Title
An improved gravitational search algorithm for solving short-term economic/environmental hydrothermal scheduling.
Abstract
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.
Year
DOI
Venue
2015
10.1007/s00500-014-1441-3
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Keywords
Field
DocType
Economic/environmental scheduling, Gravitational search algorithm, Constraints handling, Chaotic mutation, Priority index
Hydrothermal scheduling,Mathematical optimization,Computer science,Gravitational search algorithm
Journal
Volume
Issue
ISSN
19
10
1433-7479
Citations 
PageRank 
References 
3
0.39
16
Authors
4
Name
Order
Citations
PageRank
Hao Tian1141.03
Xiao-Hui Yuan253475.44
Yuehua Huang320713.11
Xiaotao Wu461.45