Gbest guided artificial bee colony algorithm for environmental/economic dispatch considering wind power

被引:82
作者
Jadhav, H. T. [1 ]
Roy, Ranjit [1 ]
机构
[1] SV Natl Inst Technol, Dept Elect Engn, Surat, India
关键词
Carbon tax; Gbest guided artificial bee colony; Multi-objective emission economic load dispatch; Weibull probability distribution function; Wind power; PARTICLE SWARM OPTIMIZATION; DYNAMIC ECONOMIC-DISPATCH; GROUP SEARCH OPTIMIZER; DIFFERENTIAL EVOLUTION; GENETIC ALGORITHM; UNIT COMMITMENT; GENERATION; OPERATION; STRATEGY; MODEL;
D O I
10.1016/j.eswa.2013.05.048
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The current energy consumption in most of the countries is weighing heavily on fossil fuels, which account for about 70-90% of total energy used. The ecological concerns about air pollution and global warming are encouraging wider use of clean renewable technologies such as wind and solar energy. In this paper, Gbest guided artificial bee colony algorithm (GABC) is applied to optimize the emission and overall cost of operation of wind-thermal power system. The random nature of wind power is modeled using weibull probability distribution function (PDF). Moreover, the uncertainty in wind power is considered in the cost model by including the power imbalance terms such as overestimation and underestimation costs of available wind power. To validate the effectiveness of proposed method, it is first applied to three standard test systems considering different technical constraints such as valve loading effect, prohibited zones, ramp rate limits, etc. In second part, the effect of wind power generation on dispatch cost and emission is analyzed for IEEE-30 bus test system. A comparative analysis with other similar optimization techniques reveals that the proposed technique has better solution accuracy and convergence results. (c) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:6385 / 6399
页数:15
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