Calculation of parameter ranges for robust gain tuning of power system controllers

This work proposes a computational tool to assist power system engineers in the field tuning of power system stabilizers (PSSs) and Automatic Voltage Regulators (AVRs). The outcome of this tool is a range of gain values for theses controllers within which there is a theoretical guarantee of stability for the closed-loop system. This range is given as a set of limit values for the static gains of the controllers of interest, in such a way that the engineer responsible for the field tuning of PSSs and/or AVRs can be confident with respect to system stability when adjusting the corresponding static gains within this range. This feature of the proposed tool is highly desirable from a practical viewpoint, since the PSS and AVR commissioning stage always involve some readjustment of the controller gains to account for the differences between the nominal model and the actual behavior of the system. By capturing these differences as uncertainties in the model, this computational tool is able to guarantee stability for the whole uncertain model using an approach based on linear matrix inequalities. It is also important to remark that the tool proposed in this paper can also be applied to other types of parameters of either PSSs or Power Oscillation Dampers, as well as other types of controllers (such as speed governors, for example). To show its effectiveness, applications of the proposed tool to two benchmarks for small signal stability studies are presented at the end of this paper.

Mycobiota, aflatoxins and cyclopiazonic acid in stored peanut cultivars

This study evaluated the presence of fungi and mycotoxins [aflatoxins (AFs), cyclopiazonic acid (CPA), and aspergillic acid] in stored samples of peanut cultivar Runner IAC Caiapó and cultivar Runner IAC 886 during 6 months. A total of 70 pod and 70 kernel samples were directly seeded onto Aspergillus flavus and Aspergillus parasiticus agar for fungi isolation and aspergillic acid detection, and AFs and CPA were analyzed by high-performance liquid chromatography. The results showed the predominance of Aspergillus section Flavi strains, Aspergillus section Nigri strains, Fusarium spp., Penicillium spp. and Rhizopus spp. from both peanut cultivars. AFs were detected in 11.4% of kernel samples of the two cultivars and in 5.7% and 8.6% of pod samples of the Caiapó and 886 cultivars, respectively. CPA was detected in 60.0% and 74.3% of kernel samples of the Caiapó and 886 cultivars, respectively. Co-occurrence of both mycotoxins was observed in 11.4% of kernel samples of the two cultivars. These results indicate a potential risk of aflatoxin production if good storage practices are not applied. In addition, the large number of samples contaminated with CPA and the simultaneous detection of AFs and CPA highlight the need to investigate factors related to the control and co-occurrence of these toxins in peanuts.