Sustainability Indicator of Renewable Energy System Based on Fuzzy Multi-Criteria Decision Making Methods

2011 ◽  
Vol 361-363 ◽  
pp. 1263-1273 ◽  
Author(s):  
Gang Liu ◽  
M. G. Rasul ◽  
M. T. O. Amanullah ◽  
M. M. K. Khan
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Energy System ◽  
Fuzzy Decision Making ◽  
Solar Pv ◽  
Sustainability Indicator ◽  
Renewable Energy System ◽  
General Indicator

Sustainability measurement of renewable energy system is complex, as is the system itself. The study proposes a general indicator to evaluate sustainability of a renewable energy system. In order to comprehensively assess the environmental, economic and social sustainability, eleven indicators with different dimensions are quantified and aggregated into a general indicator of sustainability (GIS) based on fuzzy decision making methods, such as fuzzy analytic hierarchy processing and fuzzy comprehensive evaluation. The developed GIS is able to provide numerical results of sustainability for a renewable energy system. A case of a renewable energy system in Australia are presented to explain the application of the sustainability indicator. In terms of the four different combinations of grid, solar PV and wind renewable energy, the developed GIS is used to assess their sustainability.

scholarly journals Development of a General Hybridized Optimization Model for Biogas and Solar PV Renewable Energy System Designs

2018 ◽  
Vol 3 (5) ◽  
pp. 82
Author(s):  
Ganiyu Adedayo Ajenikoko ◽  
T. O. Araoye ◽  
O. O. Aguda ◽  
S. F. Owolabi ◽  
A. O. Olushola
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Hybrid System ◽  
Optimization Model ◽  
Energy System ◽  
Total Power ◽  
Solar Pv ◽  
Renewable Energy System ◽  
Biogas Energy ◽  
Electrical Generation

Hybrid biogas/solar renewable energy system is an electricity production system made up of combination of biogas and solar energy. This hybrid is considered to be best module because it is abundant and environmentally friendly due to the limited reserves of fossil fuels and global environmental concerns for the production of electrical power generation and utilization. This paper develops a general hybridized optimization model for biogas/solar system for electrical generation of Ade-Oyo in Ibadan, Oyo State. In this paper, a pig dug was used to prepare the digester materials for biogas energy while a Shockley diode principle was used for PV power model. Simulation was carried out using MATLAB software and the total power for the hybrid system is formulated. The result revealed that the total power generated by biogas/solar hybrid system is the addition of the power generated by the biogas energy and solar PV panel and is given as: . The result shows that that there is a positive relationship between the electrical energy/power generated with biogas/solar energy. This paper will be helpful in demonstrating the viability of biogas/solar energy for rural communities and remote areas

scholarly journals Evolutionary Algorithms based AGA and BPSO Computing for Hybrid Renewable Energy System

2020 ◽  
Vol 8 (5) ◽  
pp. 3348-3352
Keyword(s):  
Renewable Energy ◽  
Evolutionary Algorithm ◽  
Pid Controller ◽  
Energy System ◽  
Energy Sources ◽  
Adaptive Genetic Algorithm ◽  
Solar Pv ◽  
Hybrid Renewable Energy System ◽  
Renewable Energy System ◽  
Hybrid Renewable Energy

Solar and wind Renewable system have more advantages compared to Conventional energy sources and it is environment friendly and also from economic point of view...For overcoming the problems of Conventional Energy sources, this paper proposed an hybrid renewable energy system using Different evolutionary algorithm approaches. This proposed method hybrids the three systems namely, solar PV, wind and Fuel Cell which have the biggest potential to provide power. The battery and loads are also integrated with this hybrid system. Then, the charging and discharging of this system is controlled by an Optimized PID controller for balancing the generated power and load power. Here, the PID controller works based on the rules to provide an efficient system. Also, the tuning parameters of the PID controller are enhanced by Adaptive Genetic Algorithm and Particle Swarm Optimization. Finally, the performance of the Combined Solar and wind system is tunedwith the Evolutionary algorithm based PID controller and is compared with the existing hybrid renewable systems based on Generated Power, Load side Power, Speed Controller and Torque.

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