An improved gravitational search algorithm for solving short-term economic/environmental hydrothermal scheduling

Verfasser / Beitragende:
[Hao Tian, Xiaohui Yuan, Yuehua Huang, Xiaotao Wu]
Ort, Verlag, Jahr:
2015
Enthalten in:
Soft Computing, 19/10(2015-10-01), 2783-2797
Format:
Artikel (online)
ID: 60546958X
LEADER caa a22 4500
001 60546958X
003 CHVBK
005 20210128100323.0
007 cr unu---uuuuu
008 210128e20151001xx s 000 0 eng
024 7 0 |a 10.1007/s00500-014-1441-3  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s00500-014-1441-3 
245 0 3 |a An improved gravitational search algorithm for solving short-term economic/environmental hydrothermal scheduling  |h [Elektronische Daten]  |c [Hao Tian, Xiaohui Yuan, Yuehua Huang, Xiaotao Wu] 
520 3 |a This paper proposes an improved gravitational search algorithm (IGSA) to find the optimum solution for short-term economic/environmental hydrothermal scheduling (SEEHTS), which considers minimizing fuel cost as well as minimizing pollutant emission. In order to improve the performance of GSA, this paper firstly uses particle memory character and population social information to update velocity. Secondly, a chaotic mutation operator is embedded into GSA and a selection-operator-based greedy rule is adopted to update population. When dealing with the constraints of the SEEHTS, a modification strategy by dividing the violation water volume into several parts and randomly selecting intervals to adjust the water discharge gradually is proposed to handle the water dynamic balance constraints. Meanwhile, a new symmetrical adjusting strategy is adopted to handle reservoir storage constraints. Furthermore, the priority index strategy based on thermal power output is applied to handle system load balance constraints. To test the performance of the proposed method, simulation results have been compared with those obtained by particle swarm optimization, evolutionary programming and differential evolution reported in literature. The results show that the proposed IGSA provides the optimum solution with less fuel cost and smaller emission. So it demonstrates that IGSA is effective for solving SEEHTS problem. 
540 |a Springer-Verlag Berlin Heidelberg, 2014 
690 7 |a Economic/environmental scheduling  |2 nationallicence 
690 7 |a Gravitational search algorithm  |2 nationallicence 
690 7 |a Constraints handling  |2 nationallicence 
690 7 |a Chaotic mutation  |2 nationallicence 
690 7 |a Priority index  |2 nationallicence 
700 1 |a Tian  |D Hao  |u School of Hydropower and Information Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China  |4 aut 
700 1 |a Yuan  |D Xiaohui  |u School of Hydropower and Information Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China  |4 aut 
700 1 |a Huang  |D Yuehua  |u College of Electrical Engineering and New Energy, China Three Gorges University, 443002, Yichang, China  |4 aut 
700 1 |a Wu  |D Xiaotao  |u School of Hydropower and Information Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China  |4 aut 
773 0 |t Soft Computing  |d Springer Berlin Heidelberg  |g 19/10(2015-10-01), 2783-2797  |x 1432-7643  |q 19:10<2783  |1 2015  |2 19  |o 500 
856 4 0 |u https://doi.org/10.1007/s00500-014-1441-3  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s00500-014-1441-3  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Tian  |D Hao  |u School of Hydropower and Information Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Yuan  |D Xiaohui  |u School of Hydropower and Information Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Huang  |D Yuehua  |u College of Electrical Engineering and New Energy, China Three Gorges University, 443002, Yichang, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Wu  |D Xiaotao  |u School of Hydropower and Information Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Soft Computing  |d Springer Berlin Heidelberg  |g 19/10(2015-10-01), 2783-2797  |x 1432-7643  |q 19:10<2783  |1 2015  |2 19  |o 500