Techno-economic and environmental assessment of a hybrid renewable energy system using multi-objective genetic algorithm: A case study for remote Island in Bangladesh

•Hybrid solar, wind, biogas with vanadium redox flow battery-based system is studied.•Cost and life cycle emissions are optimised by multi-objective genetic algorithm.•Multi-objective provides better environmental benefits than single objective one.•Evolutionary algorithm offers cost-effective solut...

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Vydáno v:	Energy conversion and management Ročník 230; s. 113823
Hlavní autoři:	Das, Barun K., Hassan, Rakibul, Tushar, Mohammad Shahed H.K., Zaman, Forhad, Hasan, Mahmudul, Das, Pronob
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford Elsevier Ltd 15.02.2021 Elsevier Science Ltd
Témata:	Algorithms Alternative energy sources Bangladesh batteries Biogas Carbon dioxide case studies Comparative analysis Computer programs computer software Cost of energy Decision making ecosystem services Electricity electricity costs Emissions energy conversion Energy resources Energy sources Environmental assessment Evolutionary algorithms flow French West Indies Genetic algorithms Hybrid systems hybrids Life cycle emissions Life cycles Multiple objective analysis Objective function Optimization Photovoltaic cells Photovoltaics probability Rechargeable batteries Reliability Renewable energy Software Software development tools solar collectors Sorting algorithms supply Supplying Turbines Vanadium Wind power Wind turbines Bangladesh French West Indies Renewable energy Cost of energy Reliability Life cycle emissions
ISSN:	0196-8904, 1879-2227
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Abstract	•Hybrid solar, wind, biogas with vanadium redox flow battery-based system is studied.•Cost and life cycle emissions are optimised by multi-objective genetic algorithm.•Multi-objective provides better environmental benefits than single objective one.•Evolutionary algorithm offers cost-effective solutions than the software tool.•Electricity cost is comparable with the grid supply at the cost of reliability. Renewable hybrid energy systems are well-proven to be capable of supplying reliable power in the remote areas, where grid extension is not viable due to geographical constraints, but not absolutely emissions free. The present study investigates a hybrid energy system that entails photovoltaic module, wind turbine, biogas generator, and vanadium redox flow battery for supplying stable power to a remote Island, Saint Martin, Bangladesh. Two well-known multi-objective optimisation techniques such as non-dominated sorting genetic algorithm II and infeasibility driven evolutionary algorithm are applied to size the hybrid system components based on the cost of energy ($/kWh) and life cycle emissions (kg CO2-eq/yr) under a certain reliability. In addition, a fuzzy decision-making technique is applied to find the optimal solution. A comparative analysis of using single objective function is compared with the multi-objective one. In addition, results from the non-dominated sorting genetic algorithm II optimisation technique is compared with the widely utilized software hybrid optimisation of multiple energy resources tool and the infeasibility driven evolutionary algorithm. Although the cost of energy is relatively comparable between the objective functions considered, the multi-objective approach provides better environmental benefits than the single objective optimisation system. The analyzed results also indicate that the intelligent techniques are the superior to the hybrid optimisation of multiple energy resources software tool in terms of costs and environmental point of view. Furthermore, the unit electricity cost of the proposed hybrid system configuration is comparable with the grid electricity supply at the loss of power supply probability of over 8% with significantly lower life cycle emissions.
AbstractList	Renewable hybrid energy systems are well-proven to be capable of supplying reliable power in the remote areas, where grid extension is not viable due to geographical constraints, but not absolutely emissions free. The present study investigates a hybrid energy system that entails photovoltaic module, wind turbine, biogas generator, and vanadium redox flow battery for supplying stable power to a remote Island, Saint Martin, Bangladesh. Two well-known multi-objective optimisation techniques such as non-dominated sorting genetic algorithm II and infeasibility driven evolutionary algorithm are applied to size the hybrid system components based on the cost of energy ($/kWh) and life cycle emissions (kg CO₂-eq/yr) under a certain reliability. In addition, a fuzzy decision-making technique is applied to find the optimal solution. A comparative analysis of using single objective function is compared with the multi-objective one. In addition, results from the non-dominated sorting genetic algorithm II optimisation technique is compared with the widely utilized software hybrid optimisation of multiple energy resources tool and the infeasibility driven evolutionary algorithm. Although the cost of energy is relatively comparable between the objective functions considered, the multi-objective approach provides better environmental benefits than the single objective optimisation system. The analyzed results also indicate that the intelligent techniques are the superior to the hybrid optimisation of multiple energy resources software tool in terms of costs and environmental point of view. Furthermore, the unit electricity cost of the proposed hybrid system configuration is comparable with the grid electricity supply at the loss of power supply probability of over 8% with significantly lower life cycle emissions. •Hybrid solar, wind, biogas with vanadium redox flow battery-based system is studied.•Cost and life cycle emissions are optimised by multi-objective genetic algorithm.•Multi-objective provides better environmental benefits than single objective one.•Evolutionary algorithm offers cost-effective solutions than the software tool.