A fuzzy linear programming model for allocation of oil and gas resources in iran with the aim of reducing the greenhouse gases

Kazemi, Aliyeh; Shakouri, G Hamed; Mehregan, Mohammad Reza; Hosseinzadeh, Mahnaz

doi:10.1002/ep.11692

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…The surplus can be exported. The electricity produced from the power plants can reduce the oil and gas consumption by end users . Rate of GHG emissions is different in each demand sector.…”

Section: Explanation Of the Main Causal Loops Of The Modelmentioning

confidence: 99%

“…Several researchers have studied GHG emissions but they have considered some parts of the energy system of Iran [5][6][7][8][9]. In 2013, a fuzzy programming model was developed by Kazemi et al to allocate the oil and gas resources of Iran optimally to minimize GHG [10]. Nonetheless, because of the existing characteristics of energy systems, this sector is one of the most complicated systems in the world and should be seen holistically [11].…”

Section: Introductionmentioning

confidence: 99%

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Policy analysis of greenhouse gases’ Mitigation in Iran Energy Sector Using System Dynamics Approach

Kazemi

Hosseinzadeh

2016

Env Prog and Sustain Energy

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The present study aims to shed new light in the energy supply planning in Iran by adopting a system dynamics (SD) model, so as to provide a quantitative assessment of each option of supply allocation policy, the long-term greenhouse gases (GHG) emissions' trends of the country as a whole. This paper thus presents the projections of future GHG emissions' trend under various options of supply policies for a time span of 15 years. The GHG emissions are projected to reach 6,20,000 tonnes of carbon dioxide equivalent (TCO 2 e) by the year 2021 if the existing supply policy options are followed. 10 different scenarios considering the major variable of "economic sanctions" -which have recently affected Iran's economy-are developed. By running different scenarios, several fundamental dynamic behaviors can be seen explicitly. The results show that the more allocation of supply resources to the power plants will lessen the GHG emissions in the long run; however this option is quite sensitive to the economic sanctions, so that in case of more economic sanctions, it is not a good decision to be made. More gas injection into the oil reservoirs and less gas exports, is highly efficient in the short term, but its relative effectiveness in not substantial in the long run. Increasing the percentage of oil and gas allocated to the industrial sector, declines cumulative GHG in the long run. The GHG emissions from the power plants' scenario are less in comparison to those from the injection and industry scenarios in the modeling period. However, combined scenarios in the both level of the sanctions are the ideal.

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“…The surplus can be exported. The electricity produced from the power plants can reduce the oil and gas consumption by end users . Rate of GHG emissions is different in each demand sector.…”

Section: Explanation Of the Main Causal Loops Of The Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Policy analysis of greenhouse gases’ Mitigation in Iran Energy Sector Using System Dynamics Approach

Kazemi

Hosseinzadeh

2016

Env Prog and Sustain Energy

Self Cite

View full text Add to dashboard Cite

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“…Jung and Jeong 13 presented a supply‐chain problem having demand uncertainty by incorporating fuzzy optimization modeling. Later, Kazemi et al 14 presented a fuzzy linear programming model for the energy‐saving model for the allocation of oil and gas resources. Similarly, Arikan 15 solved the multi‐objective formulation for minimization of cost, maximization of quality, and on‐time delivery rate by fuzzy mathematical models in supplier selections.…”

Section: Introductionmentioning

confidence: 99%

Multi‐objective optimization for sustainable production planning

Kumawat

Sinha

Chaturvedi

2021

Env Prog and Sustain Energy

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Sustainable production planning can be achieved by including several key factors along with production which affect the environment and economy. Carbon emission and energy consumption are essential factors that need to be reduced for achieving sustainable development. In this article, a methodology is proposed for production planning via several process options using available flexibility in the crisp model formulation. A fuzzy multi‐objective model is formulated for satisfying imprecise goals with a view of minimizing carbon emission and energy consumption in industries. This article addresses the decision making in order to develop a better compromise solution for production planning. For practical planning problems, linear and non‐linear membership functions are used to characterize fuzziness. For nonlinear case, two approaches are proposed with multi‐criteria programming models to deal with empirical data points that is, quadratic approximation and piecewise linear approximation. Three examples are illustrated to show the applicability and purpose of the presented methodologies.

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A fuzzy linear programming model for allocation of oil and gas resources in iran with the aim of reducing the greenhouse gases

Cited by 2 publications

References 7 publications

Policy analysis of greenhouse gases’ Mitigation in Iran Energy Sector Using System Dynamics Approach

Policy analysis of greenhouse gases’ Mitigation in Iran Energy Sector Using System Dynamics Approach

Multi‐objective optimization for sustainable production planning

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