Reduction of Fuel Consumption in PV / Diesel Hybrid Power Generation System by Dynamic Programming Combined With Genetic Algorithm

2006 ◽  
Author(s):  
Shinji Wakao ◽  
Keigo Nakao
Keyword(s):  
Genetic Algorithm ◽  
Power Generation ◽  
Dynamic Programming ◽  
Fuel Consumption ◽  
Generation System ◽  
Hybrid Power ◽  
Power Generation System

scholarly journals Metaheuristic searching genetic algorithm based reliability assessment of hybrid power generation system

2020 ◽  
pp. 014459872095974
Author(s):  
Ahmed N Abdalla ◽  
Muhammad Shahzad Nazir ◽  
MingXin Jiang ◽  
Athraa Ali Kadhem ◽  
Noor Izzri Abdul Wahab ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Power Generation ◽  
Solar Energy ◽  
Computation Time ◽  
Test System ◽  
Optimization Approach ◽  
Generation System ◽  
Power Sources ◽  
Hybrid Power ◽  
Power Generation System

Generating systems are known as adequately reliable when satisfying the load demand. Meanwhile, the efficiency of electrical systems is currently being more influenced by the growing adoption of the Wind/Solar energy in power systems compared to other conventional power sources. This paper proposed a new optimization approach called Metaheuristic Scanning Genetic Algorithm (MSGA) for the evaluation of the efficiency of power generating systems. The MSGA is based on a combination of metaheuristic scanning and Genetic Algorithm. The MSGA technique is used for evaluating the reliability and adequacy of generation systems integrated with wind/Solar energy is developed. The usefulness of the proposed algorithm was tested using Reliability Test System ‘IEEE-RTS-79’ which include both of wind power and solar power generation. The result approve the effectiveness of the proposed algorithm in improving the computation time by 85% and 2% in comparison with the particle swarm optimization (PSO) and differential evolution optimization algorithm (DEOA) respectively. In addition, the proposed model can be used to test the power capacity forecasting scheme of the hybrid power generation system with the wind, solar and storage.

An operating method using prediction of photovoltaic power for a photovoltaic-diesel hybrid power generation system

2005 ◽  
Vol 151 (3) ◽  
pp. 8-18 ◽  
Author(s):  
Shigehiro Yamamoto ◽  
Kazuyoshi Sumi ◽  
Eiichi Nishikawa ◽  
Takeshi Hashimoto
Keyword(s):  
Power Generation ◽  
Generation System ◽  
Hybrid Power ◽  
Photovoltaic Power ◽  
Power Generation System ◽  
Operating Method

scholarly journals Multi-objective optimization of solar thermal photovoltaic hybrid power generation system based on NSGA-II algorithm

2021 ◽  
Vol 336 ◽  
pp. 02022
Author(s):  
Liang Meng ◽  
Wen Zhou ◽  
Yang Li ◽  
Zhibin Liu ◽  
Yajing Liu
Keyword(s):  
Power Generation ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Solar Thermal ◽  
Multi Objective Optimization ◽  
Generation System ◽  
Nsga Ii ◽  
Multi Objective ◽  
Hybrid Power ◽  
Power Generation System

In this paper, NSGA-Ⅱ is used to realize the dual-objective optimization and three-objective optimization of the solar-thermal photovoltaic hybrid power generation system; Compared with the optimal solution set of three-objective optimization, optimization based on technical and economic evaluation indicators belongs to the category of multi-objective optimization. It can be considered that NSGA-Ⅱ is very suitable for multi-objective optimization of solar-thermal photovoltaic hybrid power generation system and other similar multi-objective optimization problems.

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