Research on the index system to evaluate power system steady state security with UPFC

2010 ◽  
Author(s):  
Li Li ◽  
Zongxiang Lu ◽  
Arui Qiu
Keyword(s):  
Steady State ◽  
Power System ◽  
Index System ◽  
State Security ◽  
The Index System

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

Energies ◽  
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.

Study on Demand Side Management of Railway Electricity System

2014 ◽  
Vol 631-632 ◽  
pp. 1347-1350
Author(s):  
Bing Feng Liu
Keyword(s):  
Power System ◽  
Index System ◽  
Demand Side Management ◽  
Fuzzy Evaluation ◽  
Demand Side ◽  
Analytic Hierarchy ◽  
Electricity System ◽  
The Index System ◽  
Hierarchy Process

An index system for evaluating the demand side management (DSM) on railway temporary power system is established in this thesis, and the part weight and the whole weight of the index system are calculated by the analytic hierarchy process (AHP). The basic theory of fuzzy evaluation is introduced, and the feasibility of applying it to DSM on railway temporary power system is analyzed. Through the establishment of index system, evaluation and comparison to DSM projects can be carried out horizontal and vertical. Then identify gaps and weaknesses, analyze the causes, guide the consciousness of energy conservation and environmental protection, supervised of electricity in an orderly manner, establish DSM long-term management mechanism.

Applications of Lagrange-Quasi-Newton Method in Power System Steady-State Security Region

2012 ◽  
Vol 516-517 ◽  
pp. 1332-1336
Author(s):  
Zhong Cheng Li ◽  
Bu Han Zhang ◽  
Cheng Xiong Mao ◽  
Kui Wang
Keyword(s):  
Steady State ◽  
Power System ◽  
Wind Farm ◽  
System Security ◽  
Power System Security ◽  
Safe Operation ◽  
State Security ◽  
Security Region ◽  
The Impact ◽  
Quasi Newton

With the proportion of the installed capacity of wind farm in the grid increasing, the impact of wind farm on the power system security becomes obvious. The steady-state security analysis is one of the important measures to improve the power system security. Based on DC flow, considering the available transmission capability limit, the paper chooses the biggest security region volume as objective function with the upper and lower limits of security region multi-dimensional cuboid being as control variables, which transforms the maximum steady-state security region into nonlinear programming problem with linear constraints. This not only includes the biggest points for the safe operation, but also the order expansion problem doesn’t exist. Then Lagrange-Quasi-Newton is used to solve the equation, and the analysis of the example proves the feasibility of the proposed model and algorithm. Then we assume that wind speed distribution is weibull distribution, so we can assess the safe operation probability of wind power.

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