Optimal operational planning of utility systems in petrochemical plants using an improved particle swarm optimization algorithm

被引：0
|
作者：
Dai, Wenzhi [1 ,2 ]
Huo, Zhaoyi [2 ]
Yin, Hongchao [2 ]
Liang, Haifeng [3 ]
机构：
[1] Liaoning Tech Univ, Sch Mech Engn, Fuxin 123000, Peoples R China
[2] Dalian Univ Technol, Dept Energy & Power Engn, Dalian 116023, Peoples R China
[3] Taiyuan Univ Technol, Taiyuan 030024, Peoples R China
来源：
SMART MATERIALS AND INTELLIGENT SYSTEMS, PTS 1 AND 2 | 2011年 / 143-144卷
关键词：
Utility Systems; Improved Particle Swarm Optimization; Energy Conservation;
D O I：
10.4028/www.scientific.net/AMR.143-144.1364
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 paper, the operation optimization problem for utility systems is formulated and a mixed integer linear program (MILP) model is presented. The objective function of the model is to minimize the operational cost of utility systems during the whole operational period. In order to obtain the optimal solution of the foregoing model, an improved particle swarm optimization is proposed. Finally, a case with quantitive results presented is considered for illustrating the advantage of proposed optimization approach. Results show that the new algorithms are much more efficient than some existing particle swarm optimization algorithms.
引用
收藏
页码：1364 / +
页数：2
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