Multi-objective design under uncertainties of hybrid renewable energy system using NSGA-II and chance constrained programming

Kamjoo, Azadeh, Maheri, Alireza, Dizqah, Arash M and Putrus, Ghanim A (2016) Multi-objective design under uncertainties of hybrid renewable energy system using NSGA-II and chance constrained programming. International Journal of Electrical Power and Energy Systems, 74. pp. 187-194. ISSN 0142‐0615

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Abstract

The optimum design of Hybrid Renewable Energy Systems (HRES) depends on different economical, environmental and performance related criteria which are often conflicting objectives. The Non-dominated Sorting Genetic Algorithm (NSGA-II) provides a decision support mechanism in solving multi-objective problems and providing a set of non-dominated solutions where finding an absolute optimum solution is not possible. The present study uses NSGA-II algorithm in the design of a standalone HRES comprising wind turbine, PV panel and battery bank with the (economic) objective of minimum system total cost and (performance) objective of maximum reliability. To address the uncertainties in renewable resources (wind speed and solar irradiance), an innovative method is proposed which is based on Chance Constrained Programming (CCP). A case study is used to validate the proposed method, where the results obtained are compared with the conventional method of incorporating uncertainties using Monte Carlo simulation.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Research Centres and Groups: Dynamics, Control and Vehicle Research Group
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA0168 Systems engineering
T Technology > TA Engineering (General). Civil engineering (General) > TA0174 Engineering design
Depositing User: Arash Moradinegade Dizqah
Date Deposited: 21 Mar 2019 10:51
Last Modified: 21 Mar 2019 10:51
URI: http://srodev.sussex.ac.uk/id/eprint/82678

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