Intelligent Control Concepts for Automatic Generation Control of Electric Power Systems

电力系统自动发电控制的智能控制概念

• 批准号: 9216549
• 负责人: Roger King
• 金额: $ 23万
• 依托单位: Mississippi State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-09-15 至 1996-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9216549&HistoricalAwards=false
• 关键词: Intelligent; Control; Concepts; Automatic; Generation

The objective of this research is to develop a design for an intelligent automatic generation control (AGC) for use on electric power systems. Electric utilities use automatic generation control to balance their moment-to-moment electrical generation to load within a given control area. The Southern Electric System uses a performance index to grade its power plants on automatic generation control. The average year-to-date performance index for 48 coal-fired units is 57.9. In-other-words, the units are not performing as well as desired on classical AGC. This poor AGC performance is reflected in poor management of system resources and higher costs. The problem with the classical control approach is that it does not have the ability to intelligently assess changes within the system it is attempting to control. This research will explore two major areas in which to add intelligence to AGC - load forecasting and plant conditions. Significant improvements in AGC can be achieved through the integration of intelligent systems into the control system that can reason about the dynamic changes in the load and the generation facilities.

本研究的目的是设计一种用于电力系统的智能自动发电控制(AGC)。电力公用事业公司使用自动发电控制来平衡其在给定控制区域内的瞬时发电量和负荷。南方电力系统使用性能指数对其发电厂进行自动发电控制评级。今年迄今，48台燃煤机组的平均业绩指数为57.9。换句话说，在传统的AGC上，这些单元的表现并不像期望的那样好。这种糟糕的AGC性能反映在对系统资源的管理不善和成本较高上。经典控制方法的问题是，它没有能力智能地评估它试图控制的系统内的变化。这项研究将探索在AGC中增加智能的两个主要领域-负荷预测和工厂条件。通过将智能系统集成到控制系统中，可以对负荷和发电设施的动态变化进行推理，从而显著改善AGC。