Title :
Applying FFQ algorithm to implement the auxiliary regulation function of SMES in multi-area AGC system
Author_Institution :
Eng. Sci. & Technol., Shanghai Ocean Univ., Shanghai, China
Abstract :
Due to the influence of technology and management mechanism, it is difficult to implement the Automatic Generation Control (AGC) in multi-area power system. Distributed Artificial Intelligence (DAI) presents a novel idea for coordination optimization control of multi-area AGC. In this paper, quick response characteristic of Superconducting Magnetic Energy Storage (SMES) and coordination skill of Multi-Agent system (MAS) were used to regulate the active power balance and system frequency. MAS with Friend-or-Foe Q (FFQ) algorithm possess the skill to interact autonomously with other MAS, at the same times, it could consider not just in the benefit of itself but whole system. Moreover, coordination control between AGC generators and energy storage devices can be implemented. Simulation results show that MAS can be used to provide power support for multi area system, therefore frequency stability can be assured. Simultaneously, it is also benefit to make more available distribution of power energy among multi areas.
Keywords :
artificial intelligence; multi-agent systems; optimal control; optimisation; power generation control; superconducting magnet energy storage; AGC generators; DAI; FFQ algorithm; MAS; SMES; active power balance; automatic generation control; auxiliary regulation function; coordination optimization control; distributed artificial intelligence; energy storage devices; frequency stability; friend-or-foe Q algorithm; multiagent system; multiarea AGC system; multiarea power system; superconducting magnetic energy storage; Abstracts; Bismuth; Fluctuations; Stability analysis; AGC; FFQ; SMES; Smart Grid;
Conference_Titel :
Electricity Distribution (CICED), 2014 China International Conference on
Conference_Location :
Shenzhen
DOI :
10.1109/CICED.2014.6991807