Predictive Maintenance of DC Capacitors in STATCOMs

Detta är en Uppsats för yrkesexamina på avancerad nivå från

Författare: Rasmus Söderström; [2020]

Nyckelord: Predictive Maintenance; STATCOM;

Sammanfattning: To further improve the reliability of STATCOM solutions a predictive maintenance system can give the user valuable readings of capacitor health an online and non-invasive, and especially readings of individual capacitors. This allows the user to replace individual deteriorating capacitor links in an MMC configuration before triggering any safety system. There are a few ways to get readings of capacitor health, equivalent series resistance (ESR) and total capacitance are two parameters that can give the user a good health indication. However, due to the large operating voltage of the STATCOM the ESR are too small to give any reliable reading. The total capacitance is the most reliable health indicator that can be used. This predictive maintenance system utilizes the voltage drop caused by capacitor discharge and the current that goes through. If one looks at the integral of that current along with voltage difference it is possible to make an estimate of the total capacitance. However, in order to add further accuracy to the monitoring system an adaptive filtering method will be applied, the Recursive Least Squares filter or RLS. With this estimation technique it is possible to limit the estimation error to approximately 1% even with a small SNR (signal to noise ratio). To give additional functionality of the system it can also be ran in parallel to the control system for the STATCOM on the FPGA control board, and thus not affecting the performance of the control systems. However, it is not uncommon for the voltage and current to be acquired on different boards and in different places. Thus, due to communication delays it is possible measurement might get skewed or phase shifted towards each other. Therefore, a system which detects this skewing are also of interest, as it could improve the accuracy of the capacitance estimations further.

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