Last years there are efforts to control water supply networks via SCADA systems and sensors for measuring energy consumption, pump operation and losses in water distribution systems. However, most of the existing systems lack optimal management practices. The division of hydraulics and environmental engineering of the faculty of engineering of the Aristotle University of Thessaloniki (AUTH) has developed codes for all types of aquifers and layouts of wells which minimize the energy cost required for water supply using genetic algorithms.
- Installation of a SCADA system combined with mechanical equipment, inverters or electric valves.
- The above mentioned hardware will communicate via telemetry and is required to introduce the genetic algorithms as part of the software of the telemetry system.
- The system aim is to evaluate and give orders to inverters to change the revolutions of pumps and consequently the pumping flow of each well at appropriate time intervals.
- In this way is ensured the minimization of pumping cost and simultaneously the energy needed to overcome friction in pipes, the local losses of the pumps as well as other parts of the distribution network
- In conclusion, the goal is the reduction of total cost required for water supply and the immediate depreciation of the investment for the installation of the system both financially and environmentally.
This technology integrates the guiding principles from both technological and hydraulic aspect to create a smart tool for optimal management of water supply systems.
Stage of development
During the last years, the research team of AUTH has investigated water resources management problems using artificial intelligence methods, analytical solutions and simulation models that use finite elements. The method of genetic algorithms which is inspired by the evolutionary theory and performs the procedures of selection, crossover, mutation and antimetathesis has also been apllied to find optimal solutions in optimization problems with many parameters, variables and constraints. All the aforementioned methods have been applied in theoretical fields and have validated in the laboratory.
Recently a study in a real field of four wells in the area of Thermaikos (Thessaloniki) was made by the research team and the method of genetic algorithms was applied. The results are encouraging as they indicate a reduction of annual pumping cost about 5-10%. This gives new prospects since the research team seeks to create a new project combining software and hardware along with optimization and able to adapt to any type of aquifer and layout of wells to reduce the pumping cost and the energy cost.
Challenge and needs
A potential application of the aquatic intelligence system could take place in the pumping station of a water supply company. Anarchic pumping should be stopped both to reduce energy cost and environmental consequences. This is why there is a need to create optimal operating rules for water supply networks and their implementation. The university can undertake the proposal preparation including the description of the technical requirements of such common project while the affiliate company could implement the project in a real context.
Prior-Art search is planned to be done
Potential markets and targets
- Companies managing water supply systems
- Companies managing irrigation networks
- Farmers interested to reduce the production cost
- Agricultural cooperatives interested to reduce the selling cost for the consumers (farmers)
Potential partners that could co-develop this technology are companies that integrate and implement tools (software, mechanical equipment) in water supply networks such as:
Companies with specialization in electromechanical facilities