Transmission Expansion Planning Using TLBO Algorithm in the Presence of Demand Response Resources

被引：23
|
作者：
Zakeri, Amir Sadegh [1 ]
Abyaneh, Hossein Askarian [1 ]
机构：
[1] Amirkabir Univ Technol, Tehran Polytech, 424 Hafez Ave, Tehran 1591634311, Iran
来源：
ENERGIES | 2017年 / 10卷 / 09期
关键词：
transmission expansion planning; demand response program; TLBO; elasticity; SENSITIVITY-ANALYSIS; DC MODEL; OPTIMIZATION; CONSTRAINTS;
D O I：
10.3390/en10091376
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
Transmission Expansion Planning (TEP) involves determining if and how transmission lines should be added to the power grid so that the operational and investment costs are minimized. TEP is a major issue in smart grid development, where demand response resources affect short- and long-term power system decisions, and these in turn, affect TEP. First, this paper discusses the effects of demand response programs on reducing the final costs of a system in TEP. Then, the TEP problem is solved using a Teaching Learning Based Optimization (TLBO) algorithm taking into consideration power generation costs, power loss, and line construction costs. Simulation results show the optimal effect of demand response programs on postponing the additional cost of investments for supplying peak load.
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页数：15
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