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
下载
收藏
页码：1364 / +
页数：2
相关论文
共 50 条
  • [21] Dependability Evaluation of Parallel Differential Evolutionary Particle Swarm Optimization for Online Optimal Operational Planning of Energy Plants
    Nishimura, Norihiro
    Fukuyama, Yoshikazu
    Matsui, Tetsuro
    PROCEEDINGS OF THE 2016 IEEE REGION 10 CONFERENCE (TENCON), 2016, : 1204 - 1207
  • [22] Dependable Multi-population Differential Evolutionary Particle Swarm Optimization for Optimal Operational Planning of Energy Plants
    Nishimura, Norihiro
    Fukuyama, Yoshikazu
    Matsui, Tetsuro
    2017 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEM APPLICATION TO POWER SYSTEMS (ISAP), 2017,
  • [23] Optimal Multi-robot Path Planning Using Particle Swarm Optimization Algorithm Improved by Sine and Cosine Algorithms
    H. K. Paikray
    P. K. Das
    S. Panda
    Arabian Journal for Science and Engineering, 2021, 46 : 3357 - 3381
  • [24] Optimal Multi-robot Path Planning Using Particle Swarm Optimization Algorithm Improved by Sine and Cosine Algorithms
    Paikray, H. K.
    Das, P. K.
    Panda, S.
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2021, 46 (04) : 3357 - 3381
  • [25] Improved Particle Swarm Optimization using Evolutionary Algorithm
    Chansamorn, Sukanya
    Somgiat, Wichaya
    2022 19TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER SCIENCE AND SOFTWARE ENGINEERING (JCSSE 2022), 2022,
  • [26] APPLICATION OF PARTICLE SWARM OPTIMIZATION ALGORITHM FOR OPTIMAL REACTIVE POWER PLANNING
    Al-Hamouz, Z.
    Faisal, S. F.
    Al-Sharif, S.
    CONTROL AND INTELLIGENT SYSTEMS, 2007, 35 (01) : 66 - 72
  • [27] Path Planning Based on Improved Binary Particle Swarm Optimization Algorithm
    Zhang Qiaorong
    Gu Guochang
    Zhang Qiaorong
    2008 IEEE CONFERENCE ON ROBOTICS, AUTOMATION, AND MECHATRONICS, VOLS 1 AND 2, 2008, : 470 - +
  • [28] Application of Improved Particle Swarm Optimization Algorithm in UCAV Path Planning
    Ma, Qianzhi
    Lei, Xiujuan
    ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, PROCEEDINGS, 2009, 5855 : 206 - 214
  • [29] Time-Optimal Trajectory Planning of Industrial Robot based on Improved Particle Swarm Optimization Algorithm
    Shi, Buhai
    Xu, Jiaxiang
    PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE, 2020, : 3683 - 3688
  • [30] An improved particle swarm optimization algorithm for optimal placement and sizing of STATCOM
    Rocha, Luis
    Castro, Rui
    Ferreira de Jesus, J. M.
    INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, 2016, 26 (04): : 825 - 840
12345