Design of distributed energy system based on artificial neural network approach

被引：0
|
作者：
Zhou, Yingya [1 ]
Zhou, Zhe [1 ]
Jiang, Dongxiang [1 ]
机构：
[1] Tsinghua Univ, Dept Thermal Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China
来源：
PROCEEDINGS OF THE 2013 FOURTH INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROL AND INFORMATION PROCESSING (ICICIP) | 2013年
关键词：
OPTIMIZATION; EXTRACTION; BUILDINGS; ALGORITHM;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Designing distributed energy system (DES) is a complex task due to large varieties and combinations of energy generation, conversion, and storage technologies as well as time-varying energy supplies and demands. In this article, an artificial neural network (ANN) is trained by known DES design samples. Results have shown that after training, ANN can approximate the complex DES mathematical model and yield similar new DES designs to the mathematical model, given new conditions of energy supplies and demands. The advantages of using ANN to design DES lie in the simple structure of ANN and the learning ability from practical as well as updated samples.
引用
收藏
页码：437 / 442
页数：6
相关论文
共 50 条
  • [41] DESIGN AND IMPLEMENTATION OF AN ARTIFICIAL NEURAL BASED CONTROL SYSTEM NETWORK FOR A MOVEMASTER ROBOTIC ARM
    Ramirez, Camilo Andres Gutierrez
    Beltran Garcia, Diego Felipe
    Montoya Gomez, Jairo Orlando
    INGENIERIA SOLIDARIA, 2009, 5 (09): : 68 - 74
  • [42] An Artificial Neural Network-Based Frequency Nadir Estimation Approach for Distributed Virtual Inertia Control
    Lu, Nanjun
    2019 IEEE 4TH INTERNATIONAL FUTURE ENERGY ELECTRONICS CONFERENCE (IFEEC), 2019,
  • [43] Artificial Neural Network based Chaotic System Design for the Simulation of EEG Time Series
    Zhang, Lei
    PROCEEDINGS OF 2018 IEEE 17TH INTERNATIONAL CONFERENCE ON COGNITIVE INFORMATICS & COGNITIVE COMPUTING (ICCI*CC 2018), 2018, : 217 - 221
  • [44] A Reference-Model-Based Artificial Neural Network Approach for a Temperature Control System
    Xu, Song
    Hashimoto, Seiji
    Jiang, YuQi
    Izaki, Katsutoshi
    Kihara, Takeshi
    Ikeda, Ryota
    Jiang, Wei
    PROCESSES, 2020, 8 (01)
  • [45] Design of Electromyography classification system using artificial neural network
    Horinek, Frantisek
    Jagelka, Martin
    Daricek, Martin
    Sladek, Eubomir
    Hanic, Michal
    Satka, Alexander
    2014 24TH INTERNATIONAL CONFERENCE RADIOELEKTRONIKA (RADIOELEKTRONIKA 2014), 2014,
  • [46] Design of an artificial neural network for assembly sequence planning system
    Erciyes University, Engineering Faculty, Department of Mechanical Engineering, 38039 Kayseri, Turkey
    Int J Ind Eng Theory Appl Pract, 2008, 1 (92-103):
  • [47] Design of An Artificial Neural Network for Assembly Sequence Planning System
    Sinanoglu, Cem
    INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE, 2008, 15 (01): : 92 - 103
  • [48] Artificial Neural Network Based Link OSNR Estimation with a Network Approach
    Yang, Zeyuan
    Gu, Rentao
    Wang, Dajiang
    Tan, Yanxia
    Li, Hongbiao
    Ji, Yuefeng
    FIBER OPTIC SENSING AND OPTICAL COMMUNICATION, 2018, 10849
  • [49] Artificial Neural Network Modeling for Efficient Photovoltaic System Design
    Paul, D.
    Mandal, S. N.
    Mukherjee, D.
    Chaudhuri, S. R. Bhadra
    2008 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER THEORY AND ENGINEERING, 2008, : 50 - +
  • [50] An Awareness-Based Artificial Neural Network for Cooperative Distributed Environments
    Paletta, Mauricio
    Herrero, Pilar
    BIO-INSPIRED SYSTEMS: COMPUTATIONAL AND AMBIENT INTELLIGENCE, PT 1, 2009, 5517 : 114 - +
12345