the most popular fruits consumed all around the world. Banana belongs to the genus Musa from the family Musaceae. It is original from tropical regions and presents a strong ability to protect itself from the oxidative stress caused by extreme climatic conditions such as intense sunshine and high temperature. For this protection, bananas increase the production of bioactive compounds with antioxidant activity, which protect the fruit from the oxidative damage. Scientific studies have demonstrated that bananas (both in the pulp and peel) contain different antioxidant compounds, like vitamins (A, B, C and E), β-carotene and phenolic compounds (catechin, epicatechin, lignin, tannins, anthocyanins). Furthermore, banana is also notably rich in minerals, like potassium and phosphorus. The knowledge about the chemical composition and the contents in compounds with biological activity is of high interest given the importance of bananas as a valuable food all over the world. However, because bananas are perishable due to some factors like chemical reactions, including those that result in the production of ethylene, their postharvest conservation in pivotal for the commercialization. The effects of postharvest treatments and storage conditions on the composition of bananas are, therefore, essential. In this way, the present chapter focus on the composition of bananas, including macronutrients, micronutrients and bioactive compounds, as well as the effect of postharvest treatments and storage conditions in the quality of bananas.