Cascade Power Generation Cycle Optimization

버전 1.0.0.0 (2.86 MB) 작성자: Mohammad Daneshian
Single-Objective Genetic Algorithm (GA) Multi-Objective Genetic Algorithm (NSGA II)

다운로드 수: 185

업데이트 날짜: 2021/2/13

GitHub에서 호스트

GitHub에서 라이선스 보기

The overall efficiency and fuel usage of the whole system (objectives) are affected by extractions pressures (opt.vars). The thermodynamic states had been extracted by CoolProp toolbox in MATLAB.

First we had to specify the pressures in the way that maximizes the efficiency and then minimizes the fuel usage. This process is a single-objective optimization. After that, we had to optimize both objectives at the same time, which is a multi-objective optimization. For this process, we used NSGA (II) in MATLAB. The obtained Pareto front has been reported as the result.

P.S.: NSGA (II) is Non-dominated Sorting Genetic Algorithm (version 2) which is an evolutionary method. (Meta Heuristic)

인용 양식

Mohammad Daneshian (2022). Cascade Power Generation Cycle Optimization (https://github.com/thegreatmd4/Cascade_Power_Generation_Cycle_Optimization/releases/tag/1.0.0.0), GitHub. 검색됨 .

MATLAB 릴리스 호환 정보
개발 환경: R2019b
모든 릴리스와 호환
플랫폼 호환성
Windows macOS Linux
태그 태그 추가

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

MultiObjective

MultiObjective/+CoolProp

SingleObjective

SingleObjective/+CoolProp

이 GitHub 애드온의 문제를 보거나 보고하려면 GitHub 리포지토리로 가십시오.
이 GitHub 애드온의 문제를 보거나 보고하려면 GitHub 리포지토리로 가십시오.