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This paper presents an effort pertaining to the simulation of the future production in Pakistan of different primary energy resources, i.e., coal, natural gas and crude oil, thereby constructing Hubbert peaks. In this context, the past 45 years' production data of primary energy resources of Pakistan have been analyzed and simulated using a generic STELLA (Systems Thinking, Experimental Learning Laboratory with Animation) model. The results show that the Hubbert peak of Pakistan's crude oil production has been somehow already achieved in 2013, with the highest production of 4.52 million toe, which is 1.51 times the production in 2000. Similarly, the natural gas peak production is expected in 2024 with a production of 32.70 million toe which shall be 1.96-fold the extraction of the resource in the year 2000. On the other hand, the coal production in the country has been historically very low and with a constant production rate that is gradually picking up, the peak production year for the coal is anticipated to be in the year 2080 with an estimated production of 134.06 million. Based on the results of this study, which provide a greater understanding of future energy patterns, it is recommended that an energy security policy be devised for the country to ensure sustained supplies in the future. [ABSTRACT FROM AUTHOR]

Energy is crucial in supporting people's daily lives and the continual quest for human development. Due to the associated complexities and uncertainties, decision makers and planners are facing increased pressure to respond more effectively to a number of energy-related issues and conflicts, as well as GHG emission mitigation within the multiple scales of energy management systems (EMSs). This quandary requires a focused effort to resolve a wide range of issues related to EMSs, as well as the associated economic and environmental implications. Effective systems analysis approaches under uncertainty to successfully address interactions, complexities, uncertainties, and changing conditions associated with EMSs is desired, which require a systematic investigation of the current studies on energy systems. Systems analysis and optimization modeling for low-carbon energy systems planning with the consideration of GHG emission reduction under uncertainty is thus comprehensively reviewed in this paper. A number of related methodologies and applications related to: (a) optimization modeling of GHG emission mitigation; (b) optimization modeling of energy systems planning under uncertainty; and (c) model-based decision support tools are examined. Perspectives of effective management schemes are investigated, demonstrating many demanding areas for enhanced research efforts, which include issues of data availability and reliability, concerns in uncertainty, necessity of post-modeling analysis, and usefulness of development of simulation techniques. [ABSTRACT FROM AUTHOR]