Fuzzy Logic Applied To Long Term Management Of Water Resource Systems
Since the origins of history, irrigation of agricultural lands has been reported to be an activity of great concern for many human societies. At the beginning, natural irrigation systems such as the Nile River flowing through the sands of Egypt have provided to neighbouring populations some amenities in their hard life. However irregular cycles of floods and droughts were a serious impediment to permanent settlements and to a continuous improvement of life conditions. Consequently human ingenuity has been continuously challenged by the development of new ways and means to master water resource system (WRS). During the last century, improved civil engineering techniques and the development of digital control systems and techniques have dramatically increased the power of human societies over their water resources. However many problems, which received some attention in the past, now require new approaches, given the steady increase in water demand and the introduction of environmental conservation considerations. Today, intelligent systems techniques appear to be able to give some insight in this direction by improving the efficiency of the different decision steps involved in the management and control of such systems. This paper focuses on the problem of the long-term management of a water resource system composed of a network of dams and river reaches. This system is viewed as a hybrid dynamic system, called here a storage/transfer/distribution system. The main long-term management objective of such a system is to manage reserves and releases so as to minimise the deficit between supply and demand by taking into account predictions of demand and contributions. Thus, in the present context of water resource scarcity, a complete approach for long-term management of a storage/transfer/distribution system is proposed. To take into account major uncertainties related to the operations of this kind of system, a sliding horizon approach (it consists of readjusting each week the release plan over the whole coming year, according to the present reserves, the most recent long-term demand estimation and the programmed release for the next week). In addition, an adaptation procedure of weighting parameters of the minimisation criterion based on fuzzy logic is implemented. The definition of an optimisation objective function is in this case a very intricate question since it involves competition, uncertainty and geographical dispersion. However, it is crucial to guarantee the quality of long-term management. This is why Fuzzy Logic is used as a particularly appropriate means to refine on-line the formulation of the objective function of the recurrent optimisation problem. Fuzzy Logic is also shown to be very useful in defining what is at stake in the long-term management. This criterion adaptation concept seems judicious, in view of the difficulty of defining the weighting parameters of such optimisation problems and their influence on the relevant solution obtained. The long-term management problem is solved with improved heuristics using linear programming and dynamic programming in order to reduce the effects of spatial discretisation, which is so restrictive in this context. The suggested approach is applied to a case study, which highlights its relative simplicity of implementation.