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This paper proposes a sensorless control method to improve the performance of a high-power, high-speed, and dual three-phase interior permanent magnet synchronous motor (PMSM). The motor has two sets of three-phase stator windings spatially phase shifted by 30 electrical degrees. First, a sliding-mode observer (SMO) is used to estimate the back EMF of the motor. Then the synchronous frequency tracking filter (SFTF) replaces the low-pass filter in the traditional sensorless control method, which can obtain the fundamental wave component in the back EMF. Finally, a phase-locked loop (PLL) is used to obtain the rotor position angle. An LC filter is also designed and adopted to reduce the current ripple due to the small inductance. In order not to generate additional losses, an active damper that also achieves the effect of suppressing resonance replaces the actual resistor.

Aggregated load modeling is an important daily practice in utility companies, but existing statistics- or measurement-based methods suffer from various limitations. This work proposes an effective approach to identify ZIP coefficients of the aggregated residential load model using advanced measurement infrastructure (AMI) data. A non-intrusive load monitoring (NILM) based algorithm is developed to disaggregate household power consumption into appliance-level activities. Such appliance activities are then associated with ZIP attributes and aggregated to household and feeder level. Therefore, the equivalent ZIP coefficients are obtained without the dependence of other information. The effectiveness of the proposed approach is verified using a real-world smart meter data set and the IEEE 34-bus feeder test case.