Transmission Congestion Control Research in Power System Based on Immune Genetic Algorithm
This paper investigates the cost control problem of congestion management model in the real-time power systems. An improved optimal congestion cost model is built by introducing the congestion factor in dealing with the cases: opening the generator side and load side simultaneously. The problem of real-time congestion management is transformed to a nonlinear programming problem. While the transmission congestion is maximum the adjustment cost is minimum based on the immune genetic algorithm, and the global optimal solution is obtained. Simulation results show that the improved optimal model can obviously reduce the adjustment cost and the designed algorithm is safe and easy to implement.
Electricity Systems Congestion Management Immune Genetic Algorithm Minimax Adjustment Cost
LIU Bin JIANG Nan LIU Ting JING Yuanwei
Faculty of Information Science and Engineering, Northeastern University, Shenyang 110819
国际会议
The 31st Chinese Control Conference(第三十一届中国控制会议)
合肥
英文
7487-7492
2012-07-01（万方平台首次上网日期，不代表论文的发表时间）