Smarter Water Network Operation Management
[EN] Water utilities cannot operate on the basis of a regular business aiming at just increasing sales to increase revenue. They rather have to discourage demand for the sake of environmental and resource sustainability . But, how to discour age demand without affecting the financial viability of ut...
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Zusammenfassung: | [EN] Water utilities cannot operate on the basis of a regular business aiming at just
increasing sales to increase revenue. They rather have to discourage demand for the sake
of environmental and resource sustainability . But, how to discour age demand without
affecting the financial viability of utilities, wh ile keeping a high standard service? It is
one of the main challenges of the twenty first century utility management. Succeeding in
this challenge requires adding a higher level of intelligence into our water systems that
help us identify problems that could a llow for robust mitigation, and give us the
information necessary to decide better, to act quickly and to operate efficiently. Achieving
this in praxis requires efficient numerical techniques and advanced soft computing
algorithms due to the comp lexity of Water Distribution Systems. Design and
refurbishment tasks need the support of multi-objective evolu tionary algorithms able to
deal with conflicting objectives, nonlinear ities, mixed variables and the evaluation of
different working conditions dur ing the decision-making proce ss. Monitoring of service
quality, especially in real-time, will benefit from efficient tec hniques of time series data
treatment. Operation may be integrated into appropriate data structures, which may rely,
in turn, on other types of optimization techniques. These and other use cases are proposed
in this paper to illustrate how utilities can use soft computing for smarter water network
operation management
Montalvo Arango, I.; Izquierdo Sebastián, J.; Herrera Fernández, AM.; Ayala Cabrera, D. (2017). Smarter Water Network Operation Management. International Center for Numerical Methods in Engineering (CIMNE). 1678-1682. http://hdl.handle.net/10251/179964 |
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