In this work, we address the simultaneous optimization for the integrated water supply systems scheduling and pump operation to minimize the cost and energy consumption of pumps. The water supply systems are operated to transport water from sources to consumers [1-3]. The operation of the water supply systems is expensive because of large amount of water demands in the industry process and the daily life. Optimal scheduling of the water supply systems helps obtain remarkable savings by coordinating the pumping with time varying electricity tariffs . The characteristics of the pumps can be described by a set of differential equations . A great amount of energy can be saved if the operation of the pumps can be optimized. We integrate and optimize the water supply system scheduling and the pump operation simultaneously. We first formulate the integrated problem into a mixed-integer dynamic optimization (MIDO) model, which is then reformulated into a mixed-integer nonlinear programming (MINLP) full space model by discretizing the differential equations [6-8]. We propose an efficient flexible recipe method which can reduce the computational complexity significantly to solve the integrated problem [9, 10]. The flexible recipe method uses a set of discrete points to approximate the detailed dynamic optimization problems. In case study, we use a real water supply network system to demonstrate the applicability of the proposed full space modeling framework and the efficiency of the flexible recipe solution method.
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