Application of Multi-agent in Power Term Load Forecasting

被引:0
|
作者
Zhao Wenqing [1 ]
Niu Chunxiang [1 ]
Wang Fei [1 ]
机构
[1] N China Elect Power Univ, Sch Control & Comp Engn, Baoding 071003, Hebei Province, Peoples R China
关键词
electric system; mid-long term load forecasting; Multi-agent;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The mid-long term electric load forecasting provide essential data for the grid planning, it is helpful to optimize the planning of the power system. Solving the problem by the way of some agents' cooperation is the focus of multi-agent systems theory and technology. It is more useful to do the forecasting by the multi-agent collaboration than individual agent do it independently. So that, in this paper introduces a multi-agent system diagnosis model. This model include three diagnosis-agents, a management-agent and fusion-agent. In this model the Diagnosis-agent are established according to the growth trend prediction technology, regression model and Grey forecasting techniques, which are three different kinds of load forecasting algorithm. Those diagnosis-agents are regulated and controlled by the Management-agent, which purpose to achieve the fault diagnosis in consultation under all diagnosis-agents. The fusion-agent will give the final load under the control situation which is from the Management-agent's message, forecasting result which should be from all the Diagnosis-agents' forecast result and numbers of different diagnosis-agent.
引用
收藏
页码:359 / 362
页数:4
相关论文
共 50 条
  • [1] Multi-Agent Framework for Spatial Load Forecasting
    Melo, J. D.
    Carreno, E. M.
    Padilha-Feltrin, A.
    2011 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING, 2011,
  • [2] Electric Load Forecasting: A Multi-Agent Systems Approach
    Nejat, A.
    Mohsenian-Rad, H.
    2012 15TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2012, : 863 - 869
  • [3] Multi-agent residential demand response based on load forecasting
    Dusparic, Ivana
    Harris, Colin
    Marinescu, Andrei
    Cahill, Vinny
    Clarke, Siobhan
    2013 1ST IEEE CONFERENCE ON TECHNOLOGIES FOR SUSTAINABILITY (SUSTECH), 2013, : 90 - 96
  • [4] Multi-Agent GIS System for Improved Spatial Load Forecasting
    Borges, Cruz E.
    Kamara Esteban, Oihane
    Pijoan, Ander
    Penya, Yoseba K.
    AAMAS'14: PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS, 2014, : 1667 - 1668
  • [5] A Cooperative Multi-Agent System for Wind Power Forecasting
    Esteoule, Tanguy
    Perles, Alexandre
    Bernon, Carole
    Gleizes, Marie-Pierre
    Barthod, Morgane
    ADVANCES IN PRACTICAL APPLICATIONS OF AGENTS, MULTI-AGENT SYSTEMS, AND COMPLEXITY: THE PAAMS COLLECTION, 2018, 10978 : 152 - 163
  • [6] Multi-agent load power segregation for electric vehicles
    Rosario, LC
    Economou, JT
    Luk, PCK
    2005 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC), 2005, : 91 - 96
  • [7] Multi-Agent Simulation of Urban Social Dynamics for Spatial Load Forecasting
    Melo, Joel D.
    Carreno, Edgar Manuel
    Padilha-Feltrin, Antonio
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2012, 27 (04) : 1870 - 1878
  • [8] Multi-agent consensus for distributed power dispatch with load balancing
    Hanada, Kenta
    Wada, Takayuki
    Masubuchi, Izumi
    Asai, Toru
    Fujisaki, Yasumasa
    ASIAN JOURNAL OF CONTROL, 2021, 23 (02) : 611 - 619
  • [9] Automatic Power Load Balancing using a Multi-Agent System
    Prymek, Miroslav
    Baxant, Petr
    Horak, Ales
    11TH INTERNATIONAL SCIENTIFIC CONFERENCE ELECTRIC POWER ENGINEERING 2010, PROCEEDINGS, 2010, : 93 - 97
  • [10] Application of Multi-Agent Evolutionary Algorithm for Load Optimal Dispatching Among Power Plant Units
    Hou Guolian
    Zhang Jianhua
    Yang Xin
    Zhou Beiwen
    2008 INTERNATIONAL CONFERENCE ON RISK MANAGEMENT AND ENGINEERING MANAGEMENT, ICRMEM 2008, PROCEEDINGS, 2008, : 145 - +