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Multi-objective design under uncertainties of hybrid renewable energy system using NSGA-II and chance constrained programming
journal contribution
posted on 2023-06-09, 17:20 authored by Azadeh Kamjoo, Alireza Maheri, Arash Moradinegade DizqahArash Moradinegade Dizqah, Ghanim A PutrusThe 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.
History
Publication status
- Published
File Version
- Published version
Journal
International Journal of Electrical Power and Energy SystemsISSN
0142-0615Publisher
ElsevierExternal DOI
Volume
74Page range
187-194Department affiliated with
- Engineering and Design Publications
Research groups affiliated with
- Dynamics, Control and Vehicle Research Group Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2019-03-21First Compliant Deposit (FCD) Date
2019-03-20Usage metrics
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