04092nam a22005655i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001800172072001700190072002300207072001600230100009500246245020500341250001800546264006900564300006400633336002600697337002600723338003600749347002400785490004100809505016700850520159101017650002602608650004102634650005702675650002702732650003602759650004102795650005002836650003302886650002702919650003602946700009502982700008603077700009103163710003403254773002603288776003603314776003603350830004803386856004603434912001403480912001503494999001703509978-3-031-65906-5DE-He21320251030112854.0cr nn 008mamaa240814s2024    sz |    s    |||| 0|eng d  a97830316590659978-3-031-65906-57 a10.1007/978-3-031-65906-52doi 4aHD9502-9502.5 7aJPQB2bicssc 7aPOL0680002bisacsh 7aJPQB2thema1 aGhadertootoonchi, Alireza.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut98235510aEnergy System Modeling and Optimizationh[electronic resource] :bA Practical Guide Using Pyomo /cby Alireza Ghadertootoonchi, Armaghan  Solaimanian , Mehdi  Davoudi, Moein Moeini Aghtaie.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aIX, 118 p. 50 illus., 36 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aSpringerBriefs in Energy,x2191-55390 aIntroduction -- How to Use Pyomo -- Electricity System Modeling -- Pyomo Formulation of Electricity System Optimization Problem -- Analyzing Optimization Results.  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. 0aEnergy policy.961992 0aMathematicsxData processing.965715 0aProgramming languages (Electronic computers).966206 0aSustainability.957661 0aEngineering mathematics.96414514aEnergy System Transformation.97014124aComputational Science and Engineering.96571724aProgramming Language.96620824aSustainability.95766124aEngineering Mathematics.9641451 aSolaimanian , Armaghan .eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut9823561 aDavoudi, Mehdi .eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut9823571 aMoeini Aghtaie, Moein.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut9823582 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303165905808iPrinted edition:z9783031659072 0aSpringerBriefs in Energy,x2191-553997199240uhttps://doi.org/10.1007/978-3-031-65906-5  aZDB-2-ENE  aZDB-2-SXEN  c62473d62473