A parametric rule for planning and management of multiple‐reservoir systems

Abstract

A parametric rule for multireservoir system operation is formulated and tested. It is a generalization of the well‐known space rule of simultaneously accounting for various system operating goals, in addition to the standard goal of avoiding unnecessary spills, including avoiding leakage losses, avoiding conveyance problems, taking into account the impacts of the reservoir system topology, and assuring satisfaction of secondary uses. Theoretical values of the rule's parameters for each one of these isolated goals are derived. In practice, parameters are evaluated to optimize one or more objective functions selected by the user. The rule is embedded in a simulation model so that optimization requires repeated simulations of the system operation with specific values of the parameters each time. The rule is tested on the case of the multireservoir water supply system of the city of Athens, Greece, which is driven by all of the operating goals listed above. Two problems at the system design level are tackled. First, the total release from the system is maximized for a selected level of failure probability. Second, the annual operating cost is minimized for given levels of water demand and failure probability. A detailed simulation model is used in the case study. Sensitivity analysis of the rule's parameters revealed a subset of insensitive parameters that allowed for rule simplification. Finally, the rule is validated through comparison with a number of heuristic rules also applied to the test case. Appendices are available on microfiche. Order from AmericanGeophysical Union, 2000 Florida Avenue, N.W., Washington, DC 20009. Document 97WR01034M; $2.50. Payment must accompany order.

Operação de Reservatório Sergipano via Curvas-Guia Parametrizadas por Modelo de Simulação-Otimização

“…Diante desse contexto, alguns pesquisadores começaram a empregar a simulação e a otimização de maneira conjunta, fazendo surgir a estratégia de parametrização-simulação-otimização (PSO), uma alternativa capaz de fornecer curvasguia e de lidar com a estocasticidade de maneira mais simples do que a PDE [9], [15], [16], [17], [18], [19].…”

Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction

“…In a different way, PSO predefines a rule curve shape and then utilizes optimization algorithms to obtain the combination of rule curve parameters that provides the best reservoir operating performance under possible inflow scenarios or a long inflow series (Nalbantis and Koutsoyiannis, 1997;Oliveira and Loucks, 1997). In this way, most stochastic aspects of the problem, including spatial and temporal correlations of unregulated inflows, are implicitly included, and reservoir rule curves could be derived directly with genetic algorithms and other direct search methods (Koutsoyiannis and Economou, 2003;Labadie, 2004).…”

Source to tap urban water cycle modelling

“…This method has the disadvantage that it requires a large number of control variables, typically the sequences of releases from all reservoirs and for all time steps of the control period. Motivated by this disadvantage, Nalbantis and Koutsoyiannis (1997) recommended an alternative method, the parameterisation-simulation-optimisation (PSO) approach. This method uses a handful of control variables, which are parameters of a simple rule.…”