Title :
Optimisation of inverter placement for mass rapid transit systems by immune algorithm
Author_Institution :
Dept. of Electr. Eng., Kao Yuan Inst. of Technol., Lu-Chu Taiwan, Taiwan
Abstract :
Optimal inverter substation planning is solved by minimising the overall cost of power consumption and inverter investment for mass rapid transit power systems with immune algorithm (IA). The objective function and constraints are expressed as antigens, and all feasible solutions are expressed as antibodies in the IA simulation process. The diversity of antibodies is then enhanced by considering the proximity of antigens so that the global optimisation during the solution process can be obtained. It is found that energy regeneration, which results from the braking operation of train sets approaching the next station, can be restored effectively by the optimal planning of inverters using the proposed immune algorithm.
Keywords :
cost reduction; invertors; investment; optimisation; power consumption; railway electrification; rapid transit systems; regenerative braking; substations; IA; IA simulation process; antibodies diversity; energy regeneration; immune algorithm; inverter investment; inverter placement; mass rapid transit power system; objective constraint; objective function; optimal inverter substation planning; optimisation; overall cost minimisation; power consumption; train set braking operation;
Journal_Title :
Electric Power Applications, IEE Proceedings -
DOI :
10.1049/ip-epa:20041143