Ziming Yan
Nanyang Technological University
21 Papers
Ziming Yan is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Chemistry & Combustion. The author has an hindex of 3, co-authored 3 publications.
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Papers
Data-Driven Load Frequency Control for Stochastic Power Systems: A Deep Reinforcement Learning Method With Continuous Action Search
Ziming Yan,Yan Xu +1 more
TL;DR: This letter proposes a data-driven, model-free method for load frequency control against renewable energy uncertainties based on deep reinforcement learning (DRL) in continuous action domain that can nonlinearly derive control strategies to minimize frequency deviation with faster response speed and stronger adaptability for unmolded system dynamics.
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A Multi-Agent Deep Reinforcement Learning Method for Cooperative Load Frequency Control of a Multi-Area Power System
Ziming Yan,Yan Xu +1 more
TL;DR: Numerical simulations on a three-area power system and the fully-modeled New-England 39-bus system demonstrate that the proposed method can effectively minimize control errors against stochastic frequency variations caused by load and renewable power fluctuations.
283
Real-Time Optimal Power Flow: A Lagrangian Based Deep Reinforcement Learning Approach
Ziming Yan,Yan Xu +1 more
TL;DR: This letter proposes a real-time optimal power flow (RT-OPF) approach using Lagrangian-based deep reinforcement learning (DRL) in continuous action domain that can achieve a high solution optimality and constraint compliance in real- time.
140
Methanol and wet ethanol as interchangeable fuels for internal combustion engines: LCA, TEA, and experimental comparison
TL;DR: In this paper , a detailed lifecycle and technoeconomic analysis showed that by combining corn stover gas fermentation wet ethanol 80 and fermentation CO 2 -to-methanol, a 113% increase in alcohol fuel energy production per hectare of crop can be achieved compared to corn ethanol.
21
A Hybrid Data-Driven Method for Fast Solution of Security-Constrained Optimal Power Flow
Ziming Yan,Yan Xu +1 more
TL;DR: Wang et al. as mentioned in this paper proposed a hybrid data-driven method for fast solutions of preventive security-constrained optimal power flow (SCOPF) of power systems, where the action-value function of DRL is augmented by contingency security constraints.
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