信息与控制2017，Vol.46Issue(4)：415-421,7.DOI:10.13976/j.cnki.xk.2017.0415
基于递归神经网络和蚁群优化算法的发电环保调度
Power Generation Dispatching for Environmental Protection Based on Recursive Neural Network and Ant Colony Optimization Algorithm
摘要
Abstract
We propose a new regression model to fit power generation and emission data (SO2, NOx, and soot) by using recurrent neural network (RNN).On the basis of the regression model and ant colony optimization (ACO), we design a real-time power generation dispatching algorithm for reducing total pollutant emissions under the premise of completing real-time power generation and achieving energy saving and emission reduction.We evaluate our proposal by using the real electricity data of Anhui Electric Power.Experimental results show the effectiveness of our method.关键词
发电调度/节能减排/回归分析/蚁群优化算法Key words
powergeneration dispatching/energy saving and emission reduction/regression analysis/ant colony optimization algorithm分类
信息技术与安全科学引用本文复制引用
柯余洋,杨训政,熊焰,梁肖..基于递归神经网络和蚁群优化算法的发电环保调度[J].信息与控制,2017,46(4):415-421,7.基金项目
国家自然科学基金重点资助项目(61232018) （61232018）
国网安徽省电力公司科技项目(52120015007W) （52120015007W）
