Optimal Bidding Strategy in Deregulated Power Market Using Krill Herd Algorithm

被引：6
|
作者：
Karri, Chandram [1 ]
Rajababu, Durgam [1 ]
Raghuram, K. [2 ]
机构：
[1] SR Engn Coll, Dept Elect & Elect Engn, Warangal, Telangana, India
[2] Laqkya Inst Technol & Sci, Khammam, India
来源：
APPLICATIONS OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN ENGINEERING, SIGMA 2018, VOL 1 | 2019年 / 698卷
关键词：
Bidding strategy; Krill herd algorithm; Deregulation; OPTIMIZATION;
D O I：
10.1007/978-981-13-1819-1_5
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this article, Krill Herd algorithm (KHA) is implemented for optimal bidding strategy. The bidding coefficients of suppliers and buyers are selected strategically. The code of proposed KHA has been developed in MATLAB. It has been tested on IEEE 30 bus power system. The simulation results are correlated with the existing algorithms. The results proved flexibility of KHA correlated with Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Monte Carlo simulation in terms of Market Clearing Price (MCP).
引用
收藏
页码：43 / 51
页数：9
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