04268nam a22006135i 4500 978-3-031-65906-5 DE-He213 20251030112854.0 cr nn 008mamaa 240814s2024 sz | s |||| 0|eng d 9783031659065 978-3-031-65906-5 10.1007/978-3-031-65906-5 doi HD9502-9502.5 JPQB bicssc POL068000 bisacsh JPQB thema Ghadertootoonchi, Alireza. author. aut http://id.loc.gov/vocabulary/relators/aut 82355 Energy System Modeling and Optimization [electronic resource] : A Practical Guide Using Pyomo / by Alireza Ghadertootoonchi, Armaghan  Solaimanian , Mehdi  Davoudi, Moein Moeini Aghtaie. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. IX, 118 p. 50 illus., 36 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda SpringerBriefs in Energy, 2191-5539 Introduction -- How to Use Pyomo -- Electricity System Modeling -- Pyomo Formulation of Electricity System Optimization Problem -- Analyzing Optimization Results. This 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. Energy policy. 61992 Mathematics Data processing. 65715 Programming languages (Electronic computers). 66206 Sustainability. 57661 Engineering mathematics. 64145 Energy System Transformation. 70141 Computational Science and Engineering. 65717 Programming Language. 66208 Sustainability. 57661 Engineering Mathematics. 64145 Solaimanian , Armaghan . author. aut http://id.loc.gov/vocabulary/relators/aut 82356 Davoudi, Mehdi . author. aut http://id.loc.gov/vocabulary/relators/aut 82357 Moeini Aghtaie, Moein. author. aut http://id.loc.gov/vocabulary/relators/aut 82358 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031659058 Printed edition: 9783031659072 SpringerBriefs in Energy, 2191-5539 71992 https://doi.org/10.1007/978-3-031-65906-5 ZDB-2-ENE ZDB-2-SXEN 62473 62473