24 citations · 87 across the 23 of their papers we have counts for
8 papers · 1 filter
Robust Data-driven Profile-based Pricing Schemes
Jingshi Cui, Haoxiang Wang, Chenye Wu +1
To enable an efficient electricity market, a good pricing scheme is of vital importance. Among many practical schemes, customized pricing is commonly believed to be able to best ex…
A Data-driven Storage Control Framework for Dynamic Pricing
Jiaman Wu, Zhiqi Wang, Chenye Wu +2
Dynamic pricing is both an opportunity and a challenge to the demand side. It is an opportunity as it better reflects the real time market conditions and hence enables an active de…
Improving Fictitious Play Reinforcement Learning with Expanding Models
Rong-Jun Qin, Jing-Cheng Pang, Yang Yu
Fictitious play with reinforcement learning is a general and effective framework for zero-sum games. However, using the current deep neural network models, the implementation of fi…
Vulnerability Analysis for Data Driven Pricing Schemes
Jingshi Cui, Haoxiang Wang, Chenye Wu +1
Data analytics and machine learning techniques are being rapidly adopted into the power system, including power system control as well as electricity market design. In this paper,…
Optimal Storage Control for Dynamic Pricing
Jiaman Wu, Zhiqi Wang, Yang Yu +1
Renewable energy brings huge uncertainties to the power system, which challenges the traditional power system operation with limited flexible resources. One promising solution is t…
Hierarchic Neighbors Embedding
Shenglan Liu, Yang Yu, Yang Liu +3
Manifold learning now plays a very important role in machine learning and many relevant applications. Although its superior performance in dealing with nonlinear data distribution,…