Abstract
Significant electrical loads such as HVAC systems can be made “aware” of the operation of other loads nearby in the electric grid. Local examination of the utility voltage waveform can provide this awareness without the need for a dedicated communication network. This is particularly true in low-inertia microgrids and “soft” sections of a utility network. This paper presents techniques for extracting frequency and voltage harmonic transients corresponding to individual load events. With data collected from a microgrid energized by diesel generators, we demonstrate the ability to identify the operation of HVAC units and generator dispatch events from their transient effects on the voltage using a cross-correlation based scoring algorithm. Ultimately, incorporating such awareness into load controllers allows loads to autonomously meet system-level objectives in addition to their individual requirements. For example, HVAC units could maintain occupant comfort while also reducing the utility’s peak aggregate electrical demand by consuming electricity on a schedule interleaved with the operation of other nearby HVAC units.
Highlights
Electric loads typically operate with uncoordinated schedules
ALGORITHM DEMONSTRATION To demonstrate the functionality of the nonintrusive voltage monitoring algorithm, the exemplar formation and transient identification algorithms described in the previous section were applied to the field data containing all 512 environmental control unit (ECU) events, 15 generator events, and several events corresponding to other loads on the grid, e.g. the latrine pump
This paper has demonstrated an effective application of a nonintrusive monitor that can detect significant events and identify them strictly from changes in the voltage waveform of the utility
Summary
Electric loads typically operate with uncoordinated schedules. For example, an environmental control unit (ECU) providing heating and cooling to a building (or section of a building) operates independently from other ECUs in neighboring buildings (or other sections of the building). Intriguing possibilities exist for the autonomous collection of operational information from neighboring loads through analysis of voltage measurements local to a load. This paper introduces new techniques for identifying load operation ‘‘signatures’’ strictly from measurements of utility voltage. These techniques are applicable in low-inertia microgrids or ‘‘street-level’’ distribution networks where the utility may not be ‘‘stiff,’’ due to generator limitations or impedance from a local distribution transformer. Among other uses, this information could be used for autonomous control of cyclically operating loads [1], [10]. A cross-correlation based transient identification technique presented here showcases the potential for algorithmic load event recognition using the extracted signatures
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