Hydro-Thermal Scheduling Using Meta-Heuristic Optimization Techniques

被引：0
作者：
Mundotiya, Prahlad [1 ]
Mathuria, Parul [2 ]
Tiwari, H. P. [1 ]
机构：
[1] MNIT Jaipur, Dept Elect Engn, Jaipur, Rajasthan, India
[2] MNIT Jaipur, Ctr Energy & Environm, Jaipur, Rajasthan, India
来源：
2022 IEEE 10TH POWER INDIA INTERNATIONAL CONFERENCE, PIICON | 2022年
关键词：
Hydrothermal Scheduling; Economic Load Dispatch; Particle Swarm Optimization (PSO); PARTICLE SWARM OPTIMIZATION; ECONOMIC-DISPATCH PROBLEM; DETAILED SURVEY; LOAD; ALGORITHM; SYSTEM;
D O I：
10.1109/PIICON56320.2022.10045256
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
The scheduling of generating units faces many challenges. In addition, the non-linear behavior of the scheduling problem is still a challenge to determine the optimal solutions. Meta-heuristic optimization algorithm provides an approximate optimal solution for non-linear problems. In this paper, a modified particle swarm (MPSO) algorithm for hydrothermal scheduling has been proposed. The algorithm is developed on the quantum computing concept for the multi-objective economic dispatch considering emission issues. The effectiveness of the proposed algorithm has been analysed with 6 hydro-thermal units in two cases. In case 1 the 6 units are 2-hydro and 4-thermal and all the units in case 2 are considered thermal units. The computation cost of the proposed algorithm has been compared with the base particle swarm algorithm. A numerical analysis of the proposed algorithm shows that proposed algorithm has better performance than the base algorithm on the chosen problem.
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页数：6
相关论文
共 29 条
[1]   Solution of an Economic Dispatch Problem Through Particle Swarm Optimization: A Detailed Survey - Part II [J].
Abbas, Ghulam ;
Gu, Jason ;
Farooq, Umar ;
Raza, Ali ;
Asad, Muhammad Usman ;
El-Hawary, M. E. .
IEEE ACCESS, 2017, 5 :24426-24445
[2]   Solution of an Economic Dispatch Problem Through Particle Swarm Optimization: A Detailed Survey - Part I [J].
Abbas, Ghulam ;
Gu, Jason ;
Farooq, Umar ;
Asad, Muhammad Usman ;
El-Hawary, Mohamed .
IEEE ACCESS, 2017, 5 :15105-15141
[3]  
Affijulla Shaik, 2011, APPL SOFT COMPUT, V11, P2526
[4]   Solving economic emission load dispatch problems using hybrid differential evolution [J].
Bhattacharya, Aniruddha ;
Chattopadhyay, Pranab Kumar .
APPLIED SOFT COMPUTING, 2011, 11 (02) :2526-2537
[5]   A fuzzy adaptive chaotic ant swarm optimization for economic dispatch [J].
Cai, Jiejin ;
Li, Qiong ;
Li, Lixiang ;
Peng, Haipeng ;
Yang, Yixian .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2012, 34 (01) :154-160
[6]   Analysis of particle interaction in particle swarm optimization [J].
Chen, Ying-ping ;
Jiang, Pei .
THEORETICAL COMPUTER SCIENCE, 2010, 411 (21) :2101-2115
[7]   An improved harmony search algorithm for power economic load dispatch [J].
Coelho, Leandro dos Santos ;
Mariani, Viviana Cocco .
ENERGY CONVERSION AND MANAGEMENT, 2009, 50 (10) :2522-2526
[8]  
Dixit Gaurav Prasad, 2011, Proceedings of the International Conference on Sustainable Energy and Intelligent Systems (SEISCON 2011), P340, DOI 10.1049/cp.2011.0386
[9]   Implementation of APSO and Improved APSO on Non-Cascaded and Cascaded Short Term Hydrothermal Scheduling [J].
Fakhar, Muhammad Salman ;
Kashif, Syed Abdul Rahman ;
Liaquat, Sheroze ;
Rasool, Akhtar ;
Padmanaban, Sanjeevikumar ;
Iqbal, Muhammad Ahmad ;
Baig, Muhammad Anas ;
Khan, Baseem .
IEEE ACCESS, 2021, 9 :77784-77797
[10]   Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review [J].
Fakhar, Muhammad Salman ;
Liaquat, Sheroze ;
Kashif, Syed Abdul Rahman ;
Rasool, Akhtar ;
Khizer, Muhammad ;
Iqbal, Muhammad Ahmad ;
Baig, Muhammad Anas ;
Padmanaban, Sanjeevikumar .
IEEE ACCESS, 2021, 9 :25993-26025
123