Multi-criteria analysis of electricity generation scenarios for sustainable energy planning in Pakistan
The now over a decade-long electricity crisis in Pakistan has adversely affected the socio-economic development of the country. This situation is mainly due to a lack of sustainable energy planning and policy formulation. In this context, energy models can be of great help but only a handful of such...
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my.ump.umpir.232712019-01-03T04:34:04Z http://umpir.ump.edu.my/id/eprint/23271/ Multi-criteria analysis of electricity generation scenarios for sustainable energy planning in Pakistan Mirjat, Nayyar Hussain Uqaili, Mohammad Aslam Harijan, Khanji Mustafa, Mohd Wazir Rahman, Md. Mizanur M., Waris HD28 Management. Industrial Management The now over a decade-long electricity crisis in Pakistan has adversely affected the socio-economic development of the country. This situation is mainly due to a lack of sustainable energy planning and policy formulation. In this context, energy models can be of great help but only a handful of such efforts have been undertaken in Pakistan. Two key shortcomings pertaining to energy models lead to their low utilization in developing countries. First, the models do not effectively make decisions, but rather provide a set of alternatives based on modeling parameters; and secondly, the complexity of these models is often poorly understood by the decision makers. As such, in this study, the Analytical Hierarchy Process (AHP) methodology of Multi-Criteria Decision-Making (MCDM) has been used for the sustainability assessment of energy modeling results for long-term electricity planning. The four scenario alternatives developed in the energy modeling effort, Reference (REF), Renewable Energy Technologies (RET), Clean Coal Maximum (CCM) and Energy Efficiency and Conservation (EEC), have been ranked using the Expert Choice® tool based on the AHP methodology. The AHP decision support framework of this study revealed the EEC scenario as the most favorable electricity generation scenario followed by the REF, RET and CCM scenarios. Besides that, this study proposes policy recommendations to undertake integrated energy modeling and decision analysis for sustainable energy planning in Pakistan. MDPI AG 2018 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/23271/1/Multi-criteria%20analysis%20of%20electricity%20generation%20scenarios%20for%20sustainable%20energy%20planning%20in%20Pakistan.pdf pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/23271/7/Multi-Criteria%20Analysis%20of%20Electricity%20Generation.pdf Mirjat, Nayyar Hussain and Uqaili, Mohammad Aslam and Harijan, Khanji and Mustafa, Mohd Wazir and Rahman, Md. Mizanur and M., Waris (2018) Multi-criteria analysis of electricity generation scenarios for sustainable energy planning in Pakistan. Energies, 11 (4). pp. 1-33. ISSN 1996-1073 https://www.mdpi.com/1996-1073/11/4/757/htm doi:10.3390/en11040757 |
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HD28 Management. Industrial Management Mirjat, Nayyar Hussain Uqaili, Mohammad Aslam Harijan, Khanji Mustafa, Mohd Wazir Rahman, Md. Mizanur M., Waris Multi-criteria analysis of electricity generation scenarios for sustainable energy planning in Pakistan |
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The now over a decade-long electricity crisis in Pakistan has adversely affected the socio-economic development of the country. This situation is mainly due to a lack of sustainable energy planning and policy formulation. In this context, energy models can be of great help but only a handful of such efforts have been undertaken in Pakistan. Two key shortcomings pertaining to energy models lead to their low utilization in developing countries. First, the models do not effectively make decisions, but rather provide a set of alternatives based on modeling parameters; and secondly, the complexity of these models is often poorly understood by the decision makers. As such, in this study, the Analytical Hierarchy Process (AHP) methodology of Multi-Criteria Decision-Making (MCDM) has been used for the sustainability assessment of energy modeling results for long-term electricity planning. The four scenario alternatives developed in the energy modeling effort, Reference (REF), Renewable Energy Technologies (RET), Clean Coal Maximum (CCM) and Energy Efficiency and Conservation (EEC), have been ranked using the Expert Choice® tool based on the AHP methodology. The AHP decision support framework of this study revealed the EEC scenario as the most favorable electricity generation scenario followed by the REF, RET and CCM scenarios. Besides that, this study proposes policy recommendations to undertake integrated energy modeling and decision analysis for sustainable energy planning in Pakistan. |
format |
Article |
author |
Mirjat, Nayyar Hussain Uqaili, Mohammad Aslam Harijan, Khanji Mustafa, Mohd Wazir Rahman, Md. Mizanur M., Waris |
author_facet |
Mirjat, Nayyar Hussain Uqaili, Mohammad Aslam Harijan, Khanji Mustafa, Mohd Wazir Rahman, Md. Mizanur M., Waris |
author_sort |
Mirjat, Nayyar Hussain |
title |
Multi-criteria analysis of electricity generation scenarios for sustainable energy planning in Pakistan |
title_short |
Multi-criteria analysis of electricity generation scenarios for sustainable energy planning in Pakistan |
title_full |
Multi-criteria analysis of electricity generation scenarios for sustainable energy planning in Pakistan |
title_fullStr |
Multi-criteria analysis of electricity generation scenarios for sustainable energy planning in Pakistan |
title_full_unstemmed |
Multi-criteria analysis of electricity generation scenarios for sustainable energy planning in Pakistan |
title_sort |
multi-criteria analysis of electricity generation scenarios for sustainable energy planning in pakistan |
publisher |
MDPI AG |
publishDate |
2018 |
url |
http://umpir.ump.edu.my/id/eprint/23271/1/Multi-criteria%20analysis%20of%20electricity%20generation%20scenarios%20for%20sustainable%20energy%20planning%20in%20Pakistan.pdf http://umpir.ump.edu.my/id/eprint/23271/7/Multi-Criteria%20Analysis%20of%20Electricity%20Generation.pdf http://umpir.ump.edu.my/id/eprint/23271/ https://www.mdpi.com/1996-1073/11/4/757/htm |
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