Publication

Optimization of an SOFC-based decentralized polygeneration system for providing energy services in an office-building in Tokyo

Daniel Favrat
2004
Conference Papers

Abstract

The electricity demands of buildings for cooling and heating, as well as for office-appliances such as computers, lighting, elevators, keep increasing [Uchiyama2002]. This increase in electricity requirement is directly accompanied by an increase in CO2-emissions. Decentralized energy conversion systems are believed to bring a solution to this ecological problem. In order to assess the ecological and economical performances of such systems, we have developped a set of integrated thermo-environomic models and evaluated the performances of the system in terms of costs and CO2-emissions of a decentralized system, using a hybrid multi-objective optimisation procedure that combines a linear programming problem and a multi-objective optimizer based on evolutionary algorithm (MOO)

Official source

https://infoscience.epfl.ch/entities/publication/29f528f0-dcee-48c0-b8e7-9da628a98348

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Daniel Favrat
2004
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/29f528f0-dcee-48c0-b8e7-9da628a98348

About this result

Related concepts (32)

Multi-objective optimization

Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute optimization) is an area of multiple-criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. Multi-objective is a type of vector optimization that has been applied in many fields of science, including engineering, economics and logistics where optimal decisions need to be taken in the presence of trade-offs between two or more conflicting objectives.

Genetic algorithm

In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover and selection. Some examples of GA applications include optimizing decision trees for better performance, solving sudoku puzzles, hyperparameter optimization, causal inference, etc.

Electricity market

In a broad sense, an electricity market is a system that facilitates the exchange of electricity-related goods and services. During more than a century of evolution of the electric power industry, the economics of the electricity markets had undergone enormous changes for reasons ranging from the technological advances on supply and demand sides to politics and ideology.

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Optimization of an SOFC-based decentralized polygeneration system for providing energy services in an office-building in Tokyo

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