The exploitation of solar power for energy supply is of increasing importance. While technical development mainly takes place in the engineering disciplines, computer science offers adequate techniques for simulation, optimisation and controller synthesis. In this paper we describe a work from this interdisciplinary area. We introduce our tool for the optimisation of parameterised solar thermal power plants, and report on the employment of genetic algorithms and neural networks for parameter synthesis. Experimental results show the applicability of our approach
The paper presents results from the first phase of a research project carried out at the solar power...
A solar community of 100 residential houses was optimized for Finnish conditions with the aim of ach...
Predicting complex systems like Renewable Energy Sources depending nonlinearly on several physical p...
Abstract. The exploitation of solar power for energy supply is of in-creasing importance. While tech...
The objective of this work is to use artificial intelligence methods, like artificial neural-network...
The objective of this work is to use artificial intelligence methods for the optimal design of solar...
In this chapter, two of the most important artificial intelligence techniques are presented together...
In this context, the optimization of photovoltaic energy production is studied and presented. In ord...
This paper deals with the problem of finding the optimum load allocation on machines and apparatuses...
In this context, the optimization of photovoltaic energy production is studied and presented. In ord...
The present thesis approaches the improvement of the performance metrics of industrially fabricated ...
This paper introduces a hybrid evolutionary optimization algorithm as a tool for training an Artific...
In recent years, there has been a growing interest in using artificial intelligence (AI) techniques ...
Solar thermal electricity technologies are attractive alternatives to produce electricity by means o...
Practical successes have been achieved with neural network models in a variety of domains, inc...
The paper presents results from the first phase of a research project carried out at the solar power...
A solar community of 100 residential houses was optimized for Finnish conditions with the aim of ach...
Predicting complex systems like Renewable Energy Sources depending nonlinearly on several physical p...
Abstract. The exploitation of solar power for energy supply is of in-creasing importance. While tech...
The objective of this work is to use artificial intelligence methods, like artificial neural-network...
The objective of this work is to use artificial intelligence methods for the optimal design of solar...
In this chapter, two of the most important artificial intelligence techniques are presented together...
In this context, the optimization of photovoltaic energy production is studied and presented. In ord...
This paper deals with the problem of finding the optimum load allocation on machines and apparatuses...
In this context, the optimization of photovoltaic energy production is studied and presented. In ord...
The present thesis approaches the improvement of the performance metrics of industrially fabricated ...
This paper introduces a hybrid evolutionary optimization algorithm as a tool for training an Artific...
In recent years, there has been a growing interest in using artificial intelligence (AI) techniques ...
Solar thermal electricity technologies are attractive alternatives to produce electricity by means o...
Practical successes have been achieved with neural network models in a variety of domains, inc...
The paper presents results from the first phase of a research project carried out at the solar power...
A solar community of 100 residential houses was optimized for Finnish conditions with the aim of ach...
Predicting complex systems like Renewable Energy Sources depending nonlinearly on several physical p...