Multi-Objective Differential Evolution for Design of Cascade Hydropower Reservoir Systems

J. Yazdi () and A. Moridi ()
Additional contact information
J. Yazdi: Shahid Beheshti University
A. Moridi: Shahid Beheshti University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2018, vol. 32, issue 14, No 19, 4779-4791

Abstract: Abstract After Paris Agreement and obligation made by various countries to decrease greenhouse gases, generation of clean energy with low carbon was taken into consideration. Hydropower plant is considered as a clean, cheap and renewable energy source for generating electrical energy. Through the construction of the multipurpose dams and their optimal planning and management, we may decrease the potential losses sustained by aquatic ecosystem in addition to supplying the energy and fulfilling the industrial, agricultural and drinking water demands. In the present study, a multi-objective optimization model was proposed for determination of design parameters in cascade hydropower multi-purpose reservoir systems. Considering the significant number of constraints and decision variables and non-convex form of the objective functions and constraints, particularly in multi-reservoir systems, a multi-objective evolutionary algorithm (MOEA) known as non-dominated sorting differential evolution (NSDE) was developed to solve the problem and reduce the computational costs. Karkheh River basin was selected as a case study in order to make an assessment on the capabilities and strength of the model. This basin is capable of generating hydropower energy and agricultural development with high environmental considerations due to Hurolazim International Wetland. Based on the results, we may supply various demands such as environmental demands of the aquatic ecosystem with high reliability as well as generating firm hydropower energy through optimal design of cascade hydropower reservoirs.

Keywords: Multi-purpose reservoir systems; Genetic algorithm; Firm energy; Meta heuristic algorithms; Optimization; Karkheh river basin (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
http://link.springer.com/10.1007/s11269-018-2083-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:32:y:2018:i:14:d:10.1007_s11269-018-2083-5

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11269

DOI: 10.1007/s11269-018-2083-5

Access Statistics for this article

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) is currently edited by G. Tsakiris

More articles in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) from Springer, European Water Resources Association (EWRA)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().