Discussion of "AGC logic based on NERCs new control performance standard and disturbance control standard" [and reply]

2000 ◽  
Vol 15 (4) ◽  
pp. 1455-1456 ◽  
Author(s):  
N. Jaleeli ◽  
L.S. VanSlyck ◽  
M.M. Yao ◽  
R.R. Shoults ◽  
R. Kelm
Keyword(s):  
Performance Standard ◽  
Control Performance ◽  
Control Performance Standard

Research on the Supplementary Analysis System Based on CPS Standard

2012 ◽  
Vol 503-504 ◽  
pp. 1605-1608
Author(s):  
Hua Ting Tao ◽  
Li Li Ji
Keyword(s):  
Frequency Control ◽  
Power Grid ◽  
Influence Factors ◽  
Power Grids ◽  
Performance Standard ◽  
Control Performance ◽  
Control Performance Standard ◽  
Pros And Cons ◽  
Analysis System ◽  
Main Influence

CPS test standard has put forward new demands to the management of power grids. This paper analyzes the main influence factors of CPS, and introduces the way of building data warehouse and constructing supplementary analysis system on this basis, which can effectively help power grid workers to research the pros and cons in dispatch and operation. The application of the supplementary analysis system is helpful for Shanghai power grid to enhance AGC control and frequency control ability under the control performance standard.

Analysis of Salmonella Control Performance in U.S. Young Chicken Slaughter and Pork Slaughter Establishments

2009 ◽  
Vol 72 (1) ◽  
pp. 6-13 ◽  
Author(s):  
MARY K. MUTH ◽  
MANSOUR FAHIMI ◽  
SHAWN A. KARNS
Keyword(s):  
Food Safety ◽  
Hazard Analysis ◽  
Control Point ◽  
Analysis Data ◽  
Performance Standard ◽  
Control Performance ◽  
Critical Control Point ◽  
Microbiological Testing ◽  
Pathogen Control ◽  
Young Chicken

In the 1996 U.S. Food Safety and Inspection Service's (FSIS) “Pathogen Reduction; Hazard Analysis and Critical Control Point (PR/HACCP) Systems, Final Rule,” Salmonella was selected for microbiological testing and monitoring. Using data from an FSIS-sponsored survey of meat and poultry slaughter establishments, inspection results, and other establishment characteristics, potential variables affecting pathogen control, as measured by Salmonella test results, were investigated. The analysis data sets included 153 federally inspected young chicken slaughter establishments, of which 111 exceeded half the Salmonella performance standard at least once from 2003 through 2005, and 121 federally inspected pork slaughter establishments, of which 28 exceeded half the Salmonella performance standard. Logistic regression results for young chicken slaughter establishments indicate they were more likely to exceed half the standard if they had higher inspection noncompliance rates (P = 0.10) and older production space (P = 0.10), and were less likely to exceed it if they used a higher percentage of raw poultry inputs purchased from outside sources (P = 0.10). Results for pork slaughter establishments indicate they were more likely to exceed half the standard if they had a higher rate of voluntary microbiological testing (P = 0.08), and were less likely to exceed it if they were larger (P = 0.08) and used a higher percentage of raw pork inputs purchased from outside sources (P = 0.02). In general, indicators of plant characteristics, food safety practices, and management philosophy are associated with different levels of pathogen control performance that vary by species slaughtered.

scholarly journals Research on Intelligent Predictive AGC of a Thermal Power Unit Based on Control Performance Standards

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4073
Author(s):  
Daogang Peng ◽  
Yue Xu ◽  
Huirong Zhao
Keyword(s):  
Neural Network ◽  
Predictive Control ◽  
Optimization Model ◽  
Power Grid ◽  
Thermal Power ◽  
Automatic Generation ◽  
Performance Standard ◽  
Control Performance ◽  
Predictive Controller ◽  
Rolling Optimization

In order to satisfy the growing demands of control performance and operation efficiency in the automatic generation control (AGC) system of a grid, a novel, intelligent predictive controller, combined with predictive control and neural network ideas, is proposed and applied to the AGC systems of thermal power units. This paper proposes a Bayesian neural network identification model for typical ultra-supercritical thermal power units, which was found to be accurate and can be used as a simulation model. Based on the model, this paper develops an intelligent predictive control for the AGC of thermal power units, which improves unit load operation and constitutes a novel, closed-loop AGC structure based on online control performance standard (CPS) evaluations. Intelligent predictive control is mainly improved because the neural network rolling optimization model replaces the traditional rolling optimization model in the rolling optimization module. The simulation results indicate that the intelligent predictive controller developed in the two-area interconnected power grid under CPS can, on the one hand, improve the load tracking performance of AGC thermal power units, and, on the other hand, the controller has strong robustness. Whether the system parameters change considerably or the AGC has different grid disturbances, the new type of the loop AGC system can still sufficiently meet the control requirements of the power grid.

scholarly journals Intelligent Frequency Control Strategy Based on Reinforcement Learning of Multi-Objective Collaborative Reward Function

2021 ◽  
Vol 9 ◽  
Author(s):  
Lei Zhang ◽  
Yumiao Xie ◽  
Jing Ye ◽  
Tianliang Xue ◽  
Jiangzhou Cheng ◽  
...  
Keyword(s):  
Large Scale ◽  
Learning Strategy ◽  
Model Simulation ◽  
Frequency Control ◽  
Power Grid ◽  
Automatic Generation ◽  
Performance Standard ◽  
Control Performance ◽  
Multi Objective ◽  
Reward Function

Large scale wind power integration into the power grid will pose a serious threat to the frequency control of power system. If only Control Performance Standard (CPS) index is used as the evaluation standard of frequency quality, it will easily lead to short-term centralized frequency crossing, which will affect the effect of intelligent Automatic Generation Control (AGC) on frequency quality. In order to solve this problem, a multi-objective collaborative reward function is constructed by introducing a collaborative evaluation mechanism with multiple evaluation indexes. In addition, Negotiated W-Learning strategy is proposed to globally optimize the solution of the objective function from multi dimensions, it avoids the poor learning efficiency of the traditional Greedy strategy. The AGC control model simulation of standard two area interconnected power grid shows that the proposed intelligent strategy can effectively improve the frequency control performance and improve the frequency quality of the system in the whole-time scale.

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