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
  • [1] Renewable Energy System Design by Artificial Neural Network Simulation Approach
    Kumar, Amar
    Zaman, Marzia
    Goel, Nita
    Srivastava, Vineet
    2014 IEEE ELECTRICAL POWER AND ENERGY CONFERENCE (EPEC), 2014, : 142 - 147
  • [2] Design of Solar Energy Based System Using Artificial Neural Network Controller
    Vinita
    Nain, Abhimanyu
    Saroha, Sumit
    JOURNAL OF ELECTRICAL SYSTEMS, 2024, 20 (05) : 282 - 289
  • [3] Design of energy consumption monitoring system of public buildings based on artificial neural network
    He C.
    Lin J.
    Xiang X.
    Yu L.
    Xiong H.-H.
    International Journal of Industrial and Systems Engineering, 2022, 41 (03) : 349 - 362
  • [4] Scheduling Distributed Energy Resources in an isolated grid - An Artificial Neural Network Approach
    Vale, Z. A.
    Faria, P.
    Morais, H.
    Khodr, H. M.
    Silva, M.
    Kadar, P.
    IEEE POWER AND ENERGY SOCIETY GENERAL MEETING 2010, 2010,
  • [5] Artificial neural network based approach for dynamic parameter design
    Jung, Jae-Ryung
    Yum, Bong-Jin
    EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (01) : 504 - 510
  • [6] Design of an environmental monitoring system based on artificial neural network
    Wang, WJ
    Jia, LF
    INTERNATIONAL CONFERENCE ON SENSORS AND CONTROL TECHNIQUES (ICSC 2000), 2000, 4077 : 392 - 395
  • [7] A Design of a Tax Prediction System based on Artificial Neural Network
    Jang, Sung-Bong
    2019 INTERNATIONAL CONFERENCE ON PLATFORM TECHNOLOGY AND SERVICE (PLATCON), 2019, : 123 - 126
  • [8] Design of speaker recognition system based on artificial neural network
    Chen, Yanhong
    Wang, Li
    Lin, Han
    Li, Jinlong
    6TH INTERNATIONAL SYMPOSIUM ON ADVANCED OPTICAL MANUFACTURING AND TESTING TECHNOLOGIES: OPTICAL SYSTEM TECHNOLOGIES FOR MANUFACTURING AND TESTING, 2012, 8420
  • [9] An artificial neural network system of distributed precipitation estimation based on EOS/MODIS
    Zhang Qiuwen
    Wang Cheng
    Liu Zhong
    Shinohara, Fumio
    Yamaoka, Tatsuo
    ADVANCED COMPUTER TECHNOLOGY, NEW EDUCATION, PROCEEDINGS, 2007, : 29 - 33
  • [10] Development of a Distributed Energy Router Control System Based on a Neural Network
    Sosnina, Elena N.
    Shumskii, Nikita, V
    Shramko, Pavel A.
    2020 INTERNATIONAL URAL CONFERENCE ON ELECTRICAL POWER ENGINEERING (URALCON), 2020, : 313 - 317
12345