Sensoriamento óptico quase-distribuído aplicado ao monitoramento de trocadores de calor de usinas hidrelétricas

This work aims to develop optical sensors for temperature monitoring in hydroelectric power plant heat exchangers. The proposed sensors are based on the Fiber Bragg Gratings technology. First of all, a prototype with three sensors inscribed in a same fiber was developed. This fiber was then fixed to a conventional Pt100 sensor rod and inserted in a thermowell. The ensemble was then calibrated in a workbench, presenting a maximum combined uncertainty of 2,06 °C. The sensor was installed in one of the heat exchangers of the Salto Osório’s hydroelectric power plant. This power plant is situated in the Iguaçu river, at the Paraná state. Despite the satisfactory results, the sensor was improved to a second version. In this, fifteen optical Bragg sensors were inscribed in a same fiber. The fixation with a conventional sensor was no longer necessary, because the first version results comproved the efficiency and response time in comparison to a conventional sensor. For this reason, it was decided to position the fiber inside a stainless steel rod, due to his low thermal expansion coefficient and high corrosion immunity. The utilization of fifteen fiber Bragg gratings aims to improve the sensor spatial resolution. Therefore, measurements every ten centimeters with respect to the heat exchanger’s height are possible. This provides the generation of a thermal map of the heat exchanger’s surface, which can be used for determination of possible points of obstruction in the hydraulic circuit of the heat exchanger. The heat exchanger’s obstruction in hydroelectric power plants usually occur by bio-fouling, and has direct influence in the generator’s cooling system efficiency. The obtained results have demonstrated the feasibility in application of the optical sensors technology in hydroelectric power plants.

Diagnóstico automático de eventos e distúrbios em unidades geradoras e usinas utilizando lógica fuzzy

The electric power systems are getting more complex and covering larger areas day by day. This fact has been contribuiting to the development of monitoring techniques that aim to help the analysis, control and planning of power systems. Supervisory Control and Data Acquisition (SCADA) systems, Wide Area Measurement Systems and disturbance record systems. Unlike SCADA and WAMS, disturbance record systems are mainly used for offilne analysis in occurrences where a fault resulted in tripping of and apparatus such as a transimission line, transformer, generator and so on. The device responsible for record the disturbances is called Digital Fault Recorder (DFR) and records, basically, electrical quantities as voltage and currents and also, records digital information from protection system devices. Generally, in power plants, all the DFRs data are centralized in the utility data centre and it results in an excess of data that difficults the task of analysis by the specialist engineers. This dissertation shows a new methodology for automated analysis of disturbances in power plants. A fuzzy reasoning system is proposed to deal with the data from the DFRs. The objective of the system is to help the engineer resposnible for the analysis of the DFRs’s information by means of a pre-classification of data. For that, the fuzzy system is responsible for generating unit operational state diagnosis and fault classification.