Z
Zhi Zhou
Researcher at Argonne National Laboratory
Publications - 62
Citations - 2586
Zhi Zhou is an academic researcher from Argonne National Laboratory. The author has contributed to research in topics: Wind power & Electricity market. The author has an hindex of 26, co-authored 58 publications receiving 2075 citations. Previous affiliations of Zhi Zhou include Rensselaer Polytechnic Institute.
Papers
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Journal ArticleDOI
Wind Power Trading Under Uncertainty in LMP Markets
Audun Botterud,Zhi Zhou,Jianhui Wang,Ricardo J. Bessa,Hrvoje Keko,Jean Sumaili,Vladimiro Miranda +6 more
TL;DR: In this article, a new model for optimal trading of wind power in day-ahead (DA) electricity markets under uncertainty in wind power and prices is presented, where utility theory and conditional value at risk (CVAR) are used to represent the risk preferences of the wind power producers.
Journal ArticleDOI
Agent-Based Electricity Market Simulation With Demand Response From Commercial Buildings
Zhi Zhou,Fei Zhao,Jianhui Wang +2 more
TL;DR: The results indicate that there is a noticeable impact from commercial buildings with price-responsive demand on the electricity market, and this impact differs with different scales of DR participation under different levels of market competitions.
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Energy Storage Arbitrage Under Day-Ahead and Real-Time Price Uncertainty
TL;DR: In this paper, a stochastic formulation of a storage owner's arbitrage profit maximization problem under uncertainty in day-ahead and real-time market prices is proposed, which helps storage owners in market bidding and operational decisions and in estimation of the economic viability of energy storage.
Journal ArticleDOI
Time-adaptive quantile-copula for wind power probabilistic forecasting
TL;DR: A novel time-adaptive quantile-copula estimator for kernel density forecast and a discussion of how to select the adequate kernels for modeling the different variables of the problem are presented.
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Agent-based simulation of electricity markets: a survey of tools
TL;DR: An agent-based simulation framework for electricity Markets is described to facilitate the development of future models for electricity markets.