Optimal Sizing of a Hybrid Power System for Driving a Passenger Boat in Bangladesh

Author(s):  
Mohammad Abu Abdullah Al Mehedi ◽  
M. Tariq Iqbal
2013 ◽  
Vol 4 (3) ◽  
pp. 774-785 ◽  
Author(s):  
Lin Xu ◽  
Xinbo Ruan ◽  
Chengxiong Mao ◽  
Buhan Zhang ◽  
Yi Luo

2013 ◽  
Vol 5 (5) ◽  
pp. 053141 ◽  
Author(s):  
Seyed Mahdi Moosavian ◽  
Mostafa Modiri-Delshad ◽  
Nasrudin Abd Rahim ◽  
Jeyraj Selvaraj

2019 ◽  
Vol 13 (15) ◽  
pp. 3354-3361 ◽  
Author(s):  
Matthew Combe ◽  
Amin Mahmoudi ◽  
Mohammed H. Haque ◽  
Rahmat Khezri

2015 ◽  
Vol 64 (1) ◽  
pp. 139-155 ◽  
Author(s):  
T. Bogaraj ◽  
J. Kanakaraj ◽  
K. Mohan Kumar

Abstract This paper presents the optimal sizing of PV/Wind/Fuel Cell/Battery Hybrid Energy System for energizing a Small Scale Industrial Application or a village domestic load of 200 kW. HOMER software is used for simulation of the complete system. The solar radiation data and wind speed data used in this paper are for the place of Coimbatore, Tamil Nadu, India which is located 11.0183° N longitude and 76.9725° E latitude. The optimized sizes of components of Hybrid Power System (HPS) are found based on Levelised Cost of Energy (LCE) and total Net Present Cost (NPC). The results are presented and compared for five different combinations of HPS components. Suggestions are also presented to choose the low cost system which produces energy at low LCE.


2013 ◽  
Vol 694-697 ◽  
pp. 2699-2703 ◽  
Author(s):  
Shi Qiong Zhou ◽  
Gui Fang Guo ◽  
Yong Yang Xiang

In a solar electric vehicle, the optimal sizing of hybrid power system can be considered as a multi-objective optimization problem. The two conflicting goals are to maximize the Loss of Peak Power Probability (LPPP) and minimize the system cost. And the former is related to the reliability of the system while the latter relates to whether production prototype so the two optimization objectives are important. An improved particle swarm algorithm was presented to optimal size the hybrid power system. Here the mutation operator of genetic algorithm was introduced and the acceleration factor could change with time. The optimization results show that: the improved particle swarm algorithm can well solve the hybrid power system for multi-objective optimization problems.


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