Renewable energy sources will play an important role in securing both the energy supply and sustainable development in the future. Renewable energy sources also make a major contribution to the protection of the environment. Gasification is a promising approach for clean and efficient power generation as well as for polygeneration of a variety of products, such as sulphur, hydrogen, methanol, and others (1). Nowadays, gasification is an attractive alternative technology for the thermal treatment of solid waste, such as biomass, scrap tires and sludge. Nevertheless this process is so complex that it is difficult to develop a reliable supervisory technology based only on a chemical-engineering classic-control approach. Particularly the gasifier is difficult to control since it is multivariable and highly non-linear, with significant cross-coupling between the input and output variables. Indeed, in existing gasifiers of this type the automatic control goes no further than closing local PI(D) flow loops around the feed system actuators (2). Because of that exists the opportunity to achieve significantly improved operation by using the modern advanced control techniques.

The use of Artificial-Intelligence (AI) systems seems to be necessary in order to obtain better results in gasification plant management. This term refers in the field of process engineering, to programs and systems, that utilise intelligent implementation techniques such as rule-based expert systems, fuzzy logic and neural networks (NNs), to extend the power of computers beyond the strictly mathematical and statistical functions. Intelligent techniques facilitate the creation of applications that have the ability to collect knowledge and, after reasoning with this knowledge, to resolve complex problems that require a certain degree of intelligence if they have to be solved by a human expert. One important tool in the AI field is the application of ontologies since it permit to represent knowledge about a domain in a form that can be understood and can be communicated between people, and heterogeneous and widely spread application systems. Typically, ontologies are composed of a set of terms representing concepts (hierarchically organized) and some specification of their meaning. (3)

This paper focuses on ontology design and construction as a foundation for knowledge representation in the domain of gasification processes. To illustrate this, the ontology built is applied to model an intelligent system for the distributed control implemented in the bench scale Pilot Plant Gasifier built at the UPC facillities. The ontology constructed can provide the basis for development of an expert system that can function as a decision support system for gasifier operators.

REFERENCES 1. Philcox, J.E., and G.W. Fenner (1996), “Gasification — An Attraction for Chemical Reactions,” Proc., 1996 Gasif. Tech. Conf., Electric Power Research Institute, San Francisco, CA, October 2-4. 2. Pike A. W, et. al., (2000), Application of Modern Simulation Tools to Power Plant Modelling And Analysis: Two Industrial Case Studies. IEE Seminar on Tools for Simulation and Modelling. Pp. 4/1 – 4/22 3. Pinto, H. S. and J. P. Martins 2004. Ontologies: How can they be built? Knowledge and Information Systems. 6:441–464.