Intelligent optimization of operation schemes for a crude oil pipeline system under a variable-electricity-price policy

Abstract

The crude oil pipeline system, comprising pumps, control valves, and pipelines, is an energy-intensive infrastructure, with pumps being the primary consumers of electricity. The variability in electricity pricing and the need to ensure device safety make it challenging to determine an optimal operational strategy. To address these issues, this study proposes an improved optimization model that integrates safety-constrained device adjustments and time-of-use electricity pricing (including peak and off-peak periods). A hybrid solution method, combining the optimization strategy with sequence, intelligent optimization algorithm and pipeline system simulation, is developed to identify optimal operation schemes. Applied to a 379 km real-world pipeline with 24 pumps and multiple electricity pricing policies, the model outperforms traditional schemes based on average pricing. The results indicate that adopting a night-priority optimization strategy can lead to more efficient all-day operation, and aligning mass flowrates with adjustable device counts significantly enhances energy efficiency. Specifically, when the flowrate varies within 80 %–120 % of the average and four devices are adjustable, the model achieves substantial energy savings. Compared with the idealized average pricing strategy, the optimized scheme reduces energy costs by 7.67 %, yielding annual savings of CNY 11.66 million over the current on-site strategy. Pressure distribution analysis further validates the rationality of the proposed operation scheme.