A Novel Binary Ant Colony Optimization: Application to the Unit Commitment Problem of Power Systems

被引：22

作者：

Jang, Se-Hwan ^{[1
]}

Roh, Jae Hyung ^{[1
]}

Kim, Wook ^{[2
]}

Sherpa, Tenzi ^{[1
]}

Kim, Jin-Ho ^{[3
]}

Park, Jong-Bae ^{[1
]}

机构：

[1] Konkuk Univ, Dept Elect Engn, Seoul, South Korea

[2] Korea So Power Co, Seoul, South Korea

[3] Kyungwon Univ, Dept Elect Engn, Songnam, South Korea

来源：

JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY | 2011年 / 6卷 / 02期

关键词：

Binary ant colony optimization; Combinatorial optimization; Unit commitment; Swarm intelligence; ALGORITHM;

D O I：

10.5370/JEET.2011.6.2.174

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper proposes a novel binary ant colony optimization (NBACO) method. The proposed NBACO is based on the concept and principles of ant colony optimization (ACO), and developed to solve the binary and combinatorial optimization problems. The concept of conventional ACO is similar to Heuristic Dynamic Programming. Thereby ACO has the merit that it can consider all possible solution sets, but also has the demerit that it may need a big memory space and a long execution time to solve a large problem. To reduce this demerit, the NBACO adopts the state probability matrix and the pheromone intensity matrix. And the NBACO presents new updating rule for local and global search. The proposed NBACO is applied to test power systems of up to 100-unit along with 24-hour load demands.

引用

页码：174 / 181

页数：8

共 50 条

[21] Ant colony system based unit-commitment problem with Gaussian load distribution
Simon, S. P.
Padhy, N. P.
Anand, R. S.
2006 POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS 1-9, 2006, : 332 - +
[22] Ant colony optimization algorithm with random perturbation behavior to the problem of optimal unit commitment with probabilistic spinning reserve determination
Shi, LB
Hao, J
Zhou, JQ
Xu, GY
ELECTRIC POWER SYSTEMS RESEARCH, 2004, 69 (2-3) : 295 - 303
[23] Scalable unit commitment by memory-bounded ant colony optimization with A* local search
Saber, Ahmed Yousuf
Alshareef, Abdulaziz Mohammed
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2008, 30 (6-7) : 403 - 414
[24] An Improved Ant Colony Optimization and Its Application on TSP Problem
Luo, Wei
Lin, Dong
Feng, Xinxin
2016 IEEE INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA), 2016, : 136 - 141
[25] Application of An improved Ant Colony Optimization on Multicast Routing Problem
Liu Yanchun
Xu Zhendong
Yang Bo
Zhang Yi
2009 INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION SYSTEMS AND APPLICATIONS, PROCEEDINGS, 2009, : 592 - 595
[26] Unit commitment Using the Ant Colony Search Algorithm
Sisworahardjo, NS
El-Keib, AA
LESCOPE'02: 2002 LARGE ENGINEERINGS SYSTEMS CONFERENCE ON POWER ENGINEERING, CONFERENCE PROCEEDINGS, 2002, : 2 - 6
[27] A Novel Hybrid Ant Colony Optimization for a Multicast Routing Problem
Zhang, Xiaoxia
Shen, Xin
Yu, Ziqiao
ALGORITHMS, 2019, 12 (01)
[28] The fault diagnosis inverse problem with Ant Colony Optimization and Ant Colony Optimization with dispersion
Camps Echevarria, Lidice
de Campos Velho, Haroldo Fraga
Becceneri, Jose Carlos
da Silva Neto, Antonio Jose
Llanes Santiago, Orestes
APPLIED MATHEMATICS AND COMPUTATION, 2014, 227 : 687 - 700
[29] An Ant Colony Optimization Approach for the Dominating Tree Problem
Sundar, Shyam
Chaurasia, Sachchida Nand
Singh, Alok
SWARM, EVOLUTIONARY, AND MEMETIC COMPUTING (SEMCCO 2015), 2016, 9873 : 143 - 153
[30] Application of Negative Learning Ant Colony Optimization to the Far from Most String Problem
Blum, Christian
Pinacho-Davidson, Pedro
EVOLUTIONARY COMPUTATION IN COMBINATORIAL OPTIMIZATION, EVOCOP 2023, 2023, 13987 : 82 - 97

← 1 2 3 4 5 →