Online Assessment of Conservation Voltage Reduction Effects With Micro-perturbation

Abstract

Online assessment of conservation voltage reduction (CVR) has great effects on the performance of CVR-based applications, especially for real-time CVR-based controls. The challenges of online CVR assessment mainly come from time-varying load composition and inevitable noise. Besides, the dynamic process resulting from motors further complicates this problem. This article proposes a micro-perturbation based load-to-voltage (LTV) process identification method to online assess the CVR effects. In particular, we construct a well-designed pseudo-random-binary-sequence voltage perturbation to excite the CVR process continually and fully. With the experimental data, the CVR factor and transfer function of LTV are estimated by the cross-correlation method, which can reflect both steady-state and dynamic CVR effects without being affected by noise. The proposed method is verified on a specific hardware-in-the-loop testbed under various cases. In addition, through the energy-saving and power smoothing applications, the impact of CVR assessment on performance of CVR-based applications is also analyzed, which further verify the validity and economic benefits of the proposed assessment method.