An automatic generation control with adaptive frequency bias setting for current NERC performance standards

Le-Ren Chang-Chien, Purdue University

Abstract

Utilities in this country use automatic generation control to track continually changing loads. Because of the uncertainties and non-linearities of the equipment involved, the decision process is quite complicated. With generation now being deregulated, load and frequency regulations are considered ancillary services with associated costs. To ensure that the reliability and responsibility of interconnection operation are well maintained, NERC has introduced new performance standards, CPS1 and CPS2, for the control areas. Control areas failing to comply with these new standards would be penalized or subject to sanctions. Since over-regulation could increase regulating costs, control areas would have an interest in improving the operations of generating control at lower cost and maintaining the control performance at a satisfactory level. This thesis focuses on control enhancements with the refined ACE model of a control area. The information available from the ACE model could be gainfully used in the operations of load frequency control, such as establishing a fair measure to regulation costs, using the ACE model in an adaptive model reference for AGC control process, and performing on-line estimation of the control area's frequency response characteristic, β. Results showing the performance of the ACE decomposition method, ACE projection algorithm and β estimate in simulation conditions and on actual field data are presented. Issues related to the impacts on the real implementation of a refined ACE model, including non-linearities in the AGC control loops and generating units are examined. In addition, the benefits of using an adaptive frequency bias setting in the tie-line bias control, specifically its effectiveness in reducing over regulation and inter-area tie flow oscillations in different operating conditions are explored.

Degree

Ph.D.

Advisors

Ong, Purdue University.

Subject Area

Electrical engineering

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