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View article: Tractable Data Enriched Distributionally Robust Chance-Constrained Conservation Voltage Reduction
Tractable Data Enriched Distributionally Robust Chance-Constrained Conservation Voltage Reduction Open
This paper proposes a tractable distributionally robust chance-constrained conservation voltage reduction (DRCC-CVR) method with enriched data-based ambiguity set in unbalanced three-phase distribution systems. The increasing penetration o…
View article: Tractable Data Enriched Distributionally Robust Chance-Constrained CVR
Tractable Data Enriched Distributionally Robust Chance-Constrained CVR Open
This paper proposes a tractable distributionally robust chance-constrained conservation voltage reduction (DRCC-CVR) method with enriched data-based ambiguity set in unbalanced three-phase distribution systems. The increasing penetration o…
View article: Multisource Data Fusion Outage Location in Distribution Systems via Probabilistic Graphical Models
Multisource Data Fusion Outage Location in Distribution Systems via Probabilistic Graphical Models Open
Efficient outage location is critical to enhancing the resilience of power distribution systems. However, accurate outage location requires combining massive evidence received from diverse data sources, including smart meter (SM) last gasp…
View article: Analyzing Photovoltaic's Impact on Conservation Voltage Reduction in Distribution Networks
Analyzing Photovoltaic's Impact on Conservation Voltage Reduction in Distribution Networks Open
Conservation voltage reduction (CVR) has been widely implemented in distribution networks and helped utilities effectively reduce energy and peak load. However, the increasing penetration level of solar photovoltaic (PV) has affected volta…
View article: A Two-layer Approach for Estimating Behind-the-Meter PV Generation Using Smart Meter Data
A Two-layer Approach for Estimating Behind-the-Meter PV Generation Using Smart Meter Data Open
As the cost of the residential solar system decreases, rooftop photovoltaic (PV) has been widely integrated into distribution systems. Most rooftop PV systems are installed behind-the-meter (BTM), i.e., only the net demand is metered, whil…
View article: Enriching Load Data Using Micro-PMUs and Smart Meters
Enriching Load Data Using Micro-PMUs and Smart Meters Open
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 limited locations in distribution networks due to budgetary cons…
View article: Distributed Optimal Conservation Voltage Reduction in Integrated Primary-Secondary Distribution Systems
Distributed Optimal Conservation Voltage Reduction in Integrated Primary-Secondary Distribution Systems Open
This paper proposes an asynchronous distributed leader-follower control method to achieve conservation voltage reduction (CVR) in three-phase unbalanced distribution systems by optimally scheduling smart inverters of distributed energy res…
View article: Disaggregating Customer-Level Behind-the-Meter PV Generation Using Smart Meter Data and Solar Exemplars
Disaggregating Customer-Level Behind-the-Meter PV Generation Using Smart Meter Data and Solar Exemplars Open
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 recorded. Therefore, the native demand and PV generation are…
View article: A Hierarchical Deep Actor-Critic Learning Method for Joint Distribution System State Estimation
A Hierarchical Deep Actor-Critic Learning Method for Joint Distribution System State Estimation Open
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 requires solving the distribution system state estimation (DSSE…
View article: Multi-Source Data Fusion Outage Location in Distribution Systems via Probabilistic Graph Models
Multi-Source Data Fusion Outage Location in Distribution Systems via Probabilistic Graph Models Open
Efficient outage location is critical to enhancing the resilience of power distribution systems. However, accurate outage location requires combining massive evidence received from diverse data sources, including smart meter (SM) last gasp…
View article: Multi-Source Data-Driven Outage Location in Distribution Systems Using Probabilistic Graph Learning.
Multi-Source Data-Driven Outage Location in Distribution Systems Using Probabilistic Graph Learning. Open
Efficient outage location is critical to enhancing the resilience of power systems. However, accurate outage location requires combining massive evidence received from diverse data sources, including smart meter (SM) signals, customer trou…
View article: Enriching Load Data Using Micro-PMUs and Smart Meters
Enriching Load Data Using Micro-PMUs and Smart Meters Open
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 limited locations in distribution networks due to budgetary cons…
View article: Quantifying Load Uncertainty Using Real Smart Meter Data
Quantifying Load Uncertainty Using Real Smart Meter Data Open
As we get closer to customers in distribution systems, load stochasticity increases. In the past, due to lack of real-time data, the comprehensive knowledge of load behavior was limited, and simplistic assumptions had to be made for distri…
View article: Disaggregating Customer-level Behind-the-Meter PV Generation Using Smart Meter Data
Disaggregating Customer-level Behind-the-Meter PV Generation Using Smart Meter Data Open
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 recorded. Therefore, the native demand and PV generation are …
View article: WECC Composite Load Model Parameter Identification Using Evolutionary Deep Reinforcement Learning
WECC Composite Load Model Parameter Identification Using Evolutionary Deep Reinforcement Learning Open
Due to the increasing penetration of distributed energy resources (DERs), the load composition in distribution grids has significantly changed. This inverter-based device has notably different behavior from traditional static and induction…
View article: Outage Detection in Partially Observable Distribution Systems Using Smart Meters and Generative Adversarial Networks
Outage Detection in Partially Observable Distribution Systems Using Smart Meters and Generative Adversarial Networks Open
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 distribution. To achieve this, first, a breadth-first search (…
View article: A Data-Driven Customer Segmentation Strategy Based on Contribution to System Peak Demand
A Data-Driven Customer Segmentation Strategy Based on Contribution to System Peak Demand Open
Advanced metering infrastructure (AMI) enables utilities to obtain granular energy consumption data, which offers a unique opportunity to design customer segmentation strategies based on their impact on various operational metrics in distr…
View article: Statistical Modeling of Networked Solar Resources for Assessing and Mitigating Risk of Interdependent Inverter Tripping Events in Distribution Grids
Statistical Modeling of Networked Solar Resources for Assessing and Mitigating Risk of Interdependent Inverter Tripping Events in Distribution Grids Open
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 quantify this risk utilities need to solve the interactive …
View article: A Data-Driven Game-Theoretic Approach for Behind-the-Meter PV Generation Disaggregation
A Data-Driven Game-Theoretic Approach for Behind-the-Meter PV Generation Disaggregation Open
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-meter (BTM), where only customers' net demand is recorded b…
View article: Two-Layer Volt/VAR Control in Unbalanced Active Distribution Systems: Efficient Optimization and Accurate Tracking
Two-Layer Volt/VAR Control in Unbalanced Active Distribution Systems: Efficient Optimization and Accurate Tracking Open
This paper proposes a novel two-layer Volt/VAR control (VVC) framework to regulate the voltage profiles across an unbalanced active distribution system, which achieves both the efficient open-loop optimization and accurate closed-loop trac…
View article: Outage Detection in Partially Observable Distribution Systems using Smart Meters and Generative Adversarial Networks
Outage Detection in Partially Observable Distribution Systems using Smart Meters and Generative Adversarial Networks Open
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 distribution. To achieve this, first, a breadth-first search (…
View article: A Probabilistic Data-Driven Method for Photovoltaic Pseudo-Measurement Generation in Distribution Systems
A Probabilistic Data-Driven Method for Photovoltaic Pseudo-Measurement Generation in Distribution Systems Open
This paper presents a probabilistic data-driven method to model the uncertainty of distributed photovoltaic (PV) generation to enhance the observability of distribution grids with a high penetration of renewable resources. The proposed met…
View article: A Data-Driven Framework for Assessing Cold Load Pick-Up Demand in Service Restoration
A Data-Driven Framework for Assessing Cold Load Pick-Up Demand in Service Restoration Open
Cold load pick-up (CLPU) has been a critical concern to utilities.\nResearchers and industry practitioners have underlined the impact of CLPU on\ndistribution system design and service restoration. The recent large-scale\ndeployment of sma…
View article: Data-Driven Based Method for Power System Time-Varying Composite Load Modeling
Data-Driven Based Method for Power System Time-Varying Composite Load Modeling Open
Fast and accurate load parameters identification has great impact on the power systems operation and stability analysis. This paper proposes a novel transfer reinforcement learning based method to identify composite ZIP and induction motor…
View article: A Multi-Timescale Data-Driven Approach to Enhance Distribution System Observability
A Multi-Timescale Data-Driven Approach to Enhance Distribution System Observability Open
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 systems. Using the proposed method, the daily consumption of…
View article: A Survey on State Estimation Techniques and Challenges in Smart Distribution Systems
A Survey on State Estimation Techniques and Challenges in Smart Distribution Systems Open
This paper presents a review of the literature on state estimation (SE) in power systems. While covering works related to SE in transmission systems, the main focus of this paper is distribution system SE (DSSE). The critical topics of DSS…