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020 _a9783031659065
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024 7 _a10.1007/978-3-031-65906-5
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050 4 _aHD9502-9502.5
072 7 _aJPQB
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072 7 _aPOL068000
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072 7 _aJPQB
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100 1 _aGhadertootoonchi, Alireza.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_982355
245 1 0 _aEnergy System Modeling and Optimization
_h[electronic resource] :
_bA Practical Guide Using Pyomo /
_cby Alireza Ghadertootoonchi, Armaghan  Solaimanian , Mehdi  Davoudi, Moein Moeini Aghtaie.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aIX, 118 p. 50 illus., 36 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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490 1 _aSpringerBriefs in Energy,
_x2191-5539
505 0 _aIntroduction -- How to Use Pyomo -- Electricity System Modeling -- Pyomo Formulation of Electricity System Optimization Problem -- Analyzing Optimization Results.
520 _aThis brief serves as a comprehensive and practical guide to energy system optimization utilizing the Pyomo optimization package in Python. It thoroughly explains the mathematical foundations of energy system technologies and how to employ Pyomo for addressing optimization challenges. The book highlights the significance of energy system optimization in terms of economic and environmental impacts, followed by a detailed exploration of Pyomo, an advanced mathematical programming language. It covers a wide spectrum of problem types, introducing various open-source solvers and outlining the steps involved in developing Python-based Pyomo code to solve optimization problems. Furthermore, the book provides mathematical formulations and Python code for diverse energy technologies, including thermal power plants, renewable energy sources like wind and solar, power transmission lines, and electricity storage systems. It also discusses topics like reliability, load loss, demand-side flexibility, and linearization techniques. To demonstrate practical application, the book offers a case study that progressively builds in complexity, guiding readers in optimizing intricate energy systems based on the models and constraints explained earlier. Targeted at professionals, researchers, and students, it is suitable for those with a foundational understanding of Python and mathematical optimization, and it underscores the crucial role of energy system optimization in addressing contemporary energy sector concerns such as environmental impact reduction and sustainable development.
650 0 _aEnergy policy.
_961992
650 0 _aMathematics
_xData processing.
_965715
650 0 _aProgramming languages (Electronic computers).
_966206
650 0 _aSustainability.
_957661
650 0 _aEngineering mathematics.
_964145
650 1 4 _aEnergy System Transformation.
_970141
650 2 4 _aComputational Science and Engineering.
_965717
650 2 4 _aProgramming Language.
_966208
650 2 4 _aSustainability.
_957661
650 2 4 _aEngineering Mathematics.
_964145
700 1 _aSolaimanian , Armaghan .
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_982356
700 1 _aDavoudi, Mehdi .
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_982357
700 1 _aMoeini Aghtaie, Moein.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_982358
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031659058
776 0 8 _iPrinted edition:
_z9783031659072
830 0 _aSpringerBriefs in Energy,
_x2191-5539
_971992
856 4 0 _uhttps://doi.org/10.1007/978-3-031-65906-5
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912 _aZDB-2-SXEN
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