Abstract:This paper used some Muti-Criteria Decision Analysis (MCDA) techniques to select the best alternative renewable energy sources in Msallata city, south east of Tripoli, Libya. They were based on the commitment from the ministry of Energy in the Libyan government to lower their carbon footprint. The renewable energy sources considered here are solar, wind, and biomass. MCDA is widely used to solve various decision problems through alternative evaluation. MCDA methods are currently applied in every field and can … Show more
“…Vishnupriyan et al [12] introduced an integrated approach combining AHP and HOMER Energy® simulation to optimize grid-connected renewable energy systems for meeting electricity demand in Tamil Nadu, India, with emphasis on annual optimum tilt photovoltaic systems based on multi-criteria decision analysis. Ali et al [13] evaluated MCDA techniques to select optimal renewable energy sources for Msallata city, Libya, favoring a wind and solar combination, followed by standalone solar, and indicating COPRAS or VIKOR as suitable methods. Indrajayanthan et al [14] addressed India's coal-heavy electricity mix by employing multicriteria decision analysis to evaluate clean energy transition potential across seven key states, identifying Gujarat as the most favorable and Uttar Pradesh as the least conducive.…”
In these days of growing awareness on Renewable Energy Sources and their benefits, there is a major issue that needs to be considered, which is selection of suitable Hybrid Renewable Energy System (HRES) among the vast multitude of choices. In this paper, multiple Multi Criteria Decision Analysis (MCDA) techniques are proposed to select the best among a choice of six HRES Systems using different criteria including but not limited to net present cost (NPC), operating cost, renewability fraction, CO2 & NOx emissions etc. The criteria weights are obtained using Analytical Hierarchy Process (AHP) based on the preference order of the criteria. The decision matrix is obtained from the statistical data of the different HRES and using different MCDA techniques such as Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), rankings are given to the HRES systems based on their closeness to the ideal solution. These rankings are helpful in the selection of suitable HRES configuration for normal household purposes. Since cost aspects are given greater preference, the obtained rankings lean more towards economically affordable solutions without compromising on the number of units generated.
“…Vishnupriyan et al [12] introduced an integrated approach combining AHP and HOMER Energy® simulation to optimize grid-connected renewable energy systems for meeting electricity demand in Tamil Nadu, India, with emphasis on annual optimum tilt photovoltaic systems based on multi-criteria decision analysis. Ali et al [13] evaluated MCDA techniques to select optimal renewable energy sources for Msallata city, Libya, favoring a wind and solar combination, followed by standalone solar, and indicating COPRAS or VIKOR as suitable methods. Indrajayanthan et al [14] addressed India's coal-heavy electricity mix by employing multicriteria decision analysis to evaluate clean energy transition potential across seven key states, identifying Gujarat as the most favorable and Uttar Pradesh as the least conducive.…”
In these days of growing awareness on Renewable Energy Sources and their benefits, there is a major issue that needs to be considered, which is selection of suitable Hybrid Renewable Energy System (HRES) among the vast multitude of choices. In this paper, multiple Multi Criteria Decision Analysis (MCDA) techniques are proposed to select the best among a choice of six HRES Systems using different criteria including but not limited to net present cost (NPC), operating cost, renewability fraction, CO2 & NOx emissions etc. The criteria weights are obtained using Analytical Hierarchy Process (AHP) based on the preference order of the criteria. The decision matrix is obtained from the statistical data of the different HRES and using different MCDA techniques such as Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), rankings are given to the HRES systems based on their closeness to the ideal solution. These rankings are helpful in the selection of suitable HRES configuration for normal household purposes. Since cost aspects are given greater preference, the obtained rankings lean more towards economically affordable solutions without compromising on the number of units generated.
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