Neural networks for power management optimal strategy in hybrid microgrid

被引：0
作者：
Tiancai Wang
Xing He
Ting Deng
机构：
[1] Southwest University,Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering
来源：
Neural Computing and Applications | 2019年 / 31卷
关键词：
Hybrid microgrid; RBF neural network prediction; Quadratic optimization; Lagrange programming neural network; Renewable energy sources;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper proposes a more reasonable objective function for combined economic emission dispatch problem. To solve it, Lagrange programming neural network (LPNN) is utilized to obtain optimal scheduling of a hybrid microgrid, which includes power generation resources, variable demands and energy storage system for energy storing and supplying. Combining variable neurons with Lagrange neurons, the LPNN aims to minimize the cost function and maximize the power generated by the renewable sources. The asymptotic stability condition of the neurodynamic model is analyzed, and simulation results show that optimal power of each component with certain time interval can be obtained. In addition, a new method by radial basis function neural network is proposed to predict the power values of renewable energy and load demand, which are used as the input values in the optimal process.
引用
收藏
页码：2635 / 2647
页数：12
相关论文
共 95 条
[1]  
Wang J(1992)Recurrent neural network for solving quadratic programming problems with equality constraints Electron Lett 28 1345-1347
[2]  
Wang Y(2016)Optimal formation of multi-robot systems based on a recurrent neural network IEEE Trans Neural Netw Learn Syst 27 322-333
[3]  
Cheng L(2011)Recurrent neural network for non-smooth convex optimization problems with application to the identification of genetic regulatory networks IEEE Trans Neural Netw 21 714-726
[4]  
Hou ZG(2013)Dynamical optimal positioning of a photovoltaic panel in all weather conditions Appl Energy 108 429-438
[5]  
Junzhi Yu(2016)Impact of EV penetration on Volt–VAR optimization of distribution networks using real-time co-simulation monitoring platform Appl Energy 169 28-39
[6]  
Tan M(2015)Operational strategy optimization in an optimal sized smart microgrid IEEE Trans Smart Grid 6 1087-1095
[7]  
Cheng L(2016)Smart grid adaptive energy conservation and optimization engine utilizing particle swarm optimization and fuzzification Appl Energy 174 69-79
[8]  
Hou ZG(2015)Distributed optimal energy management in microgrids IEEE Trans Smart Grid 6 1137-1146
[9]  
Lin Y(2014)An integrated framework of agent-based modelling and robust optimization for microgrid energy management Appl Energy 129 70-88
[10]  
Tan M(2017)Improving frequency stability based on distributed control of multiple load aggregators IEEE Trans Smart Grid 8 1553-1567
12345678910