Systems and methods for real-time DC microgrid power analytics for mission-critical power systems
摘要
說明書
The inherent risks (to safety and the operational life of components comprising the electrical system) that harmonic distortions pose to electrical systems have led to the inclusion of harmonic distortion analysis as part of traditional power analysis. Metering and sensor packages are currently available to monitor harmonic distortions within an electrical system. However, it is not feasible to fully sensor out an electrical system at all possible locations due to cost and the physical accessibility limitations in certain parts of the system. Therefore, there is a need for techniques that predict, through real-time simulation, the sources of harmonic distortions within an electrical system, the impacts that harmonic distortions have or may have, and what steps (i.e., harmonics filtering) may be taken to minimize or eliminate harmonics from the system.
Currently, there are no reliable techniques for predicting, in real-time, the potential for periodic non-sinusoidal waveforms (i.e. harmonic distortions) to occur at any location within an electrical system powered with sinusoidal voltage. In addition, existing techniques do not take into consideration the operating conditions and topology of the electrical system or utilizes a virtual system model of the system that “ages” with the actual facility or its current condition. Moreover, no existing technique combines real-time power quality meter readings and predicted power quality readings for use with a pattern recognition system such as an associative memory machine learning system to predict harmonic distortions in a system due to changes in topology or poor operational conditions within an electrical system.
