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Cooling Water intakes are usually disposed on straight with docks in the planning of the circulation cooling water system of thermal power plants that located on the coast of sea. It is convenient for maintenance of intakes, but is often inconsistent with the programming of docks. Combining with the engineering practice of Kemen Power Plant, this paper discussed the influence on temperature rise due to retraction of water intake to bank by physical model test. The results show that retraction of water intakes makes the distance between intakes and outlets shortened, the water depth nearby shoaled, the buoyant stratification caused by temperature difference weakened and the direct recurrent of hot water increased, so that the temperature rise of intake water would be increased obviously, which is unfavorable to power plant. This study can provide the basis for engineering design and also has reference value to similar projects.

The paper presents neural networks as models for prediction of the water intake. For construction of prediction models three types of neural networks were used: linear network, multi-layer network with error backpropagation and Radial Basis Function network (RBF). The prediction models were compared for obtaining optima quality prognosis. Prediction models were done for working days, Saturdays and Sundays. The research was done for selected nodes of water supply system: detached house node and nodes for 4 hydrophore stations from different pressure areas of water supply system. Models for Sundays were presented in detail. Further research concerning the creation of prognosis models should be directed towards constructing models not only for particular days, but also for the complete week, four seasons of the year: spring, summer, autumn and winter, and finally the entire year.