Intelligent agents for the optimal operation of water distribution pumping stations

Water distribution systems have become increasingly complex and more difficult to operate. With ever increasing regulations and pressure over efficient quality service, the automation of control centers seems to be the objective of the next decades for water utilities. The field of Artificial Intell...

Full description

Autores:
Hernández Cruz, Felipe
Tipo de recurso:
Fecha de publicación:
2010
Institución:
Universidad de los Andes
Repositorio:
Séneca: repositorio Uniandes
Idioma:
eng
OAI Identifier:
oai:repositorio.uniandes.edu.co:1992/11302
Acceso en línea:
http://hdl.handle.net/1992/11302
Palabra clave:
Inteligencia artificial - Investigaciones
Control en tiempo real - Investigaciones
Estaciones de bombeo - Modelos de simulación - Investigaciones
Ingeniería
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description
Summary:Water distribution systems have become increasingly complex and more difficult to operate. With ever increasing regulations and pressure over efficient quality service, the automation of control centers seems to be the objective of the next decades for water utilities. The field of Artificial Intelligence has been exploited to develop online decision support systems that interact directly with pressure and flow sensors as well as with actuators such as valves and pumps. In this thesis, a number of control scenarios are presented, where intelligent agents could be used to further optimize control objectives and provide the operators with reliable tools to make a more efficient use of the available resources. One of these scenarios was selected to be studied further: the real-time operation of pumping stations. Prototype simulators and control agents were implemented in order to assess the potential benefits that these technologies promise. An incremental level of difficulty was used for the agent to first balance between energy and maintenance costs, then to detect and recover from failures, and finally to be able to cope with stochastic demands like those in real systems. As opposed to offline implementations, online agents must deal with a number of additional complications. However, the results show that Artificial Intelligence has indeed a great potential for water distribution automation, welcoming future developments to address this still adolescent research line.