•Electricity cost is comparable with the grid supply at the cost of reliability. Renewable hybrid energy systems are well-proven to be capable of supplying reliable power in the remote areas, where grid extension is not viable due to geographical constraints, but not absolutely emissions free. The present study investigates a hybrid energy system that entails photovoltaic module, wind turbine, biogas generator, and vanadium redox flow battery for supplying stable power to a remote Island, Saint Martin, Bangladesh. Two well-known multi-objective optimisation techniques such as non-dominated sorting genetic algorithm II and infeasibility driven evolutionary algorithm are applied to size the hybrid system components based on the cost of energy ($/kWh) and life cycle emissions (kg CO2-eq/yr) under a certain reliability. In addition, a fuzzy decision-making technique is applied to find the optimal solution. A comparative analysis of using single objective function is compared with the multi-objective one. In addition, results from the non-dominated sorting genetic algorithm II optimisation technique is compared with the widely utilized software hybrid optimisation of multiple energy resources tool and the infeasibility driven evolutionary algorithm. Although the cost of energy is relatively comparable between the objective functions considered, the multi-objective approach provides better environmental benefits than the single objective optimisation system. The analyzed results also indicate that the intelligent techniques are the superior to the hybrid optimisation of multiple energy resources software tool in terms of costs and environmental point of view. Furthermore, the unit electricity cost of the proposed hybrid system configuration is comparable with the grid electricity supply at the loss of power supply probability of over 8% with significantly lower life cycle emissions. Renewable hybrid energy systems are well-proven to be capable of supplying reliable power in the remote areas, where grid extension is not viable due to geographical constraints, but not absolutely emissions free. The present study investigates a hybrid energy system that entails photovoltaic module, wind turbine, biogas generator, and vanadium redox flow battery for supplying stable power to a remote Island, Saint Martin, Bangladesh. Two well-known multi-objective optimisation techniques such as non-dominated sorting genetic algorithm II and infeasibility driven evolutionary algorithm are applied to size the hybrid system components based on the cost of energy ($/kWh) and life cycle emissions (kg CO2-eq/yr) under a certain reliability. In addition, a fuzzy decision-making technique is applied to find the optimal solution. A comparative analysis of using single objective function is compared with the multi-objective one. In addition, results from the non-dominated sorting genetic algorithm II optimisation technique is compared with the widely utilized software hybrid optimisation of multiple energy resources tool and the infeasibility driven evolutionary algorithm. Although the cost of energy is relatively comparable between the objective functions considered, the multi-objective approach provides better environmental benefits than the single objective optimisation system. The analyzed results also indicate that the intelligent techniques are the superior to the hybrid optimisation of multiple energy resources software tool in terms of costs and environmental point of view. Furthermore, the unit electricity cost of the proposed hybrid system configuration is comparable with the grid electricity supply at the loss of power supply probability of over 8% with significantly lower life cycle emissions.
ArticleNumber	113823
Author	Hasan, Mahmudul Zaman, Forhad Hassan, Rakibul Das, Pronob Das, Barun K. Tushar, Mohammad Shahed H.K.
Author_xml	– sequence: 1 givenname: Barun K. surname: Das fullname: Das, Barun K. email: bkdas@me.ruet.ac.bd organization: Department of Mechanical Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh – sequence: 2 givenname: Rakibul surname: Hassan fullname: Hassan, Rakibul organization: Department of Mechanical Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh – sequence: 3 givenname: Mohammad Shahed H.K. surname: Tushar fullname: Tushar, Mohammad Shahed H.K. organization: Department of Mechanical Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh – sequence: 4 givenname: Forhad surname: Zaman fullname: Zaman, Forhad organization: School of Engineering and Information Technology, University of New South Wales, Canberra 2600, Australia – sequence: 5 givenname: Mahmudul surname: Hasan fullname: Hasan, Mahmudul organization: School of Chemical and Biomolecular Engineering, The University of Sydney, New South Wales (NSW) 2006, Australia – sequence: 6 givenname: Pronob surname: Das fullname: Das, Pronob organization: Department of Mechanical Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh
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Snippet	•Hybrid solar, wind, biogas with vanadium redox flow battery-based system is studied.•Cost and life cycle emissions are optimised by multi-objective genetic... Renewable hybrid energy systems are well-proven to be capable of supplying reliable power in the remote areas, where grid extension is not viable due to...
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SubjectTerms	Algorithms Alternative energy sources Bangladesh batteries Biogas Carbon dioxide case studies Comparative analysis Computer programs computer software Cost of energy Decision making ecosystem services Electricity electricity costs Emissions energy conversion Energy resources Energy sources Environmental assessment Evolutionary algorithms flow French West Indies Genetic algorithms Hybrid systems hybrids Life cycle emissions Life cycles Multiple objective analysis Objective function Optimization Photovoltaic cells Photovoltaics probability Rechargeable batteries Reliability Renewable energy Software Software development tools solar collectors Sorting algorithms supply Supplying Turbines Vanadium Wind power Wind turbines
Title	Techno-economic and environmental assessment of a hybrid renewable energy system using multi-objective genetic algorithm: A case study for remote Island in Bangladesh
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