generation expansion planning;
CO2 emission constraint and improved tabu search;
D O I:
暂无
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
This paper presents a development of Improved Tabu Search (ITS) and its application to a least-cost Generation Expansion Planning (GEP) including biomass energy sources under global environmental impact consideration. A carbon tax is taken into account as countermeasure to reduce CO2 emission for introducing and promoting biomass energies to GEP problem based conventional fossil-fuel plants. The proposed ITS is conducted by the proposed a self-reforming candidate list strategies to improve search performance of a standard TS. The ITS approach is applied to the test system with 15 existing power plants, 5 types of conventional fossil-fuel and 2 types of biomass energy over a 14-year planning period. The simulation results reveal that the proposed ITS not only can yield optimal solution as well as dynamic programming, but also can remarkably reduce computational time. Moreover, the proposed method provides better solution superior to a standard tabu search with promising results.