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Multi-objective optimization for sustainable development of the power sector: An economic, environmental, and social analysis of Iran

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  • Atabaki, Mohammad Saeid
  • Aryanpur, Vahid

Abstract

This paper aims to analyze Iran's long-term power sector development from economic, environmental, social, and sustainable perspectives. For this purpose, a linear programming model is developed, which includes three objective functions: minimization of costs, minimization of CO2 emissions, and maximization of created jobs. To provide a sustainable plan, analytical hierarchy process is employed to allocate expert-based weights to the objective functions. Moreover, to support the decision-makers, Pareto-optimal alternatives are explored by varying the weights of objectives. The multi-objective model is solved by applying a weighted method based on fuzzy membership functions. The results show that a sustainable scenario leads to high technology diversification. Furthermore, the combined cycle would be the dominant option in Iran's long-term generation mix. In addition, power generation from non-hydro renewables, solar PV in particular, should grow faster than the total electricity demand. The findings indicate that the economic scenario fulfills Iran's commitment to 4% reduction of emissions compared to the current trend; however, the sustainable and environmental scenarios would cause achievement of the superior 12% reduction goal. Multi-objective analysis shows that moving away from one's objective optimum value leads to significant improvements in other objective values.

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  • Atabaki, Mohammad Saeid & Aryanpur, Vahid, 2018. "Multi-objective optimization for sustainable development of the power sector: An economic, environmental, and social analysis of Iran," Energy, Elsevier, vol. 161(C), pages 493-507.
    • Handle: RePEc:eee:energy:v:161:y:2018:i:c:p:493-507
    DOI: 10.1016/j.energy.2018.07.149
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