By Georgios M. Kopanos, Pei Liu, Michael C. Georgiadis
This e-book presents a systematic framework for built-in options to advanced power difficulties. It adopts a holistic, systems-based method of display the potential for an power structures engineering method of systematically quantify diverse suggestions at quite a few degrees of complexity (technology, plant, strength offer chain, mega-system). using modeling, simulation and optimization-based frameworks, in addition to a couple of real-life purposes, it specializes in complex strength structures together with strength offer chains, built-in biorefineries, power making plans and scheduling ways and concrete power systems.
Featuring contributions from major researchers within the box, this paintings comes in handy for teachers, researchers, practitioners in strength platforms engineering, and all those who find themselves interested in model-based power systems.
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Extra info for Advances in Energy Systems Engineering
Bazilian, M. (2014). Harmonization of initial estimates of shale gas life cycle greenhouse gas emissions for electric power generation. Proceedings of the National Academy of Sciences, 111(31), E3167–E3176. , & Slutz, J. A. (2011). Shale gas water treatment value chain—A review of technologies including case studies. In SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers. Howarth, R. W. (2014). A bridge to nowhere: Methane emissions and the greenhouse gas footprint of natural gas.
34 J. Gao et al. Fig. 4 Superstructure of the “well-to-wire” shale gas supply chain (Gao and You 2015) The resulting problem is a multi-objective, multi-period MINLP problem, which is further solved by applying a tailored global optimization method integrating both the parametric algorithm and branch-and-reﬁne approach. The proposed modeling framework and solution algorithm are demonstrated by a speciﬁc case study based on the Marcellus shale play in southwest PA. By solving this life cycle optimization problem, a Pareto-optimal curve consisting of 10 Pareto optimal solutions is obtained.
The objective is maximizing the expected proﬁt from shale gas production after considering the operating cost for water management. 41 million compared to the heuristic schedule. Notably, this work is later extended by Yang et al. (2015) to optimize the long-term investment decisions using a deterministic MILP model. Multiple design decisions including capacity of water impoundments, pipeline options, treatment technologies and facility locations, as well as the fracturing schedule are addressed.
Advances in Energy Systems Engineering by Georgios M. Kopanos, Pei Liu, Michael C. Georgiadis