activity
20052021
most citedSubspace Methods for Data Attack on State Estimation: A Data Driven Approach

206 citations · 854 across the 54 of their papers we have counts for

collaborators

55 papers

eess.SY2021

A Scenario-oriented Approach to Energy-Reserve Joint Procurement and Pricing

Jiantao Shi, Ye Guo, Lang Tong +2

We consider some crucial problems related to the secure and reliable operation of power systems with high renewable penetrations: how much reserve should we procure, how should res…

eess.SY2021

Pricing Energy Storage in Real-time Market

Cong Chen, Lang Tong, Ye Guo

The problem of pricing utility-scale energy storage resources (ESRs) in the real-time electricity market is considered. Under a rolling-window dispatch model where the operator cen…

math.OC2021

Deferrable Load Scheduling under Demand Charge: A Block Model-Predictive Control Approach

Lei Yang, Xinbo Geng, Xiaohong Guan +1

Optimal scheduling of deferrable electrical loads can reshape the aggregated load profile to achieve higher operational efficiency and reliability. This paper studies deferrable lo…

eess.SP2021★ 5 cited

Non-Bayesian Parametric Missing-Mass Estimation

Shir Cohen, Tirza Routtenberg, Lang Tong

We consider the classical problem of missing-mass estimation, which deals with estimating the total probability of unseen elements in a sample. The missing-mass estimation problem…

eess.SY2020

Probabilistic Hosting Capacity Analysis via Bayesian Optimization

Xinbo Geng, Lang Tong, Anirban Bhattacharya +2

This paper studies the probabilistic hosting capacity analysis (PHCA) problem in distribution networks considering uncertainties from distributed energy resources (DERs) and reside…

cs.LG2020

Time Synchronized State Estimation for Incompletely Observed Distribution Systems Using Deep Learning Considering Realistic Measurement Noise

Behrouz Azimian, Reetam Sen Biswas, Anamitra Pal +1

Time-synchronized state estimation is a challenge for distribution systems because of limited real-time observability. This paper addresses this challenge by formulating a deep lea…