Operators of liquid pipeline networks with multiple pumping stations are looking for ways to optimize operations, reduce fuel consumption and costs, and maximize producer and consumer throughput in real time. This paper introduces a different method for optimal pipeline operation and achieves the stated objectives by integrating a real-time based optimization algorithm into a configured, dynamic model to predict how the pipeline stations and units will respond to changes in each of the independent variables along the pipeline. The real-time optimization focuses on the different costs of operation as they change throughout the day and drag reducing agents cost and give suggested set points of pump operation as well as drag reducing agent set points. Through this method a prediction of future moves and a process operating forecast can be built to maintain optimal operations in accordance with a defined target. Drag reducing agent and batch algorithms and the simulator results were validated with real field data from a liquid pipeline to ensure model and simulation accuracy. Technological advances incorporated into the pipeline simulator included advanced regulatory control, drag reduction, batching and incorporating algorithms for daily timed operations (differences in electrical costs throughout the day). This paper describes our method and these advances and demonstrates how they may be applied to liquid pipelines to see current operating modes versus suggested operating modes.

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