Development and testing of the genetic algorithm to select a scenario of distributed generation power supply system

被引:3
|
作者
Bugaeva, Tatyana [1 ]
Khabarov, Alexandr [1 ]
Novikova, Olga [1 ]
Plotkina, Uliyana [1 ]
机构
[1] Peter Great St Petersburg Polytech Univ, Politech Skaya St 29, St Petersburg 195251, Russia
关键词
MULTIOBJECTIVE OPTIMIZATION;
D O I
10.1088/1757-899X/497/1/012056
中图分类号
F [经济];
学科分类号
02 ;
摘要
The rapid development of small distributed energy economy requires the justification and design of methods and models for planning the development of energy systems using distributed generation sources. We have studied the possibility of using the genetic algorithm to solve the problem of selecting a scenario of distributed generation power supply system. To do this, a problem-solving mechanism was developed in the MATLAB environment based on the genetic algorithm and its program code was built. In order to test the created genetic algorithm for a hypothetical large consumer of electrical and heat power with typical load curves, an optimal scenario of a power supply system based on distributed generation was searched. The analysis of the calculation results carried out using the proposed algorithm, evaluation of the model's behavior when the initial data changes, indicate its efficiency and effectiveness.
引用
收藏
页数:6
相关论文
共 50 条
  • [41] Development and Present Status of Multi-Energy Distributed Power Generation System
    Qiu, Yanhui
    Jiang, Jiahui
    Chen, Daolian
    2016 IEEE 8TH INTERNATIONAL POWER ELECTRONICS AND MOTION CONTROL CONFERENCE (IPEMC-ECCE ASIA), 2016,
  • [42] Power Demand and Supply Optimization in Islanded Microgrids with Distributed Generation
    Chidzonga, Richard
    Nleya, Bakhe
    Khumalo, Philani
    30TH SOUTHERN AFRICAN UNIVERSITIES POWER ENGINEERING CONFERENCE (SAUPEC 2022), 2022,
  • [43] Effect of Distributed Generation on Power Supply Reliability of Distribution Network
    Liu, Jinsong
    Zhang, Junyang
    Zhang, Da
    2015 8TH INTERNATIONAL CONFERENCE ON GRID AND DISTRIBUTED COMPUTING (GDC), 2015, : 32 - 35
  • [44] The HVDC Power Supply System Implementation in NTT Group and Next Generation Power Supply System
    Tanaka, Toru
    Matsumori, Hiroaki
    Hanaoka, Naoki
    Murai, Kensuke
    Takahashi, Akiko
    Yajima, Hiroya
    Babasaki, Tadatoshi
    2014 IEEE 36TH INTERNATIONAL TELECOMMUNICATIONS ENERGY CONFERENCE (INTELEC), 2014,
  • [45] Research on testing vehicular power supply system
    Zhou, YJ
    Gan, L
    Li, YL
    Wei, YM
    ISTM/2005: 6th International Symposium on Test and Measurement, Vols 1-9, Conference Proceedings, 2005, : 250 - 252
  • [46] Indoor Distributed Antenna System Planning with Optimized Antenna Power Using Genetic Algorithm
    Atawia, Ramy
    Ashour, Mohamed
    El Shabrawy, Tallal
    Hammad, Hany
    2013 IEEE 78TH VEHICULAR TECHNOLOGY CONFERENCE (VTC FALL), 2013,
  • [47] Modelling of Distributed Generation for Radial Power Flow Algorithm
    Kumar, James Ranjith R.
    Jain, Amit
    2015 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, INFORMATICS, COMMUNICATION AND ENERGY SYSTEMS (SPICES), 2015,
  • [48] A Typical Distributed Generation Scenario Reduction Method Based on an Improved Clustering Algorithm
    Lv, Sitong
    Li, Jianguo
    Guo, Yongxin
    Shi, Zhong
    APPLIED SCIENCES-BASEL, 2019, 9 (20):
  • [49] A genetic algorithm for the reliability optimization of a distributed system
    Chen, RS
    Chu, CC
    Yeh, YS
    NINTH INTERNATIONAL WORKSHOP ON DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS, 1998, : 484 - 489
  • [50] A GENETIC ALGORITHM FOR DISTRIBUTED SYSTEM TOPOLOGY DESIGN
    KUMAR, A
    PATHAK, RM
    GUPTA, YP
    PARSAEI, HR
    COMPUTERS & INDUSTRIAL ENGINEERING, 1995, 28 (03) : 659 - 670