489 citations · 1.8k across the 58 of their papers we have counts for
14 papers · 1 filter
Two-Layer Volt/VAR Control in Unbalanced Active Distribution Systems: Efficient Optimization and Accurate Tracking
Yifei Guo, Qianzhi Zhang, Zhaoyu Wang +2
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 eff…
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…
High-Fidelity Large-Signal Order Reduction Approach for Composite Load Model
Zixiao Ma, Zhaoyu Wang, Dongbo Zhao +1
With the increasing penetration of electronic loads and distributed energy resources (DERs), conventional load models cannot capture their dynamics. Therefore, a new comprehensive…
Singular Perturbation-based Large-Signal Order Reduction of Microgrids for Stability and Accuracy Synthesis with Control
Zixiao Ma, Zhaoyu Wang, Yuxuan Yuan +1
With the increasing penetration of distributed energy resources (DERs), it is of vital importance to study the dynamic stability of microgrids (MGs) with external control inputs in…
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…
Data-Driven Based Method for Power System Time-Varying Composite Load Modeling
Jian Xie, Zixiao Ma, Zhaoyu Wang +1
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…
Markov Decision Process-based Resilience Enhancement for Distribution Systems: An Approximate Dynamic Programming Approach
Chong Wang, Ping Ju, Shunbo Lei +2
Because failures in distribution systems caused by extreme weather events directly result in consumers' outages, this paper proposes a state-based decision-making model with the ob…
Counterintuitive VSM Behavior under CVR Incorporating Distribution System
Alok Kumar Bharati, Venkataramana Ajjarapu, Zhaoyu Wang
This paper analyses the impact of conservation by voltage reduction (CVR) on voltage stability margin (VSM) considering transmission and distribution (T&D) systems. VSM is determin…
Mathematical representation of the WECC composite load model
Zixiao Ma, Zhaoyu Wang, Yishen Wang +2
The Western Electricity Coordinating Council (WECC) composite load model is a newly developed load model that has drawn great interest from the industry. To analyze its dynamic cha…
A Markovian influence graph formed from utility line outage data to mitigate large cascades
Kai Zhou, Ian Dobson, Zhaoyu Wang +2
We use observed transmission line outage data to make a Markov influence graph that describes the probabilities of transitions between generations of cascading line outages, where…
Deep Generative Graph Distribution Learning for Synthetic Power Grids
Mahdi Khodayar, Jianhui Wang, Zhaoyu Wang
Power system studies require the topological structures of real-world power networks; however, such data is confidential due to important security concerns. Thus, power grid synthe…