Constrained gravitational search algorithm for large scale reservoir operation optimization problem. (June 2017)

• Record Type: Journal Article
• Authors: Moeini, R.; Soltani-nezhad, M.; Daei, M.
• Is Part Of: Engineering applications of artificial intelligence. Volume 62(2017:Feb.)
• Page Start: 222
• Page End: 233
• Publication Date: 2017-06
• Subjects: Evolutionary algorithm -- Optimal operation of reservoir -- Gravitational search algorithm -- Explicitly constraints handling -- Water releases -- Storage volumes; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2017.04.012
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: The gravitational search algorithm (GSA) is used in this paper to solve large scale reservoir operation optimization problem. Here, two constrained versions of GSA are proposed to solve this problem in which masses may be forced to satisfy problem constraints during solution building. This approach is very useful when attempting to solve large scale optimization problem as it will lead to a considerable reduction of the search space size. Here, in the second version of GSA, the storage volume bounds of the reservoir are modified prior to the main search to recognize the infeasible components of the search space and exclude from the search process before the main search starts. Two formulations are also proposed here for each proposed algorithm considering water releases or storage volumes at each operation time period as decision variable of the problem. Proposed algorithms are used to solve the simple and hydropower operation problem of "Dez" reservoir in Iran and the results are presented and compared with using original form of the GSA and any available results. The results indicate the ability of the proposed algorithm and especially the second constrained version of GSA to optimally solve the reservoir operation optimization problem. Highlights: Gravitational search algorithm (GSA) is used to solve reservoir operation problem. Constrained version of GSA is proposed here to satisfy problem constraints. Constrained GSA leads to a considerable reduction of the search space size. Water release or storage volume at each period are decision variable of the problem. The simple and hydropower operation problem of "Dez" reservoir in Iran are solved.