Optimization of Unit Commitment Problem Using Genetic Algorithm

被引：4
|
作者：
Agarwal, Aniket [1 ]
Pal, Kirti [1 ]
机构：
[1] Gautam Buddha Univ, Greater Noida, India
来源：
INTERNATIONAL JOURNAL OF SYSTEM DYNAMICS APPLICATIONS | 2021年 / 10卷 / 03期
关键词：
Alternative Current Optimal Power Flow; Genetic Algorithm; IEEE 14 Bus System; MATPOWER; Power System Constraints; Renewable Sources; Solar Thermal Power Plant; Unit Commitment;
D O I：
10.4018/IJSDA.2021070102
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The main objective of the paper is to minimize the use of conventional generators and optimize the fuel cost. To minimize the use of conventional generators, solar thermal power plant (STPP) is proposed in this paper. An approach for optimal location of STPP is also proposed in this paper. To minimize the fuel cost, firstly unit commitment (UC) is applied in conventional generators. Then genetic algorithm (GA) is used to optimize the fuel cost of committed generators. The suggested method is tested on an IEEE 14 bus test system for 24 hr. schedule with variable load. The effectiveness of the proposed methodology is illustrated in three cases. Case 1 is used to identify the STPP location to reduce the fuel cost of conventional generator. In Case 2, unit-commitment is applied to save considerable fuel input and cost. In order to optimize the committed fuel cost, a genetic algorithm is applied in Case 3.
引用
收藏
页码：21 / 37
页数：17
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