489 citations · 1.1k across the 17 of their papers we have counts for
17 papers
Mitigating Smart Meter Asynchrony Error Via Multi-Objective Low Rank Matrix Recovery
Yuxuan Yuan, Kaveh Dehghanpour, Zhaoyu Wang
Smart meters (SMs) are being widely deployed by distribution utilities across the U.S. Despite their benefits in real-time monitoring. SMs suffer from certain data quality issues;…
A Hierarchical Deep Actor-Critic Learning Method for Joint Distribution System State Estimation
Yuxuan Yuan, Kaveh Dehghanpour, Zhaoyu Wang +1
Due to increasing penetration of volatile distributed photovoltaic (PV) resources, real-time monitoring of customers at the grid-edge has become a critical task. However, this requ…
Multi-Source Data Fusion Outage Location in Distribution Systems via Probabilistic Graph Models
Yuxuan Yuan, Kaveh Dehghanpour, Zhaoyu Wang +1
Efficient outage location is critical to enhancing the resilience of power distribution systems. However, accurate outage location requires combining massive evidence received from…
Enriching Load Data Using Micro-PMUs and Smart Meters
Fankun Bu, Kaveh Dehghanpour, Zhaoyu Wang
In modern distribution systems, load uncertainty can be fully captured by micro-PMUs, which can record high-resolution data; however, in practice, micro-PMUs are installed at limit…
Disaggregating Customer-level Behind-the-Meter PV Generation Using Smart Meter Data and Solar Exemplars
Fankun Bu, Kaveh Dehghanpour, Yuxuan Yuan +2
Customer-level rooftop photovoltaic (PV) has been widely integrated into distribution systems. In most cases, PVs are installed behind-the-meter (BTM), and only the net demand is r…
Learning-Based Real-Time Event Identification Using Rich Real PMU Data
Yuxuan Yuan, Yifei Guo, Kaveh Dehghanpour +2
A large-scale deployment of phasor measurement units (PMUs) that reveal the inherent physical laws of power systems from a data perspective enables an enhanced awareness of power s…
Outage Detection in Partially Observable Distribution Systems using Smart Meters and Generative Adversarial Networks
Yuxuan Yuan, Kaveh Dehghanpour, Fankun Bu +1
In this paper, we present a novel data-driven approach to detect outage events in partially observable distribution systems by capturing the changes in smart meters' (SMs) data dis…
Statistical Modeling of Networked Solar Resources for Assessing and Mitigating Risk of Interdependent Inverter Tripping Events in Distribution Grids
Kaveh Dehghanpour, Yuxuan Yuan, Fankun Bu +1
It is speculated that higher penetration of inverter-based distributed photo-voltaic (PV) power generators can increase the risk of tripping events due to voltage fluctuations. To…
A Data-Driven Game-Theoretic Approach for Behind-the-Meter PV Generation Disaggregation
Fankun Bu, Kaveh Dehghanpour, Yuxuan Yuan +2
Rooftop solar photovoltaic (PV) power generator is a widely used distributed energy resource (DER) in distribution systems. Currently, the majority of PVs are installed behind-the-…
Multi-Agent Safe Policy Learning for Power Management of Networked Microgrids
Qianzhi Zhang, Kaveh Dehghanpour, Zhaoyu Wang +2
This paper presents a supervised multi-agent safe policy learning (SMAS-PL) method for optimal power management of networked microgrids (MGs) in distribution systems. While convent…
A Time-Series Distribution Test System Based on Real Utility Data
Fankun Bu, Yuxuan Yuan, Zhaoyu Wang +2
In this paper, we provide a time-series distribution test system. This test system is a fully observable distribution grid in Midwest U.S. with smart meters (SM) installed at all e…
A Data-Driven Customer Segmentation Strategy Based on Contribution to System Peak Demand
Yuxuan Yuan, Kaveh Dehghanpour, Fankun Bu +1
Advanced metering infrastructure (AMI) enables utilities to obtain granular energy consumption data, which offers a unique opportunity to design customer segmentation strategies ba…
A Data-Driven Framework for Assessing Cold Load Pick-up Demand in Service Restoration
Fankun Bu, Kaveh Dehghanpour, Zhaoyu Wang +1
Cold load pick-up (CLPU) has been a critical concern to utilities. Researchers and industry practitioners have underlined the impact of CLPU on distribution system design and servi…
A Learning-based Power Management for Networked Microgrids Under Incomplete Information
Qianzhi Zhang, Kaveh Dehghanpour, Zhaoyu Wang +1
This paper presents an approximate Reinforcement Learning (RL) methodology for bi-level power management of networked Microgrids (MG) in electric distribution systems. In practice,…
A Survey on State Estimation Techniques and Challenges in Smart Distribution Systems
Kaveh Dehghanpour, Zhaoyu Wang, Jianhui Wang +2
This paper presents a review of the literature on State Estimation (SE) in power systems. While covering some works related to SE in transmission systems, the main focus of this pa…
A Game-Theoretic Data-Driven Approach for Pseudo-Measurement Generation in Distribution System State Estimation
Kaveh Dehghanpour, Yuxuan Yuan, Zhaoyu Wang +1
In this paper, we present an efficient computational framework with the purpose of generating weighted pseudo-measurements to improve the quality of Distribution System State Estim…
A Multi-Timescale Data-Driven Approach to Enhance Distribution System Observability
Yuxuan Yuan, Kaveh Dehghanpour, Fankun Bu +1
This paper presents a novel data-driven method that determines the daily consumption patterns of customers without smart meters (SMs) to enhance the observability of distribution s…