Time-Varying Conservation Voltage Reduction Evaluation with Ground Truth Validation

Accurate evaluation of the conservation voltage reduction (CVR) effect is paramount in achieving peak load reduction, conserving energy, and optimizing various power system control strategies related to CVR. Given the dynamic nature of loading conditions, it becomes crucial to develop a precise method for computing the time-varying CVR factor. Existing methods are solely validated on field measurements, lacking comparison with ground truth to justify their accuracy. To address these issues, this paper first proposes a time-varying CVR factor computation approach, utilizing load modeling and a sliding window methodology. Then, to validate the accuracy of our proposed method against ground truth, we construct an OpenDSS model to simulate a real utility feeder under controlled loading conditions. Finally, simulation results verify the effectiveness and accuracy of the proposed time-varying CVR factor computation method.

I. Introduction

Conservation Voltage Reduction (CVR) is pivotal for optimizing energy consumption and addressing voltage-related challenges in power systems [1]. Assessing the impact of CVR on specific feeders is essential for utilities to pinpoint opportunities for optimal energy savings. Empirical tests have established a connection, revealing a 0.3%-1% reduction in load consumption for every 1% decrease in voltage, encapsulated by the CVR factor [2]. However, computing this factor is intricate. It is influenced by factors such as power grid configurations, load types, customer behaviors, and local weather, resulting in stochastic and time-variant loading conditions [3]. Furthermore, the growing integration of distributed generators, microgrids, electric vehicles, and demand response strategies makes the grid more active, complicating CVR factor computation [4]–[7]. Consequently, achieving a precise and robust evaluation of the CVR factor remains a significant challenge in effectively implementing CVR strategies.