Zobrazeno 1 - 10
of 424
pro vyhledávání: '"Zhao Changhong"'
Experimental evaluation of velocity sensitivity for conglomerate reservoir rock in Karamay oil field
Autor:
Han Haishui, Zhang Qun, Lv Weifeng, Han Lu, Ji Zemin, Zhang Shanyan, Zhao Changhong, Kang Hao, Sun Linghui, Shen Rui
Publikováno v:
Science and Engineering of Composite Materials, Vol 30, Iss 1, Pp 24-32 (2023)
Velocity sensitivity refers to the possibility and degree of reservoir permeability decline caused by the migration of various particles in the reservoir rock due to the increase in fluid flow velocity and the blockage of pore channels. To improve th
Externí odkaz:
https://doaj.org/article/41ca31b04ec0476c89403ff3168e5459
Autor:
Liang, Heng, Zhao, Changhong
The traditional machine learning models to solve optimal power flow (OPF) are mostly trained for a given power network and lack generalizability to today's power networks with varying topologies and growing plug-and-play distributed energy resources
Externí odkaz:
http://arxiv.org/abs/2309.12849
Autor:
Chen, Yue, Zhao, Changhong
Decarbonizing electric grids is a crucial global endeavor in the pursuit of carbon neutrality. Taking carbon emissions from generation into account when pricing electricity usage is an essential way to achieve this goal. However, such pricing is not
Externí odkaz:
http://arxiv.org/abs/2308.08195
Linear approximation commonly used in solving alternating-current optimal power flow (AC-OPF) simplifies the system models but incurs accumulated voltage errors in large power networks. Such errors will make the primal-dual type gradient algorithms c
Externí odkaz:
http://arxiv.org/abs/2306.04350
The wide deployment of distributed renewable energy sources and electric vehicles can help mitigate climate crisis. This necessitates new business models in the power sector to hedge against uncertainties while imposing a strong coupling between the
Externí odkaz:
http://arxiv.org/abs/2305.17410
In this paper, we revisit the problem of Differentially Private Stochastic Convex Optimization (DP-SCO) in Euclidean and general $\ell_p^d$ spaces. Specifically, we focus on three settings that are still far from well understood: (1) DP-SCO over a co
Externí odkaz:
http://arxiv.org/abs/2303.18047
Autor:
Huang, Wanjun, Zhao, Changhong
Power distribution networks are approaching their voltage stability boundaries due to the severe voltage violations and the inadequate reactive power reserves caused by the increasing renewable generations and dynamic loads. In the broad endeavor to
Externí odkaz:
http://arxiv.org/abs/2208.08051
Publikováno v:
Systems & Control Letters, vol. 185, p. 105753, 2024
This paper proposes a reinforcement learning-based approach for optimal transient frequency control in power systems with stability and safety guarantees. Building on Lyapunov stability theory and safety-critical control, we derive sufficient conditi
Externí odkaz:
http://arxiv.org/abs/2207.03329
Autor:
Huang, Wanjun, Zhao, Changhong
We propose an improved successive branch reduction (SBR) method to solve stochastic distribution network reconfiguration (SDNR), a mixed-integer program that is known to be computationally challenging. First, for a special distribution network with a
Externí odkaz:
http://arxiv.org/abs/2206.00327
Existing algorithms to solve alternating-current optimal power flow (AC-OPF) often exploit linear approximations to simplify system models and accelerate computations. In this paper, we improve a recent hierarchical OPF algorithm, which rested on pri
Externí odkaz:
http://arxiv.org/abs/2204.04827