A hierarchical genetic algorithm and mixed-integer linear programming-based stochastic optimization of the configuration of integrated trigeneration energy systems

Facing the growing pressure of climate change and environmental protection, integrated energy systems (IESs), which comprise different energy sources, have become promising candidates for future energy systems. However, the capacity configuration of each source remains challenging due to the various...

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Vydáno v:	Clean technologies and environmental policy Ročník 23; číslo 6; s. 1913 - 1927
Hlavní autoři:	Zhang, Yisong, Jiang, Jingjing, Zhang, Xian, Sun, Li
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2021 Springer Nature B.V
Témata:	Algorithms Candidates Climate change Configurations Cooling Cost reduction Costs Couplings Earth and Environmental Science Energy Energy sources Environment Environmental Economics Environmental Engineering/Biotechnology Environmental policy Environmental protection Genetic algorithms Genetics Heat storage Heating Hierarchies Industrial and Production Engineering Industrial Chemistry/Chemical Engineering Integer programming Integrated energy systems Linear programming Mathematical analysis Mixed integer Monte Carlo simulation Operating costs Optimization Original Paper Randomness Renewable resources Resource availability Sampling Storage Sustainable Development Stochastic optimization Genetic algorithm IES Economic evaluation MILP problem
ISSN:	1618-954X, 1618-9558
On-line přístup:	Získat plný text
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