Transonic regular reﬂection for the unsteady transonic small disturbance equation—details of the subsonic solution Katarina Jegdic´, Barbara Lee Keyﬁtz, and Sunc˘ica C˘anic´

A solar-aided power generation (SAPG) system effectively promotes the high efficiency and low cost utilization of solar energy. In this paper, the SAPG system is represented by conventional coal-fired units and an annular Fresnel solar concentrator (AFSC) system. The annular Fresnel solar concentrator system is adopted to generate solar steam to replace the extraction steam of the turbine. According to the steam–water matrix equation and improved Flugel formula, the variable conditions simulation and analysis of the thermo-economic index were proposed by Matlab. Furthermore, in order to obtain the range of small disturbance, the method of partial replacement is used, that is, the extraction steam of the turbine is replaced from 0 to 100% with a step size of 20%. In this work, a SAPG system is proposed and its thermo-economic index and small disturbance scope are analyzed. The results show that the SAPG system is energy-saving, and the application scope of small disturbance is related to the quantity of the extraction steam and evaluation index.

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Online Steady-State Security Awareness Using Cellular Computation Networks and Fuzzy Techniques

Energies ◽

10.3390/en14010148 ◽

2020 ◽

Vol 14 (1) ◽

pp. 148

Author(s):

Lili Wu ◽

Ganesh K. Venayagamoorthy ◽

Jinfeng Gao

Keyword(s):

Steady State ◽

Power System ◽

Customer Service ◽

Situation Awareness ◽

Power Flow ◽

Load Flow ◽

Security Level ◽

Small Disturbance ◽

State Security ◽

Cellular Computation

Power system steady-state security relates to its robustness under a normal state as well as to withstanding foreseeable contingencies without interruption to customer service. In this study, a novel cellular computation network (CCN) and hierarchical cellular rule-based fuzzy system (HCRFS) based online situation awareness method regarding steady-state security was proposed. A CCN-based two-layer mechanism was applied for voltage and active power flow prediction. HCRFS block was applied after the CCN prediction block to generate the security level of the power system. The security status of the power system was visualized online through a geographic two-dimensional visualization mechanism for voltage magnitude and load flow. In order to test the performance of the proposed method, three types of neural networks were embedded in CCN cells successively to analyze the characteristics of the proposed methodology under white noise simulated small disturbance and single contingency. Results show that the proposed CCN and HCRFS combined situation awareness method could predict the system security of the power system with high accuracy under both small disturbance and contingencies.

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