Abstract
Summary Multiproduct pipelines are the main way of transporting petroleum products, and they have a crucial function in ensuring a consistent supply of energy to downstream consumers. Pipelines carry various oil products using a “back-to-back” method. An effective pump scheduling method can efficiently accomplish the transportation operation while minimizing energy consumption. In this work, we present a method for accurately tracking the operating points of multiproduct pipelines by taking into consideration the physical variations among different oil batches and the impact of complex topography on pressure loss. The proposed approach uses the discrete-time method. We developed a nonlinear integer programming (NIP) model and solved it using a genetic algorithm (GA) for scheduling pumps for multiproduct pipelines. The model takes into consideration batch tracking, flow rate, pressure, and delivery schedule constraints. Ultimately, we successfully applied the developed model in a multiproduct pipeline in China, and confirmed the model’s superiority through comparison with current models. The suggested approach may offer a multiproduct pipeline pump scheduling strategy that is more precise and effective.
Published Version
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