DocumentCode :
1777366
Title :
The research on the autonomous power balance framework for distribution network based on multi-agent modeling
Author :
Jin Yong ; Liu Junyong ; Li Hongwei ; Kong Bing ; Li Chao
Author_Institution :
Sch. of Electr. Eng. & Inf., Sichuan Univ., Chengdu, China
fYear :
2014
fDate :
20-22 Oct. 2014
Firstpage :
2629
Lastpage :
2634
Abstract :
The penetration of DG has brought many problems to the operation and management of distribution network. One of which is how to reasonably coordinate and allocate DCs outputs, how to achieve maximum use of energy and rational power efficiency under security and stability as well as how to meet the requirements of both global optimization and local autonomous control. Based on Muti-Agent Technology (MAS) and Replicator Dynamics (RD algorithm) of Evolutionary Game Theory, this paper analyzes the optimal scheduling of DG\´s output based on autonomous control of local power, and compares the influence of "cost", "rated power capacity" and "electrical distance" on the results of the game. By analysis, the rules are found that DGs with lower generation cost and greater rated power capacity has more opportunities to undertake load demand and the electrical distance could be ignored which will make the solution much easier and more efficient. The hierarchical structure of the whole system is described as the power grid, distribution network and Autonomous power units. The principle of RD algorithm is clear, and the fitness function is simple and efficient. Case study for IEEE test system proves the proposed algorithm and the game models are correct and reasonable.
Keywords :
costing; distributed power generation; energy conservation; game theory; multi-agent systems; optimisation; power control; power distribution economics; power generation economics; power generation scheduling; power system management; power system security; power system simulation; power system stability; DG penetration; IEEE test system; MAS; RD algorithm; autonomous power balance framework; autonomous power control; autonomous power unit; distribution network; electrical distance; energy efficiency; evolutionary game theory; load demand; local autonomous power control; mutiagent technology; optimization; power efficiency; power grid; power system management; rated power capacity; replicator dynamics algorithm; security; stability; Algorithm design and analysis; Games; Heuristic algorithms; Optimization; Power system dynamics; Power system stability; Resource management; MAS; Replicator Dynamics; autonomous power balance; electrical distance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power System Technology (POWERCON), 2014 International Conference on
Conference_Location :
Chengdu
Type :
conf
DOI :
10.1109/POWERCON.2014.6993593
Filename :
6993593
Link To Document :
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