摘要
介绍了一种微机双绕组变压器负荷经济运行控制系统的基本工作原理、硬件结构框图和主要技术特点。该系统应用人工神经元网络技术所具有的强大的学习能力、一定的容错能力和对噪声的鲁棒性进行了短期负荷预测。该系统能自动地将日负荷曲线分为 2个典型时间段 ,并自动调整变压器的运行状态 ,最大限度地降低了变压器自身的电能损耗 ,从而达到节能。
The basic working principle, hardware structure and main technical features of a micro computer based control system for transformer economic operation is presented in this paper. Applying the advantages of artificial neural network, such as powerful learning ability, determinate error tolerance ability and the robustness to noise, the presented system can carry out the short term load forecasting, automatically divide the daily load curve into two typical time periods and regulate the transformer operation status within the two periods to reduce the loss of energy in transformer itself to a minimum to achieve the goal of saving energy and increasing economic benefit.
出处
《电网技术》
EI
CSCD
北大核心
2001年第9期44-47,共4页
Power System Technology
关键词
电力变压器
经济运行
神经网络
控制系统
saving energy
loss of energy
economic operation
artificial neural network